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An Introduction to Psychological Science
An Introduction to Psychological Science Second Canadian Edition
Mark Krause Southern Oregon University Daniel Corts Augustana College Stephen Smith University of Winnipeg Dan Dolderman University of Toronto
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978-0-13-430220-1
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library and archives canada cataloguing in Publication
Krause, Mark A. (Mark Andrew), 1971-, author
An introduction to psychological science / Mark Krause, Daniel Corts, Stephen Smith, Dan Dolderman. — Second Canadian edition.
Includes bibliographical references and index.
ISBN 978-0-13-430220-1 (hardback)
1. Psychology—Textbooks. I. Corts, Daniel Paul, 1970-, author II. Smith, Stephen D. (Stephen Douglas), 1974-, author III. Dolderman, Dan, 1972-, author IV. Title.
BF121.K73 2017 150 C2016-906938-9
For Andrea and Finn. Both of you fuel my passion and motivation for this endeavor.
I cannot thank you enough.
Mark Krause
To Kim, Sophie, and Jonah, for your patience, understanding, and forgiveness during all the hours this project has occupied me.
Dan Corts
To my brilliant wife, Jenn, and our hilarious children, Oliver and Clara. Thank you for putting up with me.
Stephen Smith
To my children, Alexandra, Kate, and Geoff, who love this world so deeply. And to my mother, who has had a huge impact on my life.
Dan Dolderman
Brief Contents 1 Introducing Psychological Science 1
2 Reading and Evaluating Scientific Research 29
3 Biological Psychology 71
4 Sensation and Perception 125
5 Consciousness 180
6 Learning 227
7 Memory 270
8 Thought and Language 313
9 Intelligence Testing 349
10 Lifespan Development 385
11 Motivation and Emotion 439
12 Personality 490
13 Social Psychology 531
14 Health, Stress, and Coping 578
15 Psychological Disorders 614
16 Therapies 653
Contents About the Authors xvii
About the Canadian Authors xvii
From the Authors xviii
Content and Features xxi
For Instructors xxvi
Acknowledgments xxviii
1 Introducing Psychological Science 1 Module 1.1 The Science of Psychology 2
The Scientific Method 3 Hypotheses: Making Predictions 3
Theories: Explaining Phenomena 4
The Biopsychosocial Model 5
Building Scientific Literacy 6
Working the Scientific Literacy Model: Planning When to Study 7 Critical Thinking, Curiosity, and a Dose of Healthy Skepticism 8
Myths in Mind Abducted by Aliens! 9
Summary 10
Module 1.2 How Psychology Became a Science 11 Psychology’s Philosophical and Scientific Origins 12
Influences from the Ancients: Philosophical Insights into
Behaviour 12
Influences from Physics: Experimenting with the Mind 13
Influences from Evolutionary Theory: The Adaptive Functions of Behaviour 13
Influences from Medicine: Diagnoses and Treatments 15
The Influence of Social Sciences: Measuring and Comparing Humans 16
The Beginnings of Contemporary Psychology 18 Structuralism and Functionalism: The Beginnings of Psychology 18
The Rise of Behaviourism 19
Radical Behaviourism 20
Humanistic Psychology Emerges 21
The Brain and Behaviour 21
The Cognitive Revolution 21
Social and Cultural Influences 23
Emerging Themes in Psychology 24 Psychology of Women 24
Comparing Cultures 25
The Neuroimaging Explosion 25
The Search for the Positive 26
Psychology in the Real World 26
Summary 28
2 Reading and Evaluating Scientific Research 29
Module 2.1 Principles of Scientific Research 30 Five Characteristics of Quality Scientific Research 31
Scientific Measurement: Objectivity 31
Scientific Measurement: Reliability, and Validity 32
Generalizability of Results 33
Sources of Bias in Psychological Research 34
Working the Scientific Literacy Model: Demand Characteristics and Participant Behaviour 35
Techniques That Reduce Bias 36
Sharing the Results 37
Psych@ The Hospital: The Placebo Effect 37 Replication 38
Five Characteristics of Poor Research 39
Summary 41
Module 2.2 Scientific Research Designs 42 Descriptive Research 43
Case Studies 43
Working the Scientific Literacy Model: Case Studies as a Form of Scientific Research 44
Naturalistic Observation 45
Surveys and Questionnaires 46
Correlational Research 47
Myths in Mind Beware of Illusory Correlations 48
Experimental Research 49 The Experimental Method 49
The Quasi-Experimental Method 50
Converging Operations 50
Summary 51
Module 2.3 Ethics in Psychological Research 53 Promoting the Welfare of Research Participants 54
Weighing the Risks and Benefits of Research 54
Obtaining Informed Consent 55
The Right to Anonymity and Confidentiality 56
The Welfare of Animals in Research 56
Working the Scientific Literacy Model: Animal Models of Disease 57 REBs for Animal-Based Research 59
Ethical Collection, Storage, and Reporting of Data 59
Summary 61
Module 2.4 A Statistical Primer 62 Descriptive Statistics 63
Frequency 63
Central Tendency 63
Variability 65
Hypothesis Testing: Evaluating the Outcome of a Study 66
Working the Scientific Literacy Model: Statistical Significance 68
Summary 70
3 Biological Psychology 71 Module 3.1 Genetic and Evolutionary Perspectives on Behaviour 72
Heredity and Behaviour 73 The Genetic Code 73
Behavioural Genomics: The Molecular Approach 75
Behavioural Genetics: Twin and Adoption Studies 75
Myths in Mind Single Genes and Behaviour 76 Gene Expression and Behaviour 78
Evolutionary Insights into Human Behaviour 79 Evolutionary Psychology 80
Working the Scientific Literacy Model: Hunters and Gatherers: Men, Women, and Spatial Memory 81
Sexual Selection and Evolution 83
BIOPSYCHOSOCIAL PERSPECTIVES Sexual Selection and the Colour Red 84
Summary 86
Module 3.2 How the Nervous System Works: Cells and Neurotransmitters 88
Neural Communication 89 The Neuron 89
Myths in Mind We Are Born with All the Brain Cells We Will Ever Have 90
Glial Cells 91
The Neuron’s Electrical System: Resting and Action Potentials 91
The Chemical Messengers: Neurotransmitters and Hormones 93 Types of Neurotransmitters 94
Drug Effects on Neurotransmission 95
Hormones and the Endocrine System 96
Working the Scientific Literacy Model: Testosterone and Aggression 97 Neurons in Context 99
Summary 100
Module 3.3 Structure and Organization of the Nervous System 101 Divisions of the Nervous System 102
The Central Nervous System 102
The Peripheral Nervous System 102
The Brain and Its Structures 104 The Hindbrain: Sustaining the Body 104
The Midbrain: Sensation and Action 105
The Forebrain: Emotion, Memory, and Thought 106
The Cerebral Cortex 108
The Four Lobes 108
Left Brain, Right Brain: Hemispheric Specialization 111
Psych@ The Gym 111 The Changing Brain: Neuroplasticity 112
Working the Scientific Literacy Model: Neuroplasticity and Recovery from Brain Injury 113
Summary 115
Module 3.4 Windows to the Brain: Measuring and Observing Brain Activity 116
Insights from Brain Damage 117 Lesioning and Brain Stimulation 117
Structural and Functional Neuroimaging 119 Structural Neuroimaging 119
Functional Neuroimaging 120
Working the Scientific Literacy Model: Functional MRI and Behaviour 122
Summary 124
4 Sensation and Perception 125 Module 4.1 Sensation and Perception at a Glance 126
Sensing the World Around Us 127 Stimulus Thresholds 129
Signal Detection 130
Priming and Subliminal Perception 131
Myths in Mind Setting the Record Straight on Subliminal Messaging 131
Perceiving the World Around Us 132 Gestalt Principles of Perception 132
Working the Scientific Literacy Model: Backward Messages in Music 134
Attention and Perception 136
Summary 137
Module 4.2 The Visual System 139 The Human Eye 140
How the Eye Gathers Light 140
The Structure of the Eye 141
The Retina: From Light to Nerve Impulse 142
The Retina and the Perception of Colours 144
Common Visual Disorders 145
Visual Perception and the Brain 146 The Ventral Stream 148
Working the Scientific Literacy Model: Are Faces Special? 148 The Dorsal Stream 151
Depth Perception 152
Psych@ The Artist’s Studio 153
Summary 155
Module 4.3 The Auditory and Vestibular Systems 156 Sound and the Structures of the Ear 157
Sound 157
The Human Ear 157
The Perception of Sound 160 Sound Localization: Finding the Source 160
Theories of Pitch Perception 160
Auditory Perception and the Brain 161
The Perception of Music 162
Working the Scientific Literacy Model: The Perception of Musical Beats 162
The Vestibular System 164 Sensation and the Vestibular System 164
The Vestibular System and the Brain 165
Summary 165
Module 4.4 Touch and the Chemical Senses 167 The Sense of Touch 168
Feeling Pain 169
Working the Scientific Literacy Model: Empathy and Pain 171 Phantom Limb Pain 172
The Chemical Senses: Taste and Smell 173 The Gustatory System: Taste 173
The Olfactory System: Smell 175
Multimodal Integration 176 What Is Multimodal Integration? 176
Synesthesia 177
Summary 178
5 Consciousness 180 Module 5.1 Biological Rhythms of Consciousness: Wakefulness and Sleep 181
What Is Sleep? 182 Biological Rhythms 182
The Stages of Sleep 184
Why Do We Need Sleep? 186 Theories of Sleep 186
Sleep Deprivation and Sleep Displacement 187
Theories of Dreaming 190 The Psychoanalytic Approach 190
The Activation– Synthesis Hypothesis 190
Working the Scientific Literacy Model: Dreams, REM Sleep, and Learning 191
Disorders and Problems with Sleep 193 Insomnia 193
Nightmares and Night Terrors 194
Movement Disturbances 194
Sleep Apnea 195
Narcolepsy 196
Overcoming Sleep Problems 196
Summary 197
Module 5.2 Altered States of Consciousness: Hypnosis, Mind- Wandering, and Disorders of Consciousness 199
Hypnosis 200 Theories of Hypnosis 200
Applications of Hypnosis 201
Myths in Mind Recovering Lost Memories through Hypnosis 202
Mind-Wandering 203 What Is Mind-Wandering? 203
Mind-Wandering and the Brain 203
The Benefits of Mind-Wandering 204
Disorders of Consciousness 205
Working the Scientific Literacy Model: Assessing Consciousness in the Vegetative State 207
Summary 210
Module 5.3 Drugs and Conscious Experience 211 Physical and Psychological Effects of Drugs 212
Short-Term Effects 212
Long-Term Effects 213
Commonly Abused “Recreational” Drugs 215 Stimulants 215
Hallucinogens 217
Marijuana 218
BIOPSYCHOSOCIAL PERSPECTIVES Recreational and Spiritual Uses of Salvia Divinorum 219 Working the Scientific Literacy Model: Marijuana, Memory, and Cognition 219
Opiates 221
Legal Drugs and Their Effects on Consciousness 222 Sedatives 222
Prescription Drug Abuse 222
Alcohol 224
Why Are Some Drugs Legal and Others Illegal? 224
Psych@ University Parties 224
Summary 226
6 Learning 227 Module 6.1 Classical Conditioning: Learning by Association 228
Pavlov’s Dogs: Classical Conditioning of Salivation 229 Evolutionary Function of the CR 231
Classical Conditioning and the Brain 231
Processes of Classical Conditioning 233 Acquisition, Extinction, and Spontaneous Recovery 233
Stimulus Generalization and Discrimination 234
Applications of Classical Conditioning 235 Conditioned Emotional Responses 235
Evolutionary Role for Fear Conditioning 236
Conditioned Taste Aversions 237
Working the Scientific Literacy Model: Conditioning and Negative Political Advertising 239
Drug Tolerance and Conditioning 241
Summary 242
Module 6.2 Operant Conditioning: Learning through Consequences 244 Basic Principles of Operant Conditioning 245
Reinforcement and Punishment 245
Positive and Negative Reinforcement and Punishment 247
Shaping 248
Applying Operant Conditioning 248
Processes of Operant Conditioning 249 Primary and Secondary Reinforcers 249
Discrimination and Generalization 250
Delayed Reinforcement and Extinction 251
Reward Devaluation 251
Reinforcement Schedules and Operant Conditioning 252 Schedules of Reinforcement 252
Psych@ Never Use Multiline Slot Machines 254
Working the Scientific Literacy Model: Reinforcement and Superstition 255
Applying Punishment 256
Are Classical and Operant Learning Distinct Events? 257
Summary 258
Module 6.3 Cognitive and Observational Learning 260 Cognitive Perspectives on Learning 261
Latent Learning 261
S-O-R Theory of Learning 262
Observational Learning 262 Processes Supporting Observational Learning 263
Myths in Mind Is Teaching Uniquely Human? 264 Imitation and Mirror Neurons 265
Working the Scientific Literacy Model: Linking Media Exposure to Behaviour 265
BIOPSYCHOSOCIAL PERSPECTIVES Violence, Video Games, and Culture 268
Summary 269
7 Memory 270 Module 7.1 Memory Systems 271
The Atkinson-Shiffrin Model 272 Sensory Memory 273
Short-Term Memory and the Magical Number 7 274
Long-Term Memory 275
Working the Scientific Literacy Model: Distinguishing Short-Term from Long-Term Memory Stores 276
The Working Memory Model: An Active STM System 279 The Phonological Loop 280
The Visuospatial Sketchpad 280
The Episodic Buffer 281
The Central Executive 281
Working Memory: Putting the Pieces Together 281
Long-Term Memory Systems: Declarative and Nondeclarative Memories 282
Declarative Memory 282
Nondeclarative Memory 283
The Cognitive Neuroscience of Memory 283 Memory at the Cellular Level 283
Memory, the Brain, and Amnesia 284
Stored Memories and the Brain 285
Summary 287
Module 7.2 Encoding and Retrieving Memories 288 Encoding and Retrieval 289
Rehearsal: The Basics of Encoding 289
Levels of Processing 290
Retrieval 290
Working the Scientific Literacy Model: Context-Dependent Memory 291 State-Dependent Memory 294
Mood-Dependent Memory 294
Emotional Memories 295 Flashbulb Memories 296
Myths in Mind The Accuracy of Flashbulb Memories 297
Forgetting and Remembering 298 The Forgetting Curve: How Soon We Forget … 298
Mnemonics: Improving Your Memory Skills 298
Summary 301
Module 7.3 Constructing and Reconstructing Memories 302 How Memories Are Organized and Constructed 303
The Schema: An Active Organization Process 303
Working the Scientific Literacy Model: How Schemas Influence Memory 303
BIOPSYCHOSOCIAL PERSPECTIVES Your Earliest Memories 305
Memory Reconstruction 306 The Perils of Eyewitness Testimony 306
Psych@ Court: Is Eyewitness Testimony Reliable? 308 Imagination and False Memories 308
Creating False Memories in the Laboratory 309
The Danger of False Remembering 310
Summary 312
8 Thought and Language 313 Module 8.1 The Organization of Knowledge 314
Concepts and Categories 315 Classical Categories: Definitions and Rules 315
Prototypes: Categorization by Comparison 315
Networks and Hierarchies 316
Working the Scientific Literacy Model: Priming and Semantic Networks 318
Memory, Culture, and Categories 319 Categorization and Experience 319
Categories, Memory, and the Brain 320
BIOPSYCHOSOCIAL PERSPECTIVES Culture and Categorical Thinking 321
Myths in Mind How Many Words for Snow? 322 Categories and Culture 322
Summary 323
Module 8.2 Problem Solving, Judgment, and Decision Making 324 Defining and Solving Problems 325
Problem-Solving Strategies and Techniques 325
Cognitive Obstacles 326
Psych@ Problem Solving and Humour 327
Judgment and Decision Making 328 Conjunction Fallacies and Representativeness 328
The Availability Heuristic 329
Anchoring and Framing Effects 330
Belief Perseverance and Confirmation Bias 331
Working the Scientific Literacy Model: Maximizing and Satisficing in Complex Decisions 332
Summary 335
Module 8.3 Language and Communication 336 What Is Language? 337
Early Studies of Language 337
Properties of Language 338
Phonemes and Morphemes: The Basic Ingredients of Language 339
Syntax: The Language Recipe 339
Pragmatics: The Finishing Touches 340
The Development of Language 341 Infants, Sound Perception, and Language Acquisition 341
Producing Spoken Language 342
Sensitive Periods for Language 342
The Bilingual Brain 343
Genes, Evolution, and Language 344
Working the Scientific Literacy Model: Genes and Language 344 Can Animals Use Language? 346
Summary 348
9 Intelligence Testing 349 Module 9.1 Measuring Intelligence 350
Different Approaches to Intelligence Testing 351 Intelligence and Perception: Galton’s Anthropometric Approach 351
Intelligence and Thinking: The Stanford– Binet Test 352
The Wechsler Adult Intelligence Scale 353
Raven’s Progressive Matrices 355
The Checkered Past of Intelligence Testing 356 IQ Testing and the Eugenics Movement 356
The Race and IQ Controversy 357
Problems with the Racial Superiority Interpretation 358
Working the Scientific Literacy Model: Beliefs about Intelligence 358
Summary 361
Module 9.2 Understanding Intelligence 362 Intelligence as a Single, General Ability 363
Spearman’s General Intelligence 363
Does G Tell Us the Whole Story? 364
Intelligence as Multiple, Specific Abilities 365 The Hierarchical Model of Intelligence 365
Working the Scientific Literacy Model: Testing for Fluid and Crystallized Intelligence 366
Sternberg’s Triarchic Theory of Intelligence 368
Myths in Mind Learning Styles 369 Gardner’s Theory of Multiple Intelligences 369
Psych@ The NFL Draft 370
The Battle of the Sexes 371 Do Males and Females have Unique Cognitive Skills? 372
Summary 373
Module 9.3 Biological, Environmental, and Behavioural Influences on Intelligence 374
Biological Influences on Intelligence 375 The Genetics of Intelligence: Twin and Adoption Studies 375
The Heritability of Intelligence 375
Behavioural Genomics 376
Working the Scientific Literacy Model: Brain Size and Intelligence 377 Environmental Influences on Intelligence 379
Birth Order 379
Socioeconomic Status 380
Nutrition 380
Stress 381
Education 381
The Flynn Effect: Is Everyone Getting Smarter? 381
Behavioural Influences on Intelligence 382 Brain Training Programs 383
Nootropic Drugs 383
Summary 384
10 Lifespan Development 385 Module 10.1 Physical Development from Conception through Infancy 386
Methods for Measuring Developmental Trends 387 Patterns of Development: Stages and Continuity 387
Zygotes to Infants: From One Cell to Billions 388 Fertilization and Gestation 388
Fetal Brain Development 388
Nutrition, Teratogens, and Fetal Development 390
Working the Scientific Literacy Model: The Long-Term Effects of Premature Birth 392
Myths in Mind Vaccinations and Autism 394
Sensory and Motor Development in Infancy 394 Motor Development in the First Year 396
Summary 399
Module 10.2 Infancy and Childhood: Cognitive and Emotional Development 400
Cognitive Changes: Piaget’s Cognitive Development Theory 401 The Sensorimotor Stage: Living in the Material World 401
The Preoperational Stage: Quantity and Numbers 402
The Concrete Operational Stage: Using Logical Thought 403
The Formal Operational Stage: Abstract and Hypothetical Thought 403
Working the Scientific Literacy Model: Evaluating Piaget 404 Complementary Approaches to Piaget 405
Social Development, Attachment, and Self-Awareness 406 What Is Attachment? 407
Types of Attachment 407
Development of Attachment 409
Self Awareness 409
Psychosocial Development 412 Development across the Lifespan 412
Parenting and Prosocial Behaviour 413
Parenting and Attachment 414
Summary 415
Module 10.3 Adolescence 417 Physical Changes in Adolescence 418
Emotional Challenges in Adolescence 419 Emotional Regulation during Adolescence 420
Working the Scientific Literacy Model: Adolescent Risk and Decision Making 420
Cognitive Development: Moral Reasoning vs. Emotions 422 Kohlberg’s Moral Development: Learning Right from Wrong 422
BIOPSYCHOSOCIAL PERSPECTIVES Emotion and Disgust 424
Social Development: Identity and Relationships 425 Who Am I? Identity Formation during Adolescence 425
Peer Groups 425
Romantic Relationships 426
Summary 427
Module 10.4 Adulthood and Aging 428 From Adolescence through Middle Age 429
Emerging Adults 429
Early and Middle Adulthood 429
Love and Marriage 431
Parenting 432
Late Adulthood 433 Happiness and Relationships 433
The Eventual Decline of Aging 434
Psych@ The Driver’s Seat 435
Working the Scientific Literacy Model: Aging and Cognitive Change 436
Summary 438
11 Motivation and Emotion 439 Module 11.1 Hunger and Eating 440
Physiological Aspects of Hunger 442 Food and Reward 443
Psychological Aspects of Hunger 445 Attention and Eating 445
Eating and Semantic Networks 446
Eating and the Social Context 446
Disorders of Eating 448 Anorexia and Bulimia 448
Working the Scientific Literacy Model: The Effect of Media Depictions of Beauty on Body Image 450
Summary 451
Module 11.2 Sex 452 Human Sexual Behaviour: Psychological Influences 453
Psychological Measures of Sexual Motivation 453
Human Sexual Behaviour: Physiological Influences 455 Physiological Measures of Sex 455
Sexual Orientation: Biology and Environment 456
Transgender and Transsexual Individuals 458
Psych@ Sex Ed 459
Human Sexual Behaviour: Cultural Influences 460 Sex and Technology 461
Working the Scientific Literacy Model: Does Sex Sell? 462
Summary 464
Module 11.3 Social and Achievement Motivation 465 Belonging and Love Needs 466
Belonging Is a Need, Not a Want 467
Love 467
Belonging, Self-Esteem, and Our Worldview 468
Working the Scientific Literacy Model: Terror Management Theory and the Need to Belong 468
Achievement Motivation 470 Self-Determination Theory 471
Extrinsic and Intrinsic Motivation 472
A Continuum of Motivation 472
Cultural Differences in Motivation 473
Summary 475
Module 11.4 Emotion 476 Physiology of Emotion 477
The Initial Response 477
The Autonomic Response: Fight or Flight? 478
The Emotional Response: Movement 479
Emotional Regulation 479
Experiencing Emotions 479
Working the Scientific Literacy Model: The Two-Factor Theory of Emotion 481
Expressing Emotions 484 Emotional Faces and Bodies 484
Culture, Emotion, and Display Rules 486
Culture, Context, and Emotion 487
Summary 489
12 Personality 490 Module 12.1 Contemporary Approaches to Personality 491
The Trait Perspective 492 Early Trait Research 492
The Five Factor Model 493
Openness 494
Conscientiousness 495
Extraversion 495
Agreeableness 495
Neuroticism 495
Beyond the Big Five: The Personality of Evil? 496 Honesty–Humility 496
The Dark Triad 496
Right-Wing Authoritarianism 497
Working the Scientific Literacy Model: Right-Wing Authoritarianism at the Group Level 497
Personality Traits over the Lifespan 499 Temperaments 499
Is Personality Stable over Time? 499
Personality Traits and States 500
Behaviourist and Social-Cognitive Perspectives 501 The Behaviourist Perspective 501
The Social-Cognitive Perspective 502
Summary 503
Module 12.2 Cultural and Biological Approaches to Personality 505 Culture and Personality 506
Universals and Differences across Cultures: The Big Five 506
Personality Structures in Different Cultures 506
Comparing Personality Traits between Nations 507
BIOPSYCHOSOCIAL PERSPECTIVES How Culture Shapes Our Development: Cultural Differences in the Self 507
How Genes Affect Personality 508 Twin Studies 509
Working the Scientific Literacy Model: From Molecules to Personality 510
The Role of Evolution in Personality 511 Animal Behaviour: The Evolutionary Roots of Personality 511
Why There Are So Many Different Personalities: The Evolutionary Explanation 512
Myths in Mind Men Are from Mars, Women Are from Venus 513
The Brain and Personality 514 Extraversion and Arousal 514
Contemporary Research: Images of Personality in the Brain 515
Extraversion 515
Neuroticism 515
Agreeableness 515
Conscientiousness 515
Openness to Experience 515
Summary 516
Module 12.3 Psychodynamic and Humanistic Approaches to Personality 518
The Psychodynamic Perspective 519 Assumptions of Psychodynamic Theories 519
Unconscious Processes and Psychodynamics 520
The Structure of Personality 520
Defence Mechanisms 521
Personality Development: The Psychosexual Stages 522
The Oral Stage (0–18 Months) 523
The Anal Stage (18 Months–3 Years) 523
The Phallic Stage (3–6 Years) 523
The Latency Stage (6–13 years) 524
The Genital Stage 524
Exploring the Unconscious with Projective Tests 525
Working the Scientific Literacy Model: Perceiving Others as a Projective Test 526
Alternatives to the Psychodynamic Approach 527 Analytical Psychology 527
The Power of Social Factors 528
Humanistic Perspectives 528
Summary 529
13 Social Psychology 531 Module 13.1 The Power of the Situation: Social Influences on Behaviour 532
The Person and the Situation 533 Mimicry and Social Norms 534
Group Dynamics: Social Loafing and Social Facilitation 535
Groupthink 536
The Asch Experiments: Conformity 537
Working the Scientific Literacy Model: Examining Why People Conform: Seeing Is Believing 538
The Bystander Effect: Situational Influences on Helping Behaviour 541
Social Roles and Obedience 544 The Stanford Prison Study 544
Obedience to Authority: The Milgram Experiment 546
Summary 549
Module 13.2 Social Cognition 551 Person Perception 552
Thin Slices of Behaviour 553
Self-Fulfilling Prophecies and Other Consequences of First Impressions 553
The Self in the Social World 554 Projecting the Self onto Others: False Consensus and Naive
Realism 554
Self-Serving Biases and Attributions 555
Ingroups and Outgroups 556
Stereotypes, Prejudice, and Discrimination 557
Myths in Mind Are Only Negative Aspects of Stereotypes Problematic? 558
Prejudice in a Politically Correct World 558
Working the Scientific Literacy Model: Explicit versus Implicit Measures of Prejudice 559
Psych@ The Law Enforcement Academy 561 Improving Intergroup Relations 562
Summary 563
Module 13.3 Attitudes, Behaviour, and Effective Communication 564 Changing People’s Behaviour 565
Persuasion: Changing Attitudes through Communication 565
Using the Central Route Effectively 566 Make It Personal 567
Working the Scientific Literacy Model: The Identifiable Victim Effect 568 Value Appeals 570
Preaching or Flip-Flopping? One-Sided vs. Two-Sided Messages 570
Emotions in the Central Route 570
Using the Peripheral Route Effectively 572 Authority 572
Liking 572
Social Validation 572
Reciprocity 572
Consistency 573
The Attitude–Behaviour Feedback Loop 574 Cognitive Dissonance 574
Attitudes and Actions 575
Summary 576
14 Health, Stress, and Coping 578 Module 14.1 Behaviour and Health 579
Smoking 580
Working the Scientific Literacy Model: Media Exposure and Smoking 580
Efforts to Prevent Smoking 581
Obesity 582 Defining Healthy Weights and Obesity 583
Genetics and Body Weight 584
The Sedentary Lifestyle 584
Social Factors 585
Psychology and Weight Loss 585
BIOPSYCHOSOCIAL PERSPECTIVES Ethnicity, Economics, and Obesity 585
Psychosocial Influences on Health 586 Poverty and Discrimination 586
Family and Social Environment 587
Social Contagion 587
Summary 588
Module 14.2 Stress and Illness 590 What Causes Stress? 591
Stress and Performance 592
Physiology of Stress 593 The Stress Pathways 594
Oxytocin: To Tend and Befriend 594
Working the Scientific Literacy Model: Hormones, Relationships, and Health 596
Stress, Immunity, and Illness 597 Stress, Personality, and Heart Disease 598
Myths in Mind Stress and Ulcers 599 Stress, Food, and Drugs 599
Stress, the Brain, and Disease 599
Summary 601
Module 14.3 Coping and Well-Being 602 Coping 603
Positive Coping Strategies 603
Optimism and Pessimism 603
Resilience 604
Biofeedback 605
Meditation and Relaxation 605
Psych@ Church 607 Exercise 608
Perceived Control 609
Working the Scientific Literacy Model: Compensatory Control and Health 610
Summary 612
15 Psychological Disorders 614 Module 15.1 Defining and Classifying Psychological Disorders 615
Defining Abnormal Behaviour 616 What Is “Normal” Behaviour? 617
Psychology’s Puzzle: How to Diagnose Psychological Disorders 617
Critiquing the DSM 618
The Power of a Diagnosis 619
Working the Scientific Literacy Model: Labelling and Mental Disorders 619
BIOPSYCHOSOCIAL PERSPECTIVES Symptoms, Treatments, and Culture 621
Applications of Psychological Diagnoses 622 The Mental Disorder Defence (AKA the Insanity Defence) 622
Summary 623
Module 15.2 Personality and Dissociative Disorders 624 Defining and Classifying Personality Disorders 625
Borderline Personality 625
Narcissistic Personality 626
Histrionic Personality 626
Working the Scientific Literacy Model: Antisocial Personality Disorder
626 The Biopsychosocial Approach to Personality Disorders 629
Psychological Factors 629
Sociocultural Factors 629
Biological Factors 629
Dissociative Identity Disorder 630 Types of Dissociative Disorders 630
Is Dissociative Identity Disorder “Real?” 630
Summary 631
Module 15.3 Anxiety, Obsessive–Compulsive, and Depressive Disorders 633
Anxiety Disorders 634 Varieties of Anxiety Disorders 634
Working the Scientific Literacy Model: Specific Phobias 635 The Vicious Cycle of Anxiety Disorders 637
Obsessive–Compulsive Disorder (OCD) 637
Mood Disorders 639 Types of Mood Disorders 639
Cognitive Aspects of Depression 639
Biological Aspects of Depression 640
Sociocultural and Environmental Influences on Mood Disorders 641
Suicide 641
Psych@ The Suicide Helpline 642
Summary 643
Module 15.4 Schizophrenia 644 Symptoms and Types of Schizophrenia 645
Stages of Schizophrenia 645
Symptoms of Schizophrenia 645
Common Sub-Types of Schizophrenia 646
Myths in Mind Schizophrenia Is Not a Sign of Violence or of Being a “Mad Genius” 647
Explaining Schizophrenia 648 Genetics 648
Schizophrenia and the Nervous System 648
Working the Scientific Literacy Model: The Neurodevelopmental Hypothesis 649
Environmental and Social Influences on Schizophrenia 650
Culture and Schizophrenia 651
Summary 652
16 Therapies 653 Module 16.1 Treating Psychological Disorders 654
Barriers to Psychological Treatment 655 Stigma about Mental Illness 655
Gender Roles 656
Logistical Barriers: Expense and Availability 656
Involuntary Treatment 656
Mental Health Providers and Settings 657 Mental Health Providers 657
Inpatient Treatment and Deinstitutionalization 658
The Importance of Community Psychology 659
Psych@ The University Mental Health Counselling Centre 659
Evaluating Treatments 660 Empirically Supported Treatments 660
Working the Scientific Literacy Model: Can Self-Help Treatments Be Effective? 661
Summary 663
Module 16.2 Psychological Therapies 664 Insight Therapies 665
Psychoanalysis: Exploring the Unconscious 665
Modern Psychodynamic Therapies 666
Humanistic–Existential Psychotherapy 666
Evaluating Insight Therapies 667
Behavioural, Cognitive, and Group Therapies 668 Systematic Desensitization 668
Working the Scientific Literacy Model: Virtual Reality Therapies 669 Aversive Conditioning 671
Cognitive–Behavioural Therapies 671
Mindfulness-Based Cognitive Therapy 672
Group and Family Therapies 673
Evaluating Cognitive–Behavioural Therapies 673
Summary 674
Module 16.3 Biomedical Therapies 676
Drug Treatments 677 Antidepressants 677
Myths in Mind Antidepressant Drugs Are Happiness Pills 678
Working the Scientific Literacy Model: Is St. John’s Wort Effective? 679 Mood Stabilizers 680
Antianxiety Drugs 680
Antipsychotic Drugs 680
Evaluating Drug Therapies 681
Technological and Surgical Methods 682 Focal Lesions 683
Electroconvulsive Therapy 683
Repetitive Transcranial Magnetic Stimulation 683
Deep Brain Stimulation 684
Summary 685
Glossary 686
References 701
Name Index 752
Subject Index 766
About the Authors Dr. Mark Krause received his Bachelor’s and Master’s degrees at Central Washington University, and his PhD at the University of Tennessee in 2000. He completed a postdoctoral appointment at the University of Texas at Austin where he studied classical conditioning of sexual behaviour in birds. Following this, Krause accepted a research fellowship through the National Institute of Aging to conduct research on cognitive neuroscience at Oregon Health and Sciences University. He has conducted research and published on pointing and communication in chimpanzees, predatory behaviour in snakes, the behavioural and evolutionary basis of conditioned sexual behaviour, and the influence of testosterone on cognition and brain function. Krause began his teaching career as a doctoral candidate and continued to pursue this passion even during research appointments. His teaching includes courses in general psychology, learning and memory, and behavioural neuroscience. Krause is currently a professor of psychology at Southern Oregon University, where his focus is on teaching, writing, and supervising student research. His spare time is spent with his family, cycling, reading, and enjoying Oregon’s outdoors.
Dr. Daniel Corts discovered psychology at Belmont University where he received his B.S. He completed a PhD in Experimental Psychology at the University of Tennessee in 1999 and then a post-doctoral position at Furman University for one year where he focused on the teaching of psychology. He is now professor of psychology at Augustana College in Rock Island, IL where he has taught for over 15 years. His research interests in cognition have led to publications on language, gesture, and memory, and he has also published in the area of college student development. Corts is increasingly involved in applied work, developing programming and assessments related to K-12 educational programming and teacher preparation. Corts is enthusiastic about getting students involved in research and has supervised or coauthored over 100
conference presentations with undergraduates. Corts has served as the local Psi Chi advisor for a dozen years and has served on the Board of Directors for several years, including his current term as President. In his spare time, he enjoys spending time with his two children, travelling, camping, and cooking.
About the Canadian Authors Dr. Stephen Smith received his Bachelor of Arts and Science in Psychology and Political Science from the University of Lethbridge, and his M.A. and PhD in Psychology from the University of Waterloo. After graduating in 2004, he completed a postdoctoral fellowship in the Affective Neuroscience Laboratory at Vanderbilt University in Nashville, TN. Smith is now an Associate Professor of Psychology at the University of Winnipeg. His research focuses on how emotion, attention, and movement interact, and on how these processes are performed by the nervous system. He has published research about emotional processing in patients with different types of brain damage, how emotion affects our perception of time, and, using neuroimaging, how emotions influence the activity of cells in both the brain and the spinal cord. Smith’s teaching includes introductory psychology, physiological psychology, and third- and fourth-year courses in cognitive neuroscience. In his spare time, he loves to travel, read, play hockey, and spend time with his wife and two young children.
Dr. Dan Dolderman received his Bachelor of Arts, M.A., and PhD from the University of Waterloo. He has taught psychology at the University of Toronto (St. George campus) since 2002 and is now a Senior Lecturer. Dolderman’s research is in the area of environmental psychology. He is actively involved in promoting environmentally sustainable behaviours and has presented his research in numerous public and government settings. He has published research papers on these topics as well as on the dynamics of human relationships. His teaching includes introductory psychology, environmental psychology, and positive psychology. In his spare time, he enjoys meditating, camping, and spending time with his three children.
From the Authors Welcome to the second Canadian edition of An Introduction to Psychological Science. It is a great privilege for us to offer an updated and revised version of our textbook. Much has happened in psychology (and the world) since the first Canadian edition and we are excited to present the latest and greatest that our field has to offer. Of course, equally (if not more) important to keeping up with the science is ensuring that our readers find our book accessible, interesting, and hopefully inspiring. To do this, we re-read the first Canadian edition from the perspective of someone new to psychology. By taking this perspective, we were able to identify parts of the book that needed reworking. This exercise also reaffirmed our belief that scientific literacy is important and should be promoted. We need science and critical thinking skills now more than ever.
Scientific literacy is more than simply memorizing lists of scientific terms and famous names; rather, it is the ability to encounter, understand, and evaluate scientific as well as nonscientific claims. Scientific literacy comprises four interrelated components:
1. Knowledge: What do we know about a phenomenon? 2. Scientific explanation: How does science explain the psychological
process we are examining?
3. Critical thinking: How do we interpret and evaluate all types of information, including scientific reporting?
4. Application: How does research apply to our own lives and to society?
To make scientific literacy the core of our text and MyPsychLab, we developed content and features with the model shown in the graphic as a guide. The competencies that surround the scientific literacy core represent different knowledge or skill sets we want to work toward during the course. The multidirectional nature of the arrows connecting the four supporting themes for
scientific literacy demonstrates the interrelatedness of the competencies, which span both core-level skills, such as knowing general information (e.g., terms, concepts), and more advanced skills, such as knowing how to explain phenomena from a scientific perspective, critical thinking, and application of material.
An Introduction to Psychological Science presents students with a model for scientific literacy; this model forms the core of how this book is written and organized. We believe a scientific literacy perspective and model will prove useful in addressing two course needs we often hear from instructors—to provide students with a systematic way to categorize the overwhelming amount of information they are confronted with, and to cultivate their curiosity and help them understand the relevance, practicality, and immense appeal of psychological science.
Psychological science is in a privileged position to help students hone their scientific literacy. It is both a rigorous scientific discipline and a field that studies the most complex of all phenomena: the behavioural, cognitive, and biological basis of behaviour. With this focus on behaviour, one can rightly argue that psychology resides at the hub or core of numerous other scientific disciplines; it also shares connections with neuroscience, education, and public health, to name a few linkages. From this perspective, the knowledge acquired by studying psychological science should transfer and apply to many other fields. This is great news when you consider that psychology is one of the few science courses
that many undergraduates will ever take.
In the second Canadian edition of this textbook, we have continued our emphasis on helping the reader organize and assess their thinking and learning about the material. Each module includes learning objectives of increasing depth (knowing, understanding, analyzing, and applying) as well as quiz items that assess learning at each level. We have also included interactive materials using the REVEL platform (found in the e-version of this book). Together, these tools should help make the concepts relevant to readers’ lives; this, in turn, should improve retention of the course material.
We would like to thank the many instructors and students who have helped us craft this model and apply it to our discipline, and we look forward to your feedback. Please feel free to contact us and share your experiences with the
second Canadian edition of An Introduction to Psychological Science.
Mark Krause
[email protected] Daniel Corts
[email protected] Stephen Smith
[email protected] Dan Dolderman
What’s New in the Second Canadian Edition? Writing the first Canadian edition of An Introduction to Psychological Science gave us a new appreciation for how important Canadian researchers have been to the study of psychological science. Although Canada is a relatively small country (in terms of population and the number of research institutions), Canadian researchers have made incredibly important contributions to a number of areas of psychology. These important contributions are again highlighted in the second Canadian edition. We have also continued to focus on issues that are of particular relevance to Canadians, including bilingualism, environmental psychology, and the experiences of first- and second-generation immigrants to Canada.
As Introductory Psychology professors ourselves, we had a chance to use the first edition of our textbook in our own classes. The second edition of our textbook provides us with an opportunity to (1) add new, cutting-edge material to the discussion of different areas of our field, and (2) expand on topics that our own students have found particularly interesting. In fact, several of the changes to this edition of the book are a result of feedback and discussions with students
in Winnipeg and Toronto (as well as a few much-appreciated emails from students at other institutions).
Each chapter of the second edition of this textbook has been updated to reflect the latest discoveries in psychology. Indeed, we have added new topics to all 16 chapters in the book. For example:
Chapter 1 , Introducing Psychological Science, includes a new section entitled Emerging Themes in Psychology. Here, we highlight five current themes that are found in modern psychology: (1) the psychology of women,
(2) cross-cultural psychology, (3) neuroimaging research, (4) positive psychology, and (5) applied psychology. Our hope is that this section will prime readers to look for these themes as they read through the other
modules of the book. Chapter 1 also contains new information showing the benefits of distributed (spaced) learning and provides students with specific suggestions for improving their academic performance. Chapter 2 , Reading and Evaluating Scientific Research, discusses the “replication crisis” in psychology and examines its implications for our field of study. We also include new information about the role that qualitative research can play in psychology, with a Canadian-based study of “friends with benefits” serving as the running example. Chapter 3 , Biological Psychology, includes a new Working the Scientific Literacy Model section on the role of testosterone in social aggression. We also updated our discussion of sex difference in spatial cognition and streamlined several sections related to evolutionary psychology. Chapter 4 , Sensation and Perception, includes a new section on the vestibular system as well as a new Working the Scientific Literacy Model section on the ability to follow musical beats. This chapter also contains new content related to two topics that have garnered significant attention in the past year: The Great Dress Debate (about the dress that appears white and gold to some and black and blue to others) and Autonomous Sensory Meridian Response (ASMR), a recently identified example of atypical multimodal integration. Chapter 5 , Consciousness, includes a new section on mind-wandering (replacing meditation, which is now discussed elsewhere). We have also added material related to the effect of caffeine on circadian rhythms, the role of social isolation in drug dependence, and the societal effects of legalizing drugs. We have also provided updated information about the legal status of
some drugs including Salvia divinorum. Chapter 6 , Learning, includes new information explaining how the unconditioned response (UR) and conditioned response (CR) aren’t always identical. We have also added a new section on how operant conditioning is used in casino settings, and have highlighted how multiline slot machines often produce losses that are disguised as wins. We also streamlined the applications of classical conditioning section in an effort to provide clearer
examples of these principles. Chapter 7 , Memory, includes new information about emotion and memory. We have also revamped our explanations of several concepts and have provided clearer examples of the differences in overlapping concepts (e.g., short-term memory and working memory). Chapter 8 , Thought and Language, includes a new Working the Scientific Literacy Model section on semantic priming. We have also added a new section on the relationship between problem solving and the interpretation of humour. Chapter 9 , Intelligence Testing, includes updated and reorganized material on a number of topics including multiple intelligences, the hierarchical model of intelligence, and the interactions between beliefs and intelligence-test scores. Chapter 10 , Lifespan Development, underwent extensive reorganization. It includes new information about fetal alcohol syndrome as well as updated information about several topics including the development of theory of mind and obstacles to healthy relationships in adulthood. Chapter 11 , Motivation and Emotion, includes a number of new sections. We have added content about semantic networks and food cravings, terror management theory and its role in Canadian and American elections, how bicultural individuals are affected by intrinsic and extrinsic motivation, and brain networks related to emotional perception and regulation. We have also added sections related to two issues that have received a great deal of attention in the past year: (1) the challenges affecting transgender and transsexual individuals, and (2) the controversies surrounding Ontario’s “Sex Ed” curriculum (which received national attention). Chapter 12 , Personality, includes a new discussion of Bandura’s social- cognitive theory as well as more refined discussions of several topics including an examination of right-wing authoritarianism and the stability of personality traits across the lifespan. Chapter 13 , Social Psychology, includes new information about the brain regions involved with implicit prejudice as well as updated information about the identifiable victim effect. Chapter 14 , Health, Stress, and Coping, includes updated statistics to several sections of Module 14.1 (Behaviour and Health). We have also
added information about individual zones of optimal performance to our discussion of stress and added new information to our discussion of meditation. Chapter 15 , Psychological Disorders, includes updated statistics related to different psychological disorders. We have also added new information about the neuroscience of antisocial personality disorder, genetics and depression, and identifying and helping individuals who are considering suicide. Several sections of this chapter were also reorganized to improve clarity. Chapter 16 , Therapies, includes new information about the effects of St. John’s wort, an herbal remedy for depression, on neurotransmitter systems in the brain. We have also updated sections related to the efficacy of antidepressants, and the use of electroconvulsive therapy and repetitive transcranial magnetic stimulation as treatments for depression.
We believe that these changes (among the many others made to the book) have allowed us to achieve our goal for the second Canadian edition: to provide readers with a thorough description of the field of psychology while also highlighting the importance of scientific literacy and the biopsychosocial model of human behaviour. We hope that you, the reader, feel the same. Enjoy the book!
Content and Features
Scientific Explanation How can science
explain it? This element of scientific literacy encompasses a basic understanding of research methodology and thinking about problems within a scientific
framework. An Introduction to Psychological Science integrates and reinforces key research methodology concepts throughout the book. This interweaving of methodology encourages students to continue practising
their scientific thinking skills.
In recent years, an increasing number of instructors have begun to focus on telling students how psychological science fits within the scientific community. Psychology serves, in essence, as a hub science. Through this emphasis on scientific literacy in psychology, students begin to see the practicality and relevance of psychology and become more literate in
the fields that our hub science supports.
Critical Thinking
Can we critically evaluate the evidence? Many departments are focusing to an increasing extent on the development of critical thinking, as these skills are highly sought after in society and the workforce. Critical thinking is generally defined as the ability to apply knowledge, use information in new ways, analyze situations and concepts, and evaluate decisions. To develop critical thinking, the module objectives and quizzes are built around an updated Bloom’s taxonomy. Objectives are listed at four levels of increasing
complexity: know, understand, apply, and analyze. The following features also help students organize, analyze, and synthesize information. Collectively, these features encourage students to connect different levels of understanding with specific objectives and quiz questions.
Application
Why is this relevant? Psychology is a highly relevant, modern science. To be scientifically literate, students should relate psychological concepts to their own lives, making decisions based on knowledge, sound methodology, and skilled interpretation of information.
For Instructors SCIENTIFIC LITERACY is a key course goal for many introductory psychology instructors.
Learning science is an active process. How do we help instructors model scientific literacy in the classroom and online in a way that meets the needs of today’s students?
Organization
Instructors consistently tell us one of the main challenges they face when teaching the introductory psychology course is organizing engaging, current, and relevant materials to span the breadth of content covered. How do we help organize and access valuable course materials?
REVEL™
Educational technology designed for the way today’s students read, think, and learn.
When students are engaged deeply, they learn more effectively and perform better in their courses. This simple fact inspired the creation of REVEL: an immersive learning experience designed for the way today’s students read, think, and learn. Built in collaboration with educators and students nationwide, REVEL is the newest, fully digital way to deliver respected Pearson content.
REVEL enlivens course content with media interactives and assessments—
integrated directly within the authors’ narrative—that provide opportunities for students to read about and practice course material in tandem. This immersive educational technology boosts student engagement, which leads to better understanding of concepts and improved performance throughout the course.
Learn more about REVEL
http://www.pearsonhighered.com/revel/
MyPsychLab
MyPsychLab offers students useful and engaging self-assessment tools, and it provides instructors with flexibility in assessing and tracking student progress. For instructors, MyPsychLab is a powerful tool for assessing student performance and adapting course content to students’ changing needs, without requiring instructors to invest additional time or resources to do so.
Instructors and students have been using MyPsychLab for more than 13 years. To date, more than 600 000 students have used MyPsychLab. During that time, three white papers on the efficacy of MyPsychLab have been published. Both the white papers and user feedback show compelling results: MyPsychLab helps students succeed and improve their test scores. One of the key ways MyPsychLab improves student outcomes is by providing continuous assessment as part of the learning process. Over the years, both instructor and student feedback have guided numerous improvements to this system, making MyPsychLab even more flexible and effective.
Pearson is committed to helping instructors and students succeed with MyPsychLab. To that end, we offer a Psychology Faculty Advisor Program designed to provide peer-to-peer support for new users of MyPsychLab. Experienced Faculty Advisors help instructors understand how MyPsychLab can improve student performance. To learn more about the Faculty Advisor Program, please contact your local Pearson representative.
MyPsychLab Video Series
The MyPsychLab Video Series is a comprehensive and cutting-edge series featuring 17 original 30-minute videos covering the most recent research and utilizing the most up-to-date film and animation technology. Multiple choice and short answer essay questions are provided within MyPsychLab so episodes can be assigned as homework.
MyPsychLab Study Plan
Students have access to a personalized study plan, based on Bloom’s taxonomy, that arranges content from less complex thinking (such as remembering and understanding) to more complex critical thinking (such as applying and analyzing). This layered approach promotes better critical thinking skills and helps students succeed in the course and beyond.
Learning Catalytics
Learning Catalytics is a “bring your own device” student engagement, assessment, and classroom intelligence system. It allows instructors to engage students in class with real-time diagnostics. Students can use any modern, web- enabled device (smartphone, tablet, or laptop) to access it.
Writing Space
Better writers make great learners—who perform better in their courses. To help you develop and assess concept mastery and critical thinking through writing, we created Writing Space.
It’s a single place to create, track, and grade writing assignments, provide writing resources, and exchange meaningful, personalized feedback with students, quickly and easily, including auto-scoring for practice writing prompts. Plus, Writing Space has integrated access to Turnitin, the global leader in plagiarism prevention.
Instructor’s Manual
The Instructor’s Manual includes suggestions for preparing for the course, sample syllabi, and current trends and strategies for successful teaching. Each chapter offers integrated teaching outlines, lists the key terms for each chapter for quick reference, and provides an extensive bank of lecture launchers, handouts, and activities, as well as suggestions for integrating third-party videos and web resources. The electronic format features click-and-view hotlinks that allow instructors to quickly review or print any resource from a particular chapter. This resource saves prep work and helps maximize classroom time. Chapter and module quiz answers can also be found in the Instructor’s Manual.
Standard Lecture PowerPoint Slides
Standard Lecture PowerPoint Slides are available online at
www.pearsoncanada.ca/highered, with a more traditional format with excerpts of the text material, photos, and artwork.
Assessment Instructors consistently tell us that assessing student progress is a critical component to their course and one of the most time-consuming tasks. Vetted, good-quality, easy-to-use assessment tools are essential. We have been listening and we have responded by creating the absolutely best assessment content available on the market today.
Test Bank
The Test Bank contains more than 3000 questions, many of which were class- tested in multiple classes at both 2-year and 4-year institutions across the country prior to publication. Item analysis is provided for all class-tested items. All questions have been thoroughly reviewed and analyzed line-by-line by a development editor and a copy editor to ensure clarity, accuracy, and delivery of
the highest-quality assessment tool. The test bank for the second Canadian edition was also extensively reviewed by a professional psychometrician with over ten years of experience teaching university psychology. Most conceptual and applied multiple-choice questions include rationales for each correct answer and the key distractors. The item analysis helps instructors create balanced tests, while the rationales serve both as an added guarantee of quality and as a time-saver when students challenge the keyed answer for a specific item.
The Test Bank also comes with Pearson MyTest, a powerful assessment generation program that helps instructors easily create and print quizzes and exams. Questions and tests can be authored online, providing instructors with the ultimate in flexibility and the ability to efficiently manage assessments wherever and whenever they want. Instructors can easily access existing questions and then edit, create, and store them using simple drag-and-drop and Word-like controls. The data for each question identifies its difficulty level and the text page number where the relevant content appears. In addition, each question maps to the text’s major section and Learning Objective. For more information,
go to www.PearsonMyTest.com.
Acknowledgments We cannot fathom completing a project like this without the help and support of many individuals. Through every bit of this process have been our families and we thank you for your love, patience, and support. Although our children will be disappointed that this book is not about the Montreal Canadiens or sea creatures, we hope that they’ll read and enjoy this book one day. Our extended families, particularly Peggy Salter, also provided immense support and helped our children feel loved even when we had to work late to finish this book. In addition, our departments have been wonderfully understanding and helpful, offering advice with their various specializations, providing examples and tips, reviewing drafts, and tolerating our occasional absences.
The second Canadian edition of this book would not exist without the hard work and dedication shown by a number of people involved with first edition. Our original Developmental Editor, Johanna Schlaepfer, went above and beyond the call of duty to ensure that the final product was something we could all be proud of. The first edition also benefited from the guidance of Matthew Christian (the Acquisitions Editor at the time); Safa Ali; and Michelle Di Nella, Steve’s former lab coordinator and unofficial “solver of all problems.”
The second edition of this book was again a team effort. Our Developmental Editor, Lise Dupont, showed super-human patience. Laura Neves provided amazing copy editing and helped turn our mad scribblings into a coherent book. We are also indebted to Darcey Pepper (Acquisitions Editor) and to everyone on the Productions and Permissions side of things: Kathryn O’Handley and Kimberley Blakey at Pearson Canada, Vastavikta Sharma at Cenveo Publisher Services, and Vignesh Sadhasivam at Integra Software Services Pvt. Ltd. Dr. Leanne Stevens of Dalhousie University deserves a separate tip-of-the-hat for her work linking the REVEL interactivities and assessments with the text of the book. We would also like to thank the entire Pearson sales team for promoting
this book as well as the supplements team for editing the MyPsychLab and other online materials.
The second Canadian edition of this book benefitted from conversations with a number of colleagues. Danielle Gaucher from the University of Winnipeg was immensely helpful in making suggestions for the new feature on Women in Psychology (Module 1.2). Pauline Pearson from the University of Winnipeg helped us clarify a number of points related to perceptual constancies (Module 4.2). Dan Smilek from the University of Waterloo (and Steve’s former soccer teammate) was kind enough to read through and edit the new section on mind- wandering (Module 5.2). Doug Williams from the University of Winnipeg provided us with a number of fantastic ideas that ended up influencing several new
sections in Chapters 6 (Learning).
Finally, we would like to thank the many reviewers and students who carefully read over the first Canadian edition and/or earlier versions of chapters from the second edition of this book. We are very grateful that you shared your expertise in the field of psychology, and in teaching, to help bring this book to life.
We value feedback from both instructors and students, and we are sure that we will need it for our Third Canadian Edition. Please do not hesitate to offer
suggestions or comments by writing to Steve Smith ([email protected]) or Dan Dolderman ([email protected]).
List of Reviewers
Jeffrey Adams, Trent University
Kimberly Burton, Marianapolis College
Stephanie Denison, University of Waterloo
Stephane Gaskin, Concordia University and Dawson College
Peter Graf, University of British Columbia
Rick Healey, Memorial University of Newfoundland
Thom Herrmann, University of Guelph
Karsten A. Loepelmann, University of Alberta
Alison Luby, University of Toronto
Laura MacKay, Capilano University
Stacey L. MacKinnon, University of Prince Edward Island
Jamal K. Mansour, Simon Fraser University
Diano Marrone, Wilfrid Laurier University
Katherine McGuire, University of New Brunswick, Saint John
Geoffrey S. Navara, Trent University
Jeffrey Nicol, Vancouver Island University
Peter Papadogiannis, University of Guelph-Humber
JDA Parker, Trent University
Tony Robertson, Vancouver Island University
Biljana Stevanovski, University of New Brunswick
Cheryl Techentin, Mount Royal University
Jennifer Tomaszczyk, University of Waterloo
Randal Tonks, Camosun College
Christine D. Tsang, Huron University College at Western
Ashley Waggoner Denton, University of Toronto
Susan G. Walling, Memorial University of Newfoundland
Stacey Wareham-Fowler, Memorial University of Newfoundland
Doug Williams, University of Winnipeg
Ross Woolley, Langara College
Chapter 1 Introducing Psychological Science
1.1 The Science of Psychology The Scientific Method 3
Module 1.1a Quiz 6
Building Scientific Literacy 6
Working the Scientific Literacy Model: Planning When to Study 7
Module 1.1b Quiz 9
Module 1.1 Summary 10
1.2 How Psychology Became a Science Psychology’s Philosophical and Scientific Origins 12
Module 1.2a Quiz 17
The Beginnings of Contemporary Psychology 18
Module 1.2b Quiz 24
Emerging Themes in Psychology 24
Module 1.2c Quiz 27
Module 1.2 Summary 28
Module 1.1 The Science of Psychology
Everett Collection
Learning Objectives
Almost everyone has misinterpreted someone else’s meaning in a
Know . . . the key terminology of the scientific method. Understand . . . the steps of the scientific method. Understand . . . the concept of scientific literacy. Apply . . . the biopsychosocial model to behaviour. Apply . . . the steps in critical thinking.
Analyze . . . the use of the term scientific theory.
1.1a 1.1b 1.1c 1.1d 1.1e 1.1f
conversation. You could misinterpret someone leaning closer to you as flirting when really you were just talking too softly. You could mistake someone’s tone of voice as being annoyed when that person was actually talking loudly to be heard over other people in the room. We also frequently misjudge other people’s attitudes and personalities. The unfriendly and arrogant person at work might actually turn out to be a shy person who dislikes crowded social events. In all of these situations, we make inferences about another person based on the different cues they provide us. But how do we decide which cues are important? Are they really the right cues to be using when we want to explain other people’s behaviour?
The situation is even more complicated in the wired world of the 21st century, with everyone plugged in to email, online gaming, and social networking sites like Facebook and Twitter. How do you interpret someone’s behaviour or intentions when all you have to go by is words on a screen and cartoon-like happy faces? How much information do you need to (safely) disclose in order for other people to understand you? These questions highlight the complexity of human behaviour as well as some of the challenges involved in trying to understand it. In this textbook, we will examine many different aspects of behaviour—from basic brain and perception functions to memory to social behaviours. But all of these chapters have the same central theme: the quest to understand why and how we behave the way we do.
Focus Questions
1. How can the human mind, with its quirks and imperfections, conduct studies on itself?
2. How can scientific and critical thinking steer us toward a clearer understanding of human behaviour and experience?
One of the reasons psychology is such an exciting field is that it is easy to see
how this field of study relates to your own life. Although chemistry and physics both have a profound effect on our lives, it is sometimes difficult to link formulas
and diagrams with real life experiences. Psychology is visceral—we feel emotions, we take in sensations, and we produce behaviours such as thoughts and actions. Psychology is you.
A more official definition of psychology is the scientific study of behaviour, thought, and experience, and how they can be affected by physical, mental, social, and environmental factors. This definition shows you that psychology involves a number of overlapping areas of investigation. Some of the overarching goals of psychology include:
to understand how different brain structures work together to produce our behaviour
to understand how nature (genetics) and nurture (our upbringing and environment) interact to make us who we are
to understand how previous experiences influence how we think and act to understand how groups—family, culture, and crowds—affect the individual to understand how feelings of control can influence happiness and health to understand how each of these factors can influence our well-being and could contribute to psychological disorders
Critically, these points are not independent of one another. As we will discuss later in this module, every topic in psychology could be examined from a biological, cognitive (thinking), or sociocultural perspective. As you progress through this book, you will begin to understand the different factors that influence
your thoughts, actions, and feelings. Psychology can help you see the world in a different way. And, just as important, psychology can help you understand why
other people behave the way they do. All of the factors that influence you also influence other people in one way or another. By understanding these influences, you can gain a better understanding—and acceptance—of the people around you.
Importantly, our knowledge of human behaviour isn’t just a series of opinions. Every topic that we will discuss is based on the hard work of scientists who
meticulously tested their ideas in laboratories and in the “real world.” This text
includes many references (e.g., Eastwood et al., 2016) to reinforce this fact. The science of psychology would be nothing without the scientific method.
The Scientific Method
What exactly does it mean to be a scientist? A person who haphazardly combines chemicals in test tubes may look like a chemist, but he is not conducting science; a person who dissects a specimen just to see how it looks may appear to be a biologist, but this is not science either. In contrast, a person
who carefully follows a system of observing, predicting, and testing is conducting science, whether the subject matter is chemicals, physiology, human memory, or social interactions. In other words, whether a field of study is a science, or a
specific type of research is scientific, is based not on the subject but on the use of the scientific method. The scientific method is a way of learning about the world through collecting observations, developing theories to explain them, and using the theories to make predictions. It involves a dynamic interaction between hypothesis testing and the construction of theories, outlined in Figure 1.1 .
Figure 1.1 The Scientific Method Scientists use theories to generate hypotheses. Once tested, hypotheses are either confirmed or rejected. Confirmed hypotheses lead to new ones and strengthen theories. Rejected hypotheses are revised and tested again, and can potentially alter an existing theory.
Hypotheses: Making Predictions
Scientific thinking and procedures revolve around the concepts of a hypothesis and a theory. Both guide the process and progress of the sciences; however, it is
important to differentiate between these terms. A hypothesis (plural: hypotheses) is a testable prediction about processes that can be observed and measured. A hypothesis can be supported or rejected—you cannot prove a hypothesis because it is always possible that a future experiment could show that it is wrong or limited in some way. This support or rejection occurs after scientists have tested the hypothesis. For a hypothesis to be testable, it must be falsifiable , meaning that the hypothesis is precise enough that it could be proven false. This precision is also important because it will help future researchers if they try to replicate the study (i.e., reproduce the findings) to
determine if it the results were due to chance (see Module 2.1 for a more in- depth discussion of replication).
“All swans are white” is a falsifiable statement. A swan that is not coloured white will falsify it. Falsification is a critical component of scientific hypotheses and theories. Ellie Rothnie/Alamy Stock Photo
These requirements are regularly broken by people claiming to be scientific. For example, astrologers and psychics are in the business of making predictions. An astrologer might tell you, “It’s a good time for you to keep quiet or defer important calls or emails.” This type of statement is impossible to test. If you keep quiet and nothing happens to you, is that due to you following the horoscope or to the
fact that you hid from the world? Horoscopes make very general predictions— typically so much so that you could easily find evidence for them if you looked hard enough, and perhaps stretched an interpretation of events a bit. In contrast, a good scientific hypothesis is stated in more precise terms that promote testability, such as the following:
People become less likely to help a stranger if there are others around.
Cigarette smoking causes cancer.
Exercise improves memory ability.
Each of these hypotheses can be confirmed or rejected through scientific testing.
An obvious difference between science and astrology is that scientists are eager to test hypotheses such as these, whereas astrologers would rather you just take their word for it. We acknowledge that astrology is an easy target for criticism. In
fact, it is often referred to as pseudoscience , an idea that is presented as science but does not actually utilize basic principles of scientific thinking or procedure. Incidentally, a 2005 Gallup poll found that 25% of Canadians (17% of males and 33% of females) believe that the position of the stars in the sky can affect a person’s behaviour.
Theories: Explaining Phenomena
In contrast to hypotheses, a theory is an explanation for a broad range of observations that also generates new hypotheses and integrates numerous findings into a coherent whole. In other words, theories are general principles or explanations of some aspect of the world (including human behaviours), whereas hypotheses are specific predictions that can test the theory or, more realistically, specific parts of that theory. Theories are built from hypotheses that are repeatedly tested and confirmed. Similar to hypotheses, an essential quality of
scientific theories is that they can be supported or proved false with new evidence. If a hypothesis is supported, it provides more support for the theory. In turn, good theories eventually become accepted explanations of behaviour or
other phenomena (i.e., they can be used to generate new hypotheses). However, if the hypothesis is not supported by the results of a well-designed
experiment, then researchers may have to rethink elements of the theory. Figure 1.1 shows how hypothesis testing eventually leads back to the theory from which it was based, and how theories can be updated with new evidence. This
process helps to ensure that science is self-correcting—bad ideas typically do not last long in the sciences.
The term theory is often used very casually, which has led to some persistent and erroneous beliefs about scientific theories. The following points clarify some common misperceptions.
Theories are not the same as opinions or beliefs. Yes, it is certainly true
that everyone is entitled to their own beliefs. But the phrase “That’s just your theory” is confusing the terms “opinion” and “theory.” A theory can help scientists develop testable hypotheses; opinions do not need to be testable, or even logical.
All theories are not equally plausible. Groups of scientists might adopt different theories for explaining the same phenomenon. For example, several theories have been proposed to explain why people become depressed. This does not mean that anyone can throw their hat into the ring and claim equal status for his or her theory (or belief). A good theory can explain previous research and can lead to even more testable hypotheses.
The quality of a theory is not related to the number of people who believe it to be true. According to a 2009 poll, only 61% of Canadians (and only 39% of Americans) believe in the theory of evolution by natural selection
(Angus Reid Public Opinion, 2012), despite the fact that it is the most plausible, rigorously tested theory of biological change and diversity.
Testing hypotheses and constructing theories are both part of all sciences. Importantly, each science, including psychology, has its own unique way of approaching its complex subject matter as well as its own unique set of challenges. In the case of psychology, we must remember that behaviour can occur on a number of different levels, including the activity of cells in different parts of the brain, thought processes such as language and memory, and sociocultural processes that shape daily life for millions of people. Therefore, psychology examines the individual as a product of multiple influences, including biological, psychological, and social factors.
The Biopsychosocial Model
Because our thoughts and behaviours have multiple influences, psychologists
adopt multiple perspectives to understand them. The biopsychosocial model
is a means of explaining behaviour as a product of biological, psychological, and sociocultural factors (see Figure 1.2 ). Biological influences on our behaviour involve brain structures and chemicals, hormones, and external substances such as drugs. Psychological influences involve our memories, emotions, and personalities, and how these factors shape the way we think about and respond
to different people and situations. Finally, social factors such as our family, peers, ethnicity, and culture can have a huge effect on our behaviour. Importantly, none of these levels of analysis exists on its own. In fact, these levels influence each other! The firing of brain cells can influence how we think and remember information; this, in turn, can affect how we interact with family members or how we respond to social situations like a concert. But, these influences can occur in the other direction as well. Social situations can affect how we think (e.g., getting annoyed by the crowded hallway at your university), which, in turn, can trigger the release of chemicals and hormones in your brain.
Figure 1.2 The Biopsychosocial Model Psychologists view behaviour from multiple perspectives. A full understanding of human behaviour comes from analyzing biological, psychological, and sociocultural factors.
The take-home message of this section is that almost every moment of your life is occurring at all three levels; psychologists have taken up the exciting challenge of trying to understand them. Indeed, behaviour can be fully explained only if multiple perspectives—and their interactions—are investigated. This “systems perspective” will become particularly apparent as you read about psychological research that tackles complex topics.
Module 1.1a Quiz:
The Scientific Method
Know . . .
1. A testable prediction about processes that can be observed and measured is referred to as a(n) .
A. theory B. hypothesis C. opinion D. hunch
Understand . . .
2. A theory or prediction is falsifiable if A. it is based on logic that is incorrect. B. it is impossible to test. C. it is precise enough that it could be proven false. D. it comes from pseudoscience.
Apply . . .
3. How would you apply the biopsychosocial model to a news report claiming that anxiety is caused by being around other people who are anxious?
A. Recognize that the news report considers all portions of the biopsychosocial model.
B. Recognize that psychologists do not regard biological factors when it comes to anxiety.
C. Recognize that the only effective treatment of anxiety must be drug-based.
D. Recognize that the news report only considers one portion of the biopsychosocial model.
Analyze . . .
4. The hypothesis that “exercise improves one’s ability to remember lists of words” is a scientific one because
A. it cannot be confirmed. B. it cannot be rejected. C. it makes a specific, testable prediction. D. it can be proven.
Building Scientific Literacy
A major aim of this book is to teach you the theoretical foundations, concepts, and applicable skills that are central to the field of psychology. This book is also
designed to help you develop scientific literacy , the ability to understand, analyze, and apply scientific information. As you can see in Figure 1.3 , scientific literacy has several key components, starting with the ability to learn new information. Certainly this text will provide you with new terminology and concepts, but you will continue to encounter psychological and scientific terminology long after you have completed this course. Being scientifically
literate means that you will be able to read and interpret new terminology, or know where to go to find out more.
Figure 1.3 A Model for Scientific Literacy Scientific literacy involves four different skills: gathering knowledge about the world, explaining it using scientific terms and concepts, using critical thinking, and applying and using information.
Memorizing different terms is not enough to make someone scientifically literate. We also have to examine whether the ideas being presented were scientifically tested, and whether those studies were designed properly. It is absolutely essential that we ask such questions. Doing so allows us to separate the
information that we should find convincing from the information that we should view with caution. It will also allow you to better analyze the information presented to you by politicians, corporations, and the media; this will make it more difficult for these groups to influence your behaviour. Finally, we want to be able to apply the results of scientific studies to different situations; in other words,
to generalize the results. Generalization shows us that the studies conducted in universities and hospitals can provide insight into behaviours that extend far beyond the confines of the lab.
Working the Scientific Literacy Model Planning When to Study
To develop your scientific literacy skills, in every module
(beginning with Chapter 2 ) we will revisit this model and its four components as they apply to a specific psychological topic—
a process we call working the scientific literacy model. This will help you to move beyond simply learning the vocabulary of
psychological research toward understanding scientific explanations, thinking critically, and discovering applications of the material. In order to demonstrate how these sections of the book will work, let’s use an example that will be familiar to many: planning study time for your different classes.
What do we know about timing and studying? In the first stage of the Scientific Literacy Model, we attempt to gather the available knowledge about the topic that we’re investigating, in this case the fact that students differ on how they attempt to remember information for exams. Many students use
what is called massed learning—they perform all of their studying for an exam in one lengthy session. Another approach is spaced or distributed learning—having shorter study sessions, but spreading them out over several days. Which technique do you prefer? If you use the massed learning technique (most students prefer it . . . or end up using it because they’ve left studying until
the last minute), it is likely because it seems easier and it may even give you the sense that it is more effective than distributed learning. Actually, the two strategies are not equally effective; more than 100 years of memory research has shown us that
distributed learning is the better of the two (Cepeda et al., 2006; Edwards, 1917).
How can science explain the effect of timing on study success? In the second stage of the Scientific Literacy Model, we examine whether the information that is available about a topic has been tested in scientific studies. In a typical study of massed vs. distributed learning, participants are asked to remember lists of words or concepts. The stimuli are presented multiple times.
What varies, however, is when these presentations occur. In some conditions, the stimuli are presented in a single session (a massed schedule). In other conditions, the studying is spread out across multiple time periods (a spaced or distributed schedule). As early as 1885, Herman Ebbinghaus, a German psychologist, found that his ability to learn sets of nonsense syllables (e.g., wej) was superior if he spread his learning over three days rather than trying to learn the lengthy list in one sitting. Similar patterns of results have been found in hundreds of other studies, providing
strong evidence in favour of distributed learning (Delaney et al., 2010; Dempster, 1988). Although there is no single explanation for this effect, one factor is particularly relevant for students. When information is learned in one massed session, it begins to feel repetitive. This leads the learners to pay less attention to the material than they would in distributed learning sessions, when
some of the material may have been forgotten (Ausubel, 1966). As a result, people learning in a distributed fashion are more likely to pay attention to the material than massed learners, a tendency that would obviously improve performance.
Can we critically evaluate this evidence? In the third stage of the Scientific Literacy Model, we examine the limitations of the studies discussed earlier; we also look for alternative explanations for the results. The most obvious criticism of this research is that results from laboratory-based studies may not reflect how memory works in a real educational setting. This is a valid concern—researchers don’t want their
effects to be isolated to the laboratory. Luckily, a number of researchers have applied the knowledge and techniques
developed by earlier researchers to applied psychology studies in the classroom. In one study, elementary school children were
taught scientific information about food charts (Gluckman et al., 2014). Each child received four lessons about this topic. One group received all four lessons on a Monday (“massed learning condition”). A second group received two lessons on a Monday and two lessons on a Tuesday (“clumped learning group”). The third group received one lesson per day from Monday through Thursday (“distributed learning group”). All groups were tested
one week after their last lesson. As can be seen in Figure 1.4 , the distributed learning group retained much more information than the other two groups. Similar patterns of results have been
found in studies with middle school children (Sobel et al., 2011) and undergraduate students at an Ontario university (Kapler et al., 2015), suggesting that the laboratory studies of the benefits of distributed learning generalize to the so-called real world.
Figure 1.4 Massed versus Distributed Learning
In a study by Gluckman and colleagues (2014), groups of students learned information in one long session (massed
learning), two sessions per day on two consecutive days (clumped learning), or spread across four days (distributed learning). A test one week later found that the distributed learning group retained much more information than the other groups. Source: Information is derived from Table 1 of Gluckman et al. (2014), Spacing Simultaneously
Promotes Multiple Forms of Learning in Children’s Science Curriculum, Applied Cognitive
Psychology, 28, p. 270, Wiley Online Library.
Why is this finding relevant? In the final stage of the Scientific Literacy Model, we attempt to apply the results to situations outside of the laboratory. The information about distributed learning is being presented in the first module of this textbook for a reason: Psychology students should benefit from psychology research. Now that you know that retention is improved if you study over the course of a few days rather than in one long session, you can alter your own study schedule. The benefits to your grades could be substantial. Distributed learning has also proven useful in many clinical contexts, such as helping people improve their memory abilities
after suffering a traumatic brain injury (Hillary et al., 2003). Sometimes simple experiments can have widespread implications; that’s something to remember.
Now that you have read this feature, we hope you understand how scientific information fits into the four components of the model. But there is still much to learn about working the model: In the next section, we will describe critical thinking skills and how to use them.
Critical Thinking, Curiosity, and a Dose of Healthy
Skepticism
People are confronted with more information on a daily basis than they have been at any other point in our history. Some of it is credible and can be used to help guide your decisions or behaviour. But we also must deal with claims—often made by people trying to sell you things—that are not always true.
“This political party will not base its positions on public opinion polls.”
“These remedies were developed by ancient cultures and have been used for centuries.”
“Join now and find your soul mate.”
Misinformation sometimes seems far more abundant than accurate information, which is why it is important to develop critical thinking skills.
Refer to Figure 1.3 . As the model shows, critical thinking is an important element of scientific literacy. Critical thinking involves exercising curiosity and skepticism when evaluating the claims of others, and with our own assumptions and beliefs. Critical thinking does not mean being negative or arbitrarily critical; rather, it means that you intentionally examine knowledge, beliefs, and the means by which conclusions were obtained.
Critical thinking involves cautious skepticism. We are constantly being told about amazing products that help us control body weight, improve thinking and memory, enhance sexual performance, and so on. As consumers, there will always be claims we really hope to be true. But as critical thinkers, we meet
these claims with a good dose of skepticism (e.g., Is there sound evidence that this diet helps people to achieve and maintain a healthy weight?). Being skeptical can be challenging, especially when it means asking for evidence that we may not want to find. Often the great products or miracle cures that we have
always hoped for really are “too good to be true.” Being curious and skeptical leads you to ask important questions about the science underlying such claims. Doing so leads us to search for and evaluate evidence, which is never a bad thing.
Importantly, the ability to think critically can be learned and developed, although
most of us need to make a conscious effort to do so (Halpern, 1996). Research points to a core set of habits and skills for developing critical thinking:
1. Be curious. Simple answers are sometimes too simple, and common sense is not always correct (or even close to it). Example: Giving your brain some time to rest after having a stroke (a form of brain damage)
hinders rather than helps your recovery (see Module 3.3 ). 2. Examine the nature and source of the evidence; not all research is of
equal quality. Example: Some studies use flawed methods or, in the case of an infamous study linking vaccines and autism, were performed by someone who would benefit financially if the results told a particular story
(see Module 2.3 ). 3. Examine assumptions and biases. This includes your own assumptions
as well as the assumptions of those making the claims. Example: Research examining the impact of human behaviour on climate change
may be biased if it is funded by oil companies (see Module 2.2 ). 4. Avoid overly emotional thinking. Emotions can tell us what we value, but
they are not always helpful when it comes to making critical decisions.
Example: you may have strong responses when hearing about differences in the cognitive abilities of males and females (see Module 3.1 ); however, it is important to put those aside to examine the studies themselves.
5. Tolerate ambiguity. Most complex issues do not have clear-cut answers. Example: Psychologists have identified a number of factors leading to depression, but no single factor guarantees that a person will suffer from this condition (see Module 15.3 ).
6. Consider alternative viewpoints and alternative interpretations of the evidence. Example: It is clear that we require sleep in order to function properly; however, there are several theories that can explain the
functions that sleep serves (see Module 5.1 ).
Using these critical-thinking skills might seem difficult at first. However, with some practice, they will soon seem like a natural way of viewing the world. They will also help you see through some rather unbelievable stories.
Myths in Mind Abducted by Aliens!
Independent reports of alien abductions often resemble events and characters depicted in science fiction movies. shiva3d/Shutterstock
Occasionally we hear claims of alien abductions, ghost sightings, and other paranormal activity. Countless television shows and movies, both fictional and documentary based, reinforce the idea that these types of events can and do occur. Alien abductions are probably the most far- fetched stories, yet many people believe they occur or at least regard them as a real possibility. What is even more interesting are the extremely detailed accounts given by purported alien abductees. However, physical evidence of an abduction is always lacking. So what can we make of the validity of alien abduction stories?
Scientific and critical thinking involve the use of the principle of parsimony , which states that the simplest of all competing explanations (the most “parsimonious”) of a phenomenon should be the one we accept. Is there a simpler explanation for alien abductions? Probably. Psychologists who study alien abduction cases have discovered some interesting patterns. First, historical reports of
abductions typically spike just after the release of science fiction movies featuring space aliens. Details of the reports often follow specific details
seen in these movies (Clancy, 2005). Second, it probably would not be too surprising to learn that people who report being abducted are prone to fantasizing and having false memories (vivid recollection and belief in
something that did not happen; Lynn & Kirsch, 1996; Spanos et al., 1994). Finally, people who claim to have been abducted are likely to experience sleep paralysis (waking up and becoming aware of being unable to move—a temporary state that is not unusual) and
hallucinations while in the paralyzed state (McNally et al., 2004). You can likely see how these three factors could explain reports of alien abductions. Following the principle of parsimony typically leads to real, though sometimes less spectacular, answers—although these answers might leave the so-called “abductees” feeling alienated.
Module 1.1b Quiz:
Building Scientific Literacy
Know . . .
1. Someone who exercises curiosity and skepticism about assumptions and beliefs is using .
A. critical thinking B. a hypothesis C. pseudoscience D. the biopsychosocial model
Understand . . .
2. Scientific literacy does not include . A. gathering knowledge
B. accepting common sense explanations C. critical thinking D. applying scientific information to everyday problems
Apply . . .
3. Paul is considering whether to take a cholesterol-reducing medicine that has been recommended by his physician. He goes to the library and learns that the government agency that oversees medications—Health Canada—has approved the medication after dozens of studies had been conducted on its usefulness. Which aspect of critical thinking does this
best represent? A. Paul has examined the nature and source of the evidence. B. Paul was simply curious. C. Paul did not consider alternative viewpoints. D. Paul was avoiding overly emotional thinking.
Module 1.1 Summary
biopsychosocial model
critical thinking
falsifiable
hypothesis
principle of parsimony
pseudoscience
psychology
scientific literacy
Know . . . the key terminology of the scientific method.1.1a
scientific method
theory
The basic model in Figure 1.1 guides us through the steps of the scientific method. Scientific theories generate hypotheses, which are specific and testable predictions. If a hypothesis is confirmed, new hypotheses may stem from it, and the original theory receives added support. If a hypothesis is rejected, the original hypothesis may be modified and retested, or the original theory may be modified or rejected.
Scientific literacy refers to the process of how we think about and understand scientific information. The model for scientific literacy was summarized in Figure 1.3 . Working the model involves answering a set of questions:
What do we know about a phenomenon?
How can science explain it?
Can we critically evaluate the evidence?
Why is this relevant?
You will see this model applied to concepts in each chapter of this text. This includes gathering knowledge, explaining phenomena in scientific terms, engaging in critical thinking, and knowing how to apply and use your knowledge.
This is a model we will use throughout the text. As you consider each topic, think about how biological factors (e.g., the brain and genetics) are influential. Also consider how psychological factors such as thinking, learning, emotion, and memory are relevant. Social and cultural factors complete the model. These
Understand . . . the steps of the scientific method.1.1b
Understand . . . the concept of scientific literacy.1.1c
Apply . . . the biopsychosocial model to behaviour.1.1d
three interacting factors influence our behaviour.
To be useful, critical thinking is something not just to memorize, but rather to use and apply. Remember, critical thinking involves (1) being curious, (2) examining evidence, (3) examining assumptions and biases, (4) avoiding emotional thinking, (5) tolerating ambiguity, and (6) considering alternative viewpoints. Try applying these steps in the activity below.
Apply Activity Practise applying critical thinking skills to the following scenario.
Magic Mileage is a high-tech fuel additive that actually increases the distance you can
drive for every litre by 20%, while costing only a fraction of the gasoline itself!! Wouldn’t
you like to cut your fuel expenses by one-fifth? Magic Mileage is a blend of complex
engine-cleaning agents and a patented “octane-booster” that not only packs in extra
kilometres per litre but also leaves your engine cleaner and running smooth while
reducing emissions!
1. How might this appeal lead to overly emotional thinking? 2. Can you identify assumptions or biases the manufacturer might have? 3. Do you have enough evidence to make a judgment about this product?
As you read in this module, the term theory is often used very casually in the English language, sometimes synonymously with opinion. Thus, it is important to analyze the scientific meaning of the term and contrast it with the alternatives. A scientific theory is an explanation for a broad range of observations, integrating numerous findings into a coherent whole. Remember, theories are not the same thing as opinions or beliefs, all theories are not equally plausible, and, strange as it may sound, the quality of a scientific theory is not determined by the number of people who believe it to be true.
Apply . . . the steps in critical thinking.1.1e
Analyze . . . the use of the term scientific theory.1.1f
Module 1.2 How Psychology Became a Science
Nagib/Shutterstock
Learning Objectives
Know . . . the key terminology of psychology’s history. Understand . . . how various philosophical and scientific fields became major influences on psychology. Apply . . . your knowledge to distinguish among the different specializations in psychology.
1.2a 1.2b
1.2c
When we try to imagine the earliest investigations of human behaviour, we rarely think about axe wounds to the head. As it turns out, we should. The ancient Egyptians were a fierce military force for several centuries. The wealth accumulated during these military campaigns filled the palaces of the pharaohs with gold and jewels and allowed them to construct massive monuments like the pyramids. But one side effect of having many battles was that members of the Egyptian army also suffered many injuries, including some to the head. Although the primitive medical knowledge of the time condemned most brain-injured patients to death, some did in fact survive and attempted to return to their normal lives. However, as one might expect when someone has suffered an axe (khopesh) wound to the head, such attempts were not always successful. Similar problems had likely occurred in earlier times, but what makes ancient Egypt stand out is that military doctors noticed—and documented —patterns that emerged in their patients. As noted in the Edwin Smith papyrus (obviously named after the American discoverer, not the Egyptian authors), damage to different parts of the brain resulted in different types of impairments ranging from problems with vision to problems with higher-order cognitive abilities. Although primitive by modern standards, this initial attempt to link a brain-based injury to a change in behaviour marked the first step toward our modern study of psychology.
Focus Questions
1. Why did it take so long for scientists to start applying their methods to human thoughts and experience?
2. What has resulted from the application of scientific methods to human behaviour?
Analyze . . . how the philosophical ideas of empiricism and determinism are applied to human behaviour.
1.2d
Psychology has long dealt with some major questions and issues that span philosophical inquiry and scientific study. For example, psychologists have questioned how environmental, genetic, and physiological processes influence behaviour. They have wrestled with the issue of whether our behaviour is determined by external events, or if we have free will to act. Psychology’s search for answers to these and other questions continues, and in this module we put this search into historical context and see how these questions have influenced the field of psychology as it exists today.
Psychology’s Philosophical and Scientific Origins
Science is more than a body of facts to memorize or a set of subjects to study. Science is actually a philosophy of knowledge that stems from two fundamental beliefs: empiricism and determinism.
Empiricism is a philosophical tenet that knowledge comes through experience. In everyday language, you might hear the phrase “Seeing is believing,” but in the scientific sense, empiricism means that knowledge about the world is based on careful observation, not on common sense or speculation. Whatever we see or measure should be observable by anyone else who follows the same methods. In addition, scientific theories must be logical explanations of how the observations fit together. Thus, although the empiricist might say, “Seeing is believing,” thinking and reasoning about observations are just as important.
Determinism is the belief that all events are governed by lawful, cause-and- effect relationships. This is easy enough when we discuss natural laws such as gravity—we probably all agree that if you drop an object, it will fall (unless it is a helium balloon). But does the lawfulness of nature apply to the way we think and act? Does it mean that we do not have control over our own actions? This
interesting philosophical debate is often referred to as free will versus
determinism. While we certainly feel as if we are in control of our own behaviours —that is, we sense that we have free will—there are compelling reasons (discussed later in this book) to believe that some of our behaviours are determined. The level of determinism or free will psychologists attribute to humans is certainly debated, and to be a psychologist, you do not have to believe that every single thought, behaviour, or experience is determined by natural laws. But psychologists certainly do recognize that behaviour is determined by both internal (e.g., genes, brain chemistry) and external (e.g., cultural) influences.
Psychological science is both empirical and deterministic. We now know that behaviour can only be understood by making observations and testing hypotheses. We also know that behaviour occurs at several different levels ranging from cells to societies. However, this modern knowledge did not appear overnight. Instead, our understanding of why we behave the way we do is built upon the hard work, creativity, and astute observational powers of scientists throughout history dating (at least) as far back as the ancient Mediterranean societies of Egypt, Greece, and Rome.
Influences from the Ancients: Philosophical
Insights into Behaviour
As you read in the opening section of this module, ancient Egyptian doctors noticed that damage to different brain areas led to vastly different impairments. While such an observation marked the first recorded linking of biology and behaviour, it was not the only important insight to come out of ancient societies.
In ancient Greece, the physician Hippocrates (460–370 BCE) developed the world’s first personality classification scheme. The ancient Greeks believed that
four humours or fluids flowed throughout the body and influenced both health and personality. These four humours included blood, yellow bile, black bile, and phlegm (theories were a bit gross in ancient times). Different combinations of these four humours were thought to lead to specific moods and behaviours. Galen of Pergamon (127–217), arguably the greatest of the ancient Roman
physicians, refined Hippocrates’s more general work and suggested that the four
humours combined to create temperaments, or emotional and personality characteristics that remained stable throughout the lifetime. Galen’s four temperaments (each related to a humour) included:
Sanguine (blood), a tendency to be impulsive, pleasure-seeking, and charismatic;
Choleric (yellow bile), a tendency to be ambitious, energetic, and a bit aggressive;
Melancholic (black bile), a tendency to be independent, perfectionistic, and a bit introverted; and
Phlegmatic (phlegm), a tendency to be quiet, relaxed, and content with life.
Although such a classification system is primitive by modern standards, the work of Hippocrates and Galen moved the understanding of human behaviour forward by attempting to categorize different types of personalities; we will see much more scientifically rigorous attempts to do the same thing later in this book (see Module 12.1 ). However, the golden age of Greek and Roman thought came to a crashing halt in the latter parts of the fourth century; this was the beginning of the Dark Ages. Although some discoveries were made about human anatomy during this period, few notable advances in the study of behaviour were made over the next one thousand years.
Psychology also did not immediately benefit from the scientific revolution of the 1500s and 1600s. Once the scientific method started to take hold around 1600, physics, astronomy, physiology, biology, and chemistry all experienced unprecedented growth in knowledge and technology. But it took psychology until the late 1800s to become scientific. Why was this the case? One of the main
reasons was zeitgeist, a German word meaning “spirit of the times.” Zeitgeist
refers to a general set of beliefs of a particular culture at a specific time in history. It can be used to understand why some ideas take off immediately, whereas other perfectly good ideas may go unnoticed for years.
The power of zeitgeist can be very strong, and there are several ways it prevented psychological science from emerging in the 1600s. Perhaps most
important is that people were not ready to accept a science that could be applied to human behaviour and thought. To the average person of the 1600s, viewing human behaviour as the result of predictable physical laws was troubling. Doing
so would seem to imply the philosophy of materialism : the belief that humans, and other living beings, are composed exclusively of physical matter. Accepting this idea would mean that we are nothing more than complex machines that lack a self-conscious, self-controlling soul. The opposing belief,
that there are properties of humans that are not material (a mind or soul separate from the body), is called dualism .
Although most early thinking about the mind and behaviour remained philosophical in nature, scientific methods were generating great discoveries for the natural sciences of physics, biology, and physiology. This meant that the early influences on psychology came from the natural and physical sciences.
(Figure 1.5 provides a timeline that summarizes some of the major events in the history of psychology.)
Figure 1.5 Major Events in the History of Psychology
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Reproduced with permission. No further reproduction or distribution is permitted without written permission from the American
Psychological Association; Left, bottom: Bettmann/Getty Images; centre, top: © 2016 Canadian Psychological Association
Inc. used with permission. All rights reserved. Canadian Psychological Association Inc. logo is a registered trademark of the
Canadian Psychological Association Inc; centre, bottom: pio3/Shutterstock.com; right, centre (right): AP Images; right, centre
(left): Science and Society/SuperStock; right, bottom: Copyright © by The Canadian Society for Brain, Behaviour and
Cognitive Science (CSBBCS). Reprinted by permission.
Influences from Physics: Experimenting with the
Mind
The initial forays into scientific psychology were conducted by physicists and physiologists. One of the earliest explorations was made by Gustav Fechner
(1801–1887), who studied sensation and perception (see Module 4.1 ). As a physicist, Fechner was interested in the natural world of moving objects and energy. He turned his knowledge to psychological questions about how the physical and mental worlds interact. Fechner coined the term psychophysics , which is the study of the relationship between the physical world and the mental representation of that world.
As an example of psychophysical research, imagine you are holding a one- pound (0.45 kg) weight in your right hand and a five-pound (2.27 kg) weight in your left hand. Obviously, your left hand will feel the heavier weight, but that is not what interested Fechner. What if a researcher places a quarter-pound weight (113 g) in each hand, resting on top of the weight that is already there? Fechner wanted to know which of the quarter-pound weights would be perceived as heavier. Oddly enough, although both weigh the same amount, the quarter- pound weight in your right hand will be more noticeable than the quarter-pound
weight added to your left hand, almost as if it were heavier (see Figure 1.6 ). Through experiments like these, Fechner demonstrated basic principles of how the physical and mental worlds interact. In fact, he developed an equation to
precisely calculate the perceived change in weight, and then extended this formula to apply to changes in brightness, loudness, and other perceptual
experiences. This work served as the foundation for the modern study of perception.
Figure 1.6 The Study of Psychophysics Gustav Fechner studied relationships between the physical world and our mental representations of that world. For example, Fechner tested how people detect changes in physical stimuli.
Influences from Evolutionary Theory: The Adaptive
Functions of Behaviour
Around the same time Fechner was doing his experiments, Charles Darwin (1809–1882) was studying the many varieties of plants and animals found around the world. Darwin noticed that animal groups that were isolated from one another often differed by only minor variations in physical features. These variations seemed to fine-tune the species according to the particular environment in which they lived, making them better equipped for survival and
reproduction. Darwin’s theory of evolution by natural selection was based on his observations that the genetically inherited traits that contribute to survival and reproductive success are more likely to flourish within the breeding population (i.e., useful traits will be passed on to future generations). These specific traits differ across locations because different traits will prove beneficial in different environments. This theory explains why there is such a diversity of life on Earth.
Darwin’s theory also helps to explain human (and animal) behaviour. As Darwin
pointed out in The Expression of the Emotions in Man and Animals (1872), behaviour is shaped by natural selection, just as physical traits are (see Module 3.1 ). Over the course of millions of years of evolution, a certain range of behaviours helped our ancestors survive and reproduce. The modern behaviours that we engage in every day—memory, emotions, forming social bonds, and so on—were the same behaviours that allowed our ancestors to flourish over the course of our species’ history. The same principle applies to other species as well. Darwin’s recognition that behaviours, like physical traits, are subject to hereditary influences and natural selection was a major contribution to psychology.
Charles Darwin proposed the theory of natural selection to explain how evolution works. Pictorial Press Ltd/Alamy Stock Photo
Influences from Medicine: Diagnoses and
Treatments
Medicine contributed a great deal to the biological perspective in psychology. It
also had a considerable influence on the development of clinical psychology , the field of psychology that concentrates on the diagnosis and treatment of psychological disorders. A research topic that impacted both fields was the study of localization of brain function, the idea that certain parts of the brain control specific mental abilities and personality characteristics.
In the mid-1800s, localization was studied in two different ways. The first was
phrenology, which gained considerable popularity for more than 100 years thanks to physicians Franz Gall (1758–1828) and Johann Spurzheim (1776– 1832). Gall, Spurzheim, and their followers believed that the brain consisted of 27 “organs,” corresponding to mental traits and dispositions that could be detected by examining the surface of the skull. Although it seems silly now, there was a logic behind phrenology. Its supporters believed that different traits and abilities were distributed across different regions of the brain (e.g., “combativeness” was located at the back of the brain behind the ears). If a person possessed a particular trait or ability, then the brain area related to that characteristic would be larger in the same way that the muscles in your arms would be larger if your job required you to lift things. Larger brain areas would cause bumps on a person’s head in the same way that a muscular arm could cause the fabric of a shirt to stretch. So, by measuring the bumps on a person’s head, proponents of phrenology believed that it would be possible to identify the different traits that an individual possessed. Phrenology continued to gather supporters for nearly a century before being abandoned by serious scientists.
You may have encountered images of the phrenological map of the skull (see Figure 1.7 ).
Figure 1.7 A Phrenology Map Early scholars of the brain believed that mental capacities and personalities could be measured by the contours, bumps, and ridges distributed across the surface of the skull. Classic Image/Alamy Stock Photo
The other approach to localization entailed the study of brain injuries and the ways in which they affect behaviour. This work had a scientific grounding that phrenology lacked. There were many intriguing cases described by physicians of the 1800s. For example:
Physician Paul Broca found that a patient who had difficulties producing spoken language had brain damage in an area of the left frontal lobes of brain (near his left temple).
Prussian physician Karl Wernicke found that damage to another area in the left hemisphere led to problems with speech comprehension. Doctors in Vermont described a railroad employee who became impulsive and somewhat childlike after suffering damage to part of his frontal lobes.
These compelling clinical cases provided early brain researchers with new information about the roles of different brain areas, findings that are still relevant today.
Of course, the influence of the medical perspective was not isolated to studies of the localization of brain function. Additional medical influences on psychology came from outside of mainstream practices. Franz Mesmer, an 18th-century Austrian physician practising in Paris, believed that prolonged exposure to magnets could redirect the flow of metallic fluids in the body, thereby curing disease and insanity. Although his claim was rejected outright by the medical and scientific communities in France, some of his patients seemed to be cured after being lulled into a trance. Modern physicians and scientists attribute these
“cures” to the patients’ belief in the treatment—what we now call psychosomatic medicine.
The medical establishment eventually grew more intrigued by the trances
Mesmer produced in his patients, naming the phenomenon hypnosis (see Module 5.2 ). This practice also caught the attention of an Austrian physician named Sigmund Freud (1856–1939), who began to use hypnosis to treat his own patients. Freud was particularly interested in how hypnosis seemed to have
cured several patients of hysterical paralysis—a condition in which an individual loses feeling and control in a specific body part, despite the lack of any known neurological damage or disease. These experiences led Freud to develop his
famous theory and technique called psychoanalysis.
Psychoanalysis is a psychological approach that attempts to explain how behaviour and personality are influenced by unconscious processes. Freud acknowledged that conscious experience includes perceptions, thoughts, a sense of self, and the sense that we are in control of ourselves. However, he also believed in an unconscious mind that contained forgotten episodes from early childhood as well as urges to fulfill self-serving sexual and aggressive impulses. Freud proposed that because these urges were unconscious, they could exert influence in strange ways, such as restricting the use of a body part (psychosomatic or hysterical paralysis). Freud believed hypnosis played a valuable role in his work. When a person is hypnotized, dreaming, or perhaps medicated into a trancelike state, he thought, the psychoanalyst could have more direct access into the individual’s unconscious mind. Once Freud gained access, he could attempt to determine and correct any desires or emotions he believed were causing the unconscious to create the psychosomatic conditions.
Sigmund Freud developed the concept of an unconscious mind and its underlying processes in his theory of psychoanalysis. Mary Evans Picture Library/Alamy Stock Photo
Although Freud did not conduct scientific experiments, his legacy can be seen in some key elements of scientific psychology. First, many modern psychologists make inferences about unconscious mental activity, just as Freud had advocated (although not all of them agree with the specific theories proposed by Freud). Second, the use of medical ideas to treat disorders of emotions, thought, and
behaviour—an approach known as the medical model—can be traced to Freud’s influence. Third, Freud incorporated evolutionary thinking into his work; he emphasized how physiological needs and urges relating to survival and reproduction can influence our behaviour. Finally, Freud placed great emphasis on how early life experiences influence our behaviour as adults—a perspective that comes up many times in this text. So, although people often mock some of
his theories, Freud’s impact on modern psychology is deserving of respect.
The Influence of Social Sciences: Measuring and
Comparing Humans
A fifth influential force came out of the social sciences of economics, sociology, and anthropology. These disciplines developed statistical methods for measuring human traits, which soon became relevant to the emerging field of psychology. An early pioneer in measuring perception and in applying statistical analyses to the study of behaviour was Sir Francis Galton.
Galton was also influential in the study of individual differences between people. He noticed that great achievement tended to run in families; as a result, Galton came to believe that heredity (genetics) could explain the physical and psychological differences found in a population. After all, Galton’s cousin—some guy named Charles Darwin—was a great naturalist, his uncle Erasmus was a celebrated physician and writer, and Galton himself was no slouch (he began reading as a 2-year-old child, and was a fan of Shakespeare by age 6). To Galton, it seemed natural that people who did better in scholarship, business,
and wealth were able to do so because they were better people (genetically speaking).
To support his beliefs, Galton developed ways of measuring what he called
eminence—a combination of ability, morality, and achievement. One observation supporting his claim for a hereditary basis for eminence was that the closer a relative, the more similar the traits. Galton was one of the first investigators to
scientifically take on the question of nature and nurture relationships , the inquiry into how heredity (nature) and environment (nurture) influence behaviour and mental processes. Galton came down decidedly on the nature side, seemingly ignoring the likelihood that nurturing influences such as upbringing and family traditions, rather than biological endowments, could explain similarities among relatives.
Galton’s beliefs and biases led him to pursue scientific justification for eugenics,
which literally translates as “good genes.” He promoted the belief that social programs should encourage intelligent, talented individuals to have children, whereas criminals, those with physical or mental disability, and non-White races
should not receive such encouragement (see Module 9.1 ). The eugenics movement was based largely on what the researchers wanted to believe was true, not on quality research methods. It ultimately led to the mistreatment of many individuals, particularly immigrants and the descendants of slaves who were not of Galton’s own demographic group. It also influenced the thinking of Adolf Hitler, with chilling consequences.
In modern times, biological and genetic approaches to explaining behaviour are thriving (and, thankfully, eugenics has vanished). With the advent of new brain-
imaging techniques, this area of psychology— biological psychology—is poised to provide new and important insights into the underlying causes of our behaviour.
Module 1.2a Quiz:
Psychology’s Philosophical and Scientific Origins
Know . . .
1. In philosophical terms, a materialist is someone who might believe that A. money buys happiness. B. species evolve through natural selection. C. personality can be measured by feeling for bumps on the surface
of the skull.
D. everything that exists, including human beings, is composed exclusively of physical matter.
Understand . . .
2. According to Sigmund Freud, which of the following would be the most
likely explanation for why someone is behaving aggressively?
A. They are acting according to psychophysics. B. There is something going on at the unconscious level that is
causing them to behave this way.
C. Their cigars are missing and someone’s got to pay. D. The environment is determining their behavioural response.
Apply . . .
3. Jan believes that all knowledge is acquired through careful observation. Jan is probably .
A. an empiricist B. a supporter of eugenics C. a clinical psychologist D. a phrenologist
Analyze . . .
4. Francis Galton made a significant contribution to psychology by introducing methods for studying how heredity contributes to human behaviour. Which alternative explanation did Galton overlook when he argued that heredity accounts for these similarities?
A. The primary importance of the nature side of the nature-versus- nurture debate
B. The fact that people who share genes live together in families, so they tend to share environmental privileges or disadvantages
C. A materialistic account of behaviour D. The concept of dualism, which states that the mind is separate
from the body
The Beginnings of Contemporary Psychology
Before psychology became its own discipline, there were scientists working across different fields who were converging on a study of human behaviour. By modern standards, Darwin, Fechner, and others had produced psychological research but it was not referred to as such because the field had not yet fully formed. Nevertheless, progress toward a distinct discipline of psychology was beginning.
By the late 1800s, the zeitgeist had changed so that the study of human behaviour was acceptable. Ideas flourished. Most importantly, researchers began to investigate behaviour in a number of different ways. You will see this breadth as you read the rest of this module. We will include references to other
modules (e.g., see Module 6.1 ) to illustrate that the history that you are reading in this module had a direct effect on the modern understanding of behaviour that you will read about in the rest of this textbook.
Structuralism and Functionalism: The Beginnings
of Psychology
Most contemporary psychologists agree that Wilhelm Wundt (1832–1920) was largely responsible for establishing psychology as an independent scientific field. Wundt established the first laboratory dedicated to studying human behaviour in 1879 at the University of Leipzig, where he conducted numerous experiments on
how people sense and perceive. His primary research method was introspection, meaning “to look within.” Introspection required a trained volunteer to experience a stimulus and then report each individual sensation he or she could identify. For example, if the volunteer was given a steel ball to hold in one hand, he would likely report the sensations of cold, hard, smooth, and heavy. To Wundt, these basic sensations were the mental “atoms” that combined to form the molecules
of experience. Wundt also developed reaction time methods as a way of measuring mental effort. In one such study, volunteers watched an apparatus in which two metal balls swung into each other to make a clicking sound. The volunteers required about one-eighth of a second to react to the sound, leading Wundt to conclude that mental activity is not instantaneous, but rather requires a small amount of effort measured by the amount of time it takes to react. What
made Wundt’s work distinctly psychological was his focus on measuring mental events and examining how they were affected by his experimental manipulations.
Wundt’s ideas made their way to the United States and Canada through students who worked with him. However, whereas Wundt’s research often attempted to link a person’s perceptions with concepts such as free will (a philosophy known
as voluntarism), many of his students wanted to move psychological research in a different direction (Rieber & Tobinson, 1980). One student, Edward Titchener, adopted the same method of introspection used by Wundt to devise an organized map of the structure of human consciousness. His line of research, structuralism , was an attempt to analyze conscious experience by breaking it down into basic elements, and to understand how these elements work together. Titchener chose the term elements deliberately as an analogy with the periodic table in the physical sciences. He believed that mental experiences were made up of a limited number of sensations, which were analogous to elements in physics and chemistry. According to Titchener, different sensations can form and create complex compounds, just like hydrogen and oxygen can
combine to form water—H O—or the hydroxide ion—OH . The challenge for psychologists was to determine which elements were grouped together during different conscious experiences and to figure out what caused these specific
groupings to occur (Titchener, 1898).
2 –
German scientist Wilhelm Wundt is widely credited as the “father” of experimental psychology. AKG Images/Newscom
The same year Wundt set up his first laboratory, an American scholar named
William James (1842–1910) set out to write the first textbook in psychology, The Principles of Psychology, which was eventually published in 1890. Trained as a physician, James combined his knowledge of physiology with his interest in the philosophy of mental activity. Among his many interests, he sought to understand how the mind functions. In contrast to structuralism, which looks for permanent, unchanging elements of thought, James was influenced by Darwin’s evolutionary principles; he preferred to examine behaviour in context and explain how our thoughts and actions help us adapt to our environment. This led to the
development of functionalism, the study of the purpose and function of behaviour and conscious experience. According to functionalists, in order to fully understand a behaviour, one must try to figure out what purpose it may have served over the course of our evolution. These principles are found today in the
modern field of evolutionary psychology, an approach that interprets and explains modern human behaviour in terms of forces acting upon our distant
ancestors (see Module 3.1 ). According to this approach, our brains and behaviours have been shaped by the physical and social environment that our ancestors encountered. Over the next century, this idea was extended to a number of subfields in psychology ranging from the study of brain structures to the study of social groups. Indeed, regardless of their research area, most
psychologists are still fascinated by the question, What function does the behaviour we’re investigating serve? In other words, why do we behave the way we do?
William James was a highly influential American psychologist who took a functionalist approach to explaining behaviour. Mary Evans Picture Library/Alamy Stock Photo
During the early years of psychology, the pioneers of this field were trying to find a way to use the methods and instruments of the natural sciences to understand behaviour. Although some of their techniques fell out of favour, by the beginning of the 20th century it was clear that the discipline of psychology was here to stay. With that sense of permanence in place, the second generation of psychologists could focus on refining the subject matter and the methods, and on turning psychology into a widely accepted scientific field.
The Rise of Behaviourism
Early in the 20th century, biologists became interested in how organisms learn to anticipate their bodily functions and responses. One of the first to do so was Professor Edwin Twitmyer (1873–1943), an American psychologist interested in reflexes. His work involved a contraption with a rubber mallet that would regularly tap the patellar tendon just below the kneecap; this, of course, causes a kicking reflex in most individuals. To make sure his volunteers were not startled by the mallet, the contraption would ring a bell right before the mallet struck the tendon. As is often the case in experiments, the technology failed after a number of these bell-ringing and hammer-tapping combinations: The machine rang the bell, but the hammer did not come down on the volunteer’s knee. But the real surprise was this—the volunteer’s leg kicked anyway! How did that happen? Because the sound of the bell successfully predicted the hammer, the ringing soon had the
effect of the hammer itself, a process now called classical conditioning (see Module 6.1 ). The study of conditioning would soon become a focus of behaviourism , an approach that dominated the first half of the 20th century of North American psychology and had a singular focus on studying only observable behaviour, with little to no reference to mental events or instincts as possible influences on behaviour.
Twitmyer’s research was coolly received when he announced his findings at the
American Psychological Association meeting. Not a single colleague bothered to ask him a question. The credit for discovering classical conditioning typically goes to a Russian physiologist named Ivan Pavlov (1849–1936). Pavlov, who won the 1904 Nobel Prize for his research on the digestive system, noticed that the dogs in his laboratory began to salivate when the research technician entered the room and turned on the device that distributed the meat powder
(food). Importantly, salivation occurred before the delivery of food, suggesting that the dogs had learned an association between the technician and machine noises and the later appearance of food. This observation quickly led to more focused research on mechanisms of learning; the principles of learning that Pavlov and others identified provided a foundation for the behaviourist movement.
Ivan Pavlov (on the right) explained classical conditioning through his studies of salivary reflexes in dogs. Mansell/Time Life Pictures/Getty Images
In North America, behaviourism was championed by John B. Watson, a
researcher at Johns Hopkins University in Baltimore (1878–1958). As research accumulated on the breadth of behaviours that could be conditioned, Watson began to believe that all behaviour could ultimately be explained through conditioning. This emphasis on learning also came with stipulations about what could and could not be studied in psychology. Watson was adamant that only observable changes in the environment and behaviour were appropriate for scientific study. Methods such as Wundt’s introspection, he said, were too subjective to even consider:
Psychology as the behaviorist views it is a purely objective natural science. Its
theoretical goal is the prediction and control of behavior. Introspection forms no
essential part of its methods. (Watson, 1913, p. 158)
In the diplomatic world of science, this statement was akin to carving “Wundt sucks!” in a park bench. Watson believed so much in the power of experience (and so little in the power of genetics) that he was certain he could engineer a personality however he wished, if given enough control over the environment. Perhaps his most famous statement sums it up:
Give me a dozen healthy infants, well-formed, and my own specified world to bring
them up in and I’ll guarantee to take any one at random and train him to become any
type of specialist I might select—doctor, lawyer, artist, merchant-chief and, yes, even
beggar-man and thief, regardless of his talents, penchants, tendencies, abilities,
vocations, and race of his ancestors. (John Broadus Watson, Behaviorism. Chicago:
University of Chicago Press. p. 82, 1930.)
After a rather public indiscretion involving a female graduate student (due to his wife’s social status, his extramarital affair appeared on the front page of the
Baltimore newspapers; Fancher, 1990), Watson was dismissed from his university job. But, he quickly found his new career—as well as his fortune—in advertising. Most advertisers at the time just assumed they should inform people about the merits of a product. Watson and his colleagues applied a scientific approach to advertising and discovered a consumer’s knowledge about the product really was not that important, so long as he or she had positive emotions associated with it. Thus, Watson’s company developed ads that employed
behaviourist principles to form associations between a product’s brand image and positive emotions. If Pavlov’s dogs could be conditioned to salivate when they heard a tone, what possibilities might there be for conditioning humans in a similar way? Modern advertisers want the logos for their brands of snacks or the trademark signs for their restaurants to bring on a specific craving, and some salivation along the way. And so, from beer commercials with scantily clad women dancing at parties, to car commercials with high-intensity music and vistas of the Cabot Trail, and from impossibly cute kittens playing with toilet paper rolls to giant billboards of bunnies and hippos pitching telecommunications products, the influence of John B. Watson and his colleagues on modern advertising is felt every day.
Radical Behaviourism
The study of learning was not limited to classical conditioning. As early as 1905, psychologists such as Edward Thorndike (1874–1949) had shown that the frequency of different behaviours could be changed based on whether or not that
behaviour led to positive consequences or “satisfaction” (Thorndike, 1905). Taking up the reins from Thorndike was B. F. Skinner (1904–1990), another behaviourist who had considerable influence over North American psychology for
several decades (see Module 6.2 ).
In Skinner’s view, known as radical behaviourism, the foundation of behaviour was how an organism responded to rewards and punishments. This theory is logical in many ways—we tend to repeat actions that are rewarded (e.g., studying for exams leads to better grades, so we study for other exams) and avoid actions that lead to punishment (e.g., if you vomit after eating a 2L container of ice cream, you will be unlikely to do so again . . . for a while). In order to identify the principles of reward and punishment, Skinner opted to use a tightly controlled experimental setup involving animals such as rats and pigeons. Typically, these studies occurred with animals held in small chambers in which they could manipulate a lever to receive rewards. The experimenter would control when rewards were available, and would observe the effects that changing the reward schedule had on the animals’ behaviour. You might ask what this work had to do with human behaviour. The behaviourists believed that
the principles of reward and punishment could apply to all organisms, both human and nonhuman. Indeed, Watson explicitly stated that behaviourist
psychology “recognizes no line between man and brute” (Watson, 1913, p. 158).
B. F. Skinner revealed how rewards affect behaviour by conducting laboratory studies on animals. Nina Leen/Time Life Pictures/Getty Images
Humanistic Psychology Emerges
Psychology, by the mid-20th century, was dominated by two perspectives, behaviourism and Freudian psychoanalytic approaches, which had almost entirely removed free will from the understanding of human behaviour. To the behaviourists, human experience was the product of a lifetime of rewards, punishments, and learned associations. To the psychoanalysts, human experience was the result of unconscious forces at work deep in the human psyche. From both perspectives, the individual person was merely a product of
forces that operated on her, and she had little if any control over her own destiny or indeed, even her own choices, beliefs, and feelings.
In contrast to these disempowering perspectives, a new movement of psychologists arose, which emphasized personal responsibility; free will; and the universal longing for growth, meaning and connection, and which highlighted the power that individuals possessed to shape their own consciousness and choose
their own path through life. This new perspective, humanistic psychology , focuses on the unique aspects of each individual human, each person’s freedom to act, his or her rational thought, and the belief that humans are fundamentally different from other animals. Among the many major figures of humanistic psychology were Carl Rogers (1902–1987) and Abraham Maslow (1908–1970). Both psychologists focused on the positive aspects of humanity and the factors that lead to a productive and fulfilling life. Humanistic psychologists sought to
understand the meaning of personal experience. They believed that people could attain mental well-being and satisfaction through gaining a greater understanding of themselves, rather than by being diagnosed with a disorder or having their problems labelled. Both Rogers and Maslow believed that humans strive to develop a sense of self and are motivated to personally grow and fulfill their
potential (see Module 12.3 ). This view stands in particular contrast to the psychoanalytic tradition, which originated from a medical model and, therefore, focused on illnesses of the body and brain. The humanistic perspective also contrasted with behaviourism in proposing that humans had the freedom to act and a rational mind to guide the process.
The Brain and Behaviour
The behaviourists and humanists were not the only researchers attempting to understand human abilities. Many neurologists, surgeons, and brain scientists were also focused on these questions. Notable among them was Donald Hebb (1904–1985), a Canadian neuroscientist working at the Montreal Neurological Institute. Hebb conducted numerous studies examining how cells in the brain change over the course of learning. He observed that when a brain cell consistently stimulates another cell, metabolic and physical changes occur to strengthen this relationship. In other words, cells that fire together wire together
(Hebb, 1949; see Module 7.1 ). This theory, now known as Hebb’s Law, demonstrated that memory—a behaviour that we can measure and that affects so many parts of our lives—is actually related to activity occurring at the cellular
level (Brown & Milner, 2003; Cooper, 2005). It also reinforced the notion that behaviour can be studied at a number of different levels ranging from neurons
(brain cells) to the entire brain. (Later research, discussed in Module 7.3 , has noted that memory is related to social factors as well.)
Further evidence for the relationship between the brain and everyday behaviours came from the stimulating work of Wilder Penfield (1891–1976), founder and original director of the Montreal Neurological Institute. Along with his colleague, Herbert Jasper, Penfield developed a surgical procedure to help patients with epilepsy. This procedure involved removing cells from the brain regions where the seizures began; doing so would prevent the seizures from spreading to other areas of the brain. However, before operating, Penfield needed to find a way to map out the functions of the surrounding brain regions so that he could try to avoid damaging areas that performed important functions such as language. To do this, Penfield electrically stimulated each patient’s brain while the patient was under local anesthetic (i.e., was awake, and therefore conscious). The patient was then able to report the sensations he experienced after each burst of electricity. Based on several patients’ reports, Penfield was able to create precise maps of the sensory and motor (movement) cortices in the brain
(Penfield & Jasper, 1951; Todman, 2008). Importantly, his work also showed that people’s subjective experiences can be represented in the brain (see Module 3.3 ). This insight suggested that the simple learning model put forth by the behaviourists was not a complete representation of our complex mental world.
The Cognitive Revolution
Although behaviourism dominated psychology in the United States and Canada throughout the first half of the 20th century, the view that observable behaviours were more important than thoughts and mental imagery was not universal. In Europe, psychologists retained an emphasis on thinking, and ignored the North Americans’ cries to study only what could be directly observed. The European
focus on thought flourished through the early 1900s, long before psychologists in North America began to take seriously the idea that they could study mental processes, even if they could not directly see them. Thus, it was the work of European psychologists that formed the basis of the cognitive perspective. Early evidence of an emerging cognitive perspective concerned the study of memory. The German psychologist Hermann Ebbinghaus (1850–1909) collected reams of
data on remembering and forgetting (see Module 7.2 ). British psychologist Frederick Bartlett (1886–1969) found that our memory was not like a photograph. Instead, our cultural knowledge and previous experiences shape what elements of an event or storyline are judged to be important enough to remember.
Donald Hebb made significant contributions to our understanding of memory and the brain. Montreal Gazette/The Canadian Press
Another precursor to cognitive psychology can be seen in the early to mid-1900s
movement of Gestalt psychology , an approach emphasizing that psychologists need to focus on the whole of perception and experience, rather than its parts (see Module 4.1 ). (Gestalt is a German word that refers to the complete form of an object; see Figure 1.8 .) This contrasts with the structuralist goal of breaking experience into its individual parts. For example, if Wundt or Titchener were to hand you an apple, you would not think, “Round, red, has a stem …”; you would simply think to yourself, “This is an apple.” Gestalt psychologists argued that much of our thinking and experience occur at a higher, more organized level than Wundt emphasized; they believed that Wundt’s approach to understanding experience made about as much sense as understanding water only by studying its hydrogen and oxygen atoms.
Figure 1.8 The Whole Is Greater Than the Sum of Its Parts The Gestalt psychologists emphasized humans’ ability to see whole forms. For example, you probably perceive a sphere in the centre of this figure, even though it does not exist on the page.
Wilder Penfield, founder of the world-famous Montreal Neurological Institute, used electrical stimulation of the brain to discover how movement and touch were represented in the brain. Like Hebb’s, many of his discoveries are still taught in psychology and neuroscience classes throughout the world. Montreal Gazette/The Canadian Press
In the 1950s and 1960s—around the time that there was increasing interest in humanistic psychology—the scientific study of cognition was becoming accepted practice in North American psychology. The invention of the computer gave psychologists a useful analogy for understanding and talking about the mind (the
software of the brain). Linguists such as Noam Chomsky argued that grammar and vocabulary were far too complex to be explained in behaviourist terms; the
alternative was to propose abstract mental processes. There was a great deal of interest in memory and perception as well, but it was not until 1968 that these areas of research were given the name “cognitive psychology” by Ulrich Neisser
(1928–2012). Cognitive psychology is a modern psychological perspective that focuses on processes such as memory, thinking, and language. Thus, much of what cognitive psychologists study consists of mental processes that are inferred through rigorous experimentation.
Social and Cultural Influences
The vast majority of behaviourist and cognitive psychology research focuses on an individual’s responses to some sort of stimulus. Missing from this equation, however, is that fact that people often have to respond to stimuli or events in the presence of other people. The effects of other people on one’s behaviour have not been lost on psychologists; indeed, the recognition of this influence can be found in the very early years of psychology. An American psychologist, Norman Triplett (1861–1931), conducted one of the first formal experiments in this area, observing that cyclists ride faster in the presence of other people than when riding alone. Triplett published the first social psychology research in 1898, and a few social psychology textbooks appeared in 1908.
Despite the early interest in this field, studies of how people influence the behaviour of others did not take off until the 1940s. The events in Nazi-controlled Germany that led up to World War II contributed to the development of this new perspective in psychology. Images from the Holocaust highlighted the need to learn about the role that social factors play in human behaviour. Researchers (and the general public) wanted to understand how normal individuals could be transformed into brutal prison camp guards, how political propaganda affected people, and how society might address issues of stereotyping and prejudice (see Module 13.1 ). This research evolved into what is now known as social psychology , the study of the influence of other people on our behaviour.
However, psychologists also noted that not all people responded to social groups or the presence of others in the same way. While some people were transformed
into prison camp guards in World War II, others objected and joined resistance movements. These individual differences were observable in normal, everyday life as well: Some people are talkative and outgoing while others are quiet.
These observations led to the development of personality psychology , the study of how different personality characteristics can influence how we think and act.
Social psychologists are often inspired to study human behaviours observed in real-world events. Some of these behaviour are heart-warming—others are not. akg-images/Newscom
Although it’s easy to think of social psychology (the effect of external factors) and personality psychology (the effect of internal traits) as being distinct, in reality, your personality and the social situations you are in interact. This relationship was most eloquently described by Kurt Lewin (1890–1947), the founder of modern social psychology. Lewin suggested that behaviour is a function of the individual and the environment, or, if you’re a fan of formulas (and who isn’t?), B = f{I,E}. What Lewin meant was that all behaviours could be predicted and explained through understanding how an individual with a specific set of traits
would respond in a context that involved a specific set of conditions. Take two individuals as an example: One tends to be quiet and engages in solitary activities such as reading, whereas the other is talkative and enjoys being where the action is. Now put them in a social situation, such as a large party at a university dorm or a small get-together at a friend’s house. How will the two behave? Given the disparity between the individuals and between the two environments, we would suspect that very different behaviours would emerge for these two individuals in the different settings. The outgoing person may have a wonderful time at the big party, while the quiet person desperately tries to find someone to talk to or pretends to be fascinated by something on his phone. But, at the smaller get-together, the quieter person will likely be much more relaxed,
while the outgoing person might be bored. Neither behaviour is better, but they are different. These outcomes illustrate the essence of Lewin’s formulation of social psychology.
Module 1.2b Quiz:
The Beginnings of Contemporary Psychology
Know . . .
1. was the study of the basic components of the mind, while examined the role that specific behaviours may have served in our species’ evolution.
A. Structuralism; functionalism B. Behaviourism; functionalism C. Functionalism; structuralism D. Humanism; structuralism
Understand . . .
2. A distinct feature of behaviourism is its A. search for the deeper meaning of human existence.
B. search for patterns that create a whole that is greater than its parts.
C. use of introspection. D. exclusive emphasis on observable behaviour.
Apply . . .
3. Gwen is in search of the deeper meaning of her life, and would like to learn more about her potential as a human being. Which of the following types of psychologists would likely be most useful to her?
A. Humanistic B. Cognitive C. Behaviourist D. Social
4. The Gestalt psychologists, with their focus on perception and experience, are closely linked to modern-day psychologists.
A. developmental B. social C. cognitive D. evolutionary
Emerging Themes in Psychology
The history of psychology is not over, of course. All of the fields discussed in the previous section of this module continue today. Indeed, psychology is expanding, examining new topics and using new research tools to provide interesting insights into human behaviour. In this section, we highlight five trends or topics
that are becoming particularly prominent in psychology. This is not an exhaustive list of “hot topics.” Instead, it is a list of important themes that are currently influencing the course of modern psychology.
Psychology of Women
After reading earlier sections of this module, many readers might assume that psychology is the exclusive domain of older white men, many sporting
impressive beards. In fact, this module does have photographs of nine prominent male psychologists (five with beards). There were female psychologists teaching and performing research during the early stages of the history of psychology. Indeed, Anna Freud (1895–1982) and Karen Horney (1885–1952) made groundbreaking contributions to our understanding of personality. The 1960s saw a dramatic shift in both the role of women in society and in the study of the psychology of women. Until then, many people believed that the male domination of society was due to innate differences between the sexes that made men better leaders; women were thought to be more agreeable and emotional. However, pioneering research from psychologists such as Sandra Bem began to change these views. Researchers began examining how sex differences in power were due in large part to the rampant sexism in politics, the
business world, academia, and the home (Bem & Bem, 1973). They also examined how stereotypes could affect women’s beliefs about their own abilities
(Bem, 1981, 1993). This research led to changes that helped promote greater equality between the sexes. This important work continues today, with new
generations of female and male psychologists working to promote equality.
Studies of the psychology of women also examine important issues such as women’s health, violence toward women, and experiences that are unique to females (e.g., pregnancy). However, this field is not meant to appear “man hating” or exclusive. In fact, many researchers are interested in differences between the sexes and how they influence social behaviour. For instance, in Module 14.2 , you will read about the research of Shelly Taylor, who examined sex differences in response to stress. She found that while males in general produce a “fight or flight” response to stress, females are more likely to seek out social supports, a tendency she called the “tend and befriend” response
(Taylor et al., 2000). Although a complete description of the psychology of women requires its own course, the purpose of this section is to highlight this topic for readers so that they will see how important these types of questions can be for understanding human behaviour, and so that they can better appreciate the obstacles that many of these early researchers faced.
Comparing Cultures
In addition to studying differences between the sexes, researchers have performed numerous studies examining how human behaviour differs across
cultures. Cross-cultural psychology is the field that draws comparisons about individual and group behaviour among cultures; it helps us understand the role of society in shaping behaviour, beliefs, and values. Many cross-cultural studies compare the responses of North American research participants (generally psychology students like you) to those of individuals in non-Western countries such as China or Japan. However, Western countries with high immigration rates like Canada and the U.S. also provide researchers with the opportunity to compare the responses and experiences of first- and second-generation
Canadians (Abouguendia & Noels, 2001; Gaudet et al., 2005). This type of research therefore allows us to examine how people respond when being pulled in different directions by family history and the culture of their current country of residence. Such comparisons are also being performed using brain imaging, demonstrating that our social and cultural experiences can also be embedded in
our brain tissue (Losin et al., 2010).
Pioneering researchers such as Sandra Bem began the systematic study of the psychology of women. Photograph Provided by Daryl Bem
The Neuroimaging Explosion
Although it has been possible to detect brain activity using sensors attached the scalp since the late 1920s, the use of brain imaging to study behaviour became much more common in the early 1990s. It was at this time that a technique
known as functional magnetic resonance imaging (fMRI) was developed. fMRI allows us to reliably detect activity throughout the entire brain and to depict this
activity on clear three-dimensional images (see Module 3.4 ). Initially, fMRI
was used to examine relatively straightforward behaviours such as visual perception. However, it quickly became the “go to” tool for researchers interested in understanding the neural mechanisms for cognitive behaviours such as memory, emotion, and decision-making. This field, which combines elements of
cognitive psychology and biopsychology is known as cognitive neuroscience.
fMRIs allow us to reliably detect activity throughout the entire brain and to depict this activity in clear three-dimensional images. Living Art Enterprises/Photo Researchers, Inc./Science Source
As fMRI became accessible, researchers in other fields of psychology began to incorporate it into their studies. Psychologists studying social behaviours ranging from racism to relationships use fMRI in their experiments; this new field is
known as social neuroscience. Neuroimaging has also been used to study personality traits and consumer behaviour. In fact, it is difficult to find an area not touched by the development of neuroimaging technologies.
The Search for the Positive
Another rapidly growing area of psychology involves promoting human strengths and potentials. Rather than focusing on pathologies or negative events such as
rejection, the goal of positive psychology is to help people see the good in their lives by promoting self-acceptance and improving social relationships with others. The eventual goal of this field is to help people experience feelings of
happiness and fulfillment; in short, to help them flourish (Seligman & Csikszentmihalyi, 2000).
Positivity has been linked with improvements in some cognitive abilities
(Fredrickson, 2003) and to changes in neural pathways associated with controlling your attention (Tang et al., 2010). In fact, researchers are only beginning to understand the potential benefits of positive thinking. Elements of positive psychology can be found in a number areas of psychological study,
ranging from our motivation to achieve (Module 11.3 ) to techniques for coping with stress and psychological disorders (Modules 14.3 and 16.2 ).
Psychology in the Real World
Finally, it is important to remember that psychology research isn’t limited to the laboratory. Although many researchers are interested in the basic mechanisms of human behaviour, many others apply psychological science in different
settings. Applied psychology can take place in schools, in the workplace, in the military, or in a number of other settings. For example, researchers at Memorial University in Newfoundland are performing research that will lead to
improvements in how children are interviewed in the legal arena (Eastwood et al., 2016; Snook et al., 2014); researchers at the University of Alberta, University of Victoria, Queen’s University, and Simon Fraser University examine other areas of psychology in the law, ranging from psychopathy to eyewitness
testimony (Douglas et al., 2009; Lindsay et al., 2008). Psychologists across the country have come together to help develop anti-bullying policy and educational
initiatives (http://www.prevnet.ca/). Industrial/organizational psychologists at the University of Guelph, University of Waterloo, and St. Mary’s University, among others, apply psychological research to the workplace, helping to ensure
that the work environment is fair for all employees. Human factors psychologists help to ensure that our interactions with technologies ranging from computer programs to airplane cockpits are intuitive and efficient. And, psychologists are also involved in the promotion of environmentally sustainable behaviours, searching for factors that influence attitudes toward the environment and for
ways to transform our society into one that works with nature, rather than against it (Hirsh & Dolderman, 2007; Nisbet & Gick, 2008). In short, psychological science affects every aspect of our society, even if we don’t realize or appreciate it.
Psychologists work in a number of applied settings. For example, researchers from a number of provinces are involved in important anti-bullying research. These studies are used to influence policies of provincial agencies and local school boards. Steve Debenport/E+/Getty Images
In conclusion, the trends that emerged during the formative years of psychology laid the foundation for the modern perspectives and theories we see today. Psychology is now a clearly established discipline—there are established venues such as professional organizations and journals to disseminate the results of psychological research. Although modern technology, such as brain imaging and computing, would astound psychology’s founders, it is likely that they would find the results of modern research absolutely relevant to their own interests. It is also likely that they would be enthusiastic about the increasing levels of collaboration between the different areas of psychology, and about the current zeitgeist of treating human behaviour as a complex system with biological, psychological, and sociocultural components.
Module 1.2c Quiz:
Emerging Themes in Psychology
Know . . .
1. Cognitive neuroscience examines A. what computers can tell us about different cognitive functions. B. how functions like memory differ across cultures. C. how different brain areas are involved with different cognitive
abilities.
D. how the brains of different animals can help us understand evolutionary forces on behaviour.
Apply . . .
2. Which is NOT an example of applied psychology? A. Calculating how many words participants can remember from a
lengthy list
B. Examining whether the wording of questions influences the reports of people who witnessed a crime
C. Testing ways to promote recycling in the workplace D. Examining different techniques to improve relations between
police and the community
Module 1.2 Summary
behaviourism
clinical psychology
cognitive psychology
determinism
dualism
empiricism
functionalism
Gestalt psychology
humanistic psychology
materialism
nature and nurture relationships
personality psychology
psychoanalysis
psychophysics
social psychology
structuralism
Know . . . the key terminology of psychology’s history.1.2a
zeitgeist
The philosophical schools of determinism, empiricism, and materialism provided a background for a scientific study of human behaviour. The first psychologists were trained as physicists and physiologists. Fechner, for example, developed psychophysics, whereas Titchener looked for the elements of thought. Darwin’s theory of natural selection influenced psychologist William James’s idea of functionalism—the search for how behaviours may aid the survival and reproduction of the organism.
Apply Activity Apply your knowledge to distinguish among different specializations in psychology. You should be able to read a description of a psychologist on the left
of Table 1.1 and match her or his work to a specialization on the right.
Table 1.1 Areas of Specialization within Psychology
1. I am an academic psychologist who studies various methods for improving study habits. I hope to help
people increase memory performance and become
better students. I am a(n) .
2. My work focuses on how the presence of other people influences an individual’s acceptance of and willingness
to express various stereotypes. I am a(n) .
3. I have been studying how childrearing practices in Guatemala, Canada, and Cambodia all share some
common elements, as well as how they differ. I am
a(n) .
a. social psychologist
b. cross- cultural
psychologist
c. cognitive psychologist
d. humanistic psychologist
e. evolutionary psychologist
Understand . . . how various philosophical and scientific fields became major influences on psychology.
1.2b
Apply . . . your knowledge to distinguish among the different specializations in psychology.
1.2c
4. I am interested in behaviours that are genetically influenced to help animals adapt to their changing
environments. I am a(n) .
5. I help individuals identify problem areas of their lives and ways to correct them, and guide them to live up to
their full potential. I am a(n) .
Psychology is based on empiricism, the belief that all knowledge—including knowledge about human behaviour—is acquired through the senses. All sciences, including psychology, require a deterministic viewpoint. Determinism is the philosophical tenet that all events in the world, including human actions, have a physical cause. The deterministic view is also essential to the sciences. Applying determinism to human behaviour has been met with resistance by many because it appears to deny a place for free will.
Analyze . . . how the philosophical ideas of empiricism and determinism are applied to human behaviour.
1.2d
Chapter 2 Reading and Evaluating Scientific Research
2.1 Principles of Scientific Research Five Characteristics of Quality Scientific Research 31
Working the Scientific Literacy Model: Demand Characteristics and Participant Behaviour 35
Module 1.2a Quiz 39
Five Characteristics of Poor Research 39
Module 2.1b Quiz 40
Module 2.1 Summary 41
2.2 Scientific Research Designs Descriptive Research 43
Working the Scientific Literacy Model: Case Studies as a Form of Scientific Research 44
Module 2.2a Quiz 46
Correlational Research 47
Module 2.2b Quiz 49
Experimental Research 49
Module 2.2c Quiz 51
Module 2.2 Summary 51
2.3 Ethics in Psychological Research Promoting the Welfare of Research Participants 54
Working the Scientific Literacy Model: Animal Models of Disease 57
Module 3.2a Quiz 59
Ethical Collection, Storage, and Reporting of Data 59
Module 2.3b Quiz 60
Module 2.3 Summary 61
2.4 A Statistical Primer Descriptive Statistics 63
Module 4.2a Quiz 66
Hypothesis Testing: Evaluating the Outcome of a Study 66
Working the Scientific Literacy Model: Statistical Significance 68
Module 2.4b Quiz 69
Module 2.4 Summary 70
Module 2.1 Principles of Scientific Research
Miodrag Gajic/E+/Getty Images
Learning Objectives
Know . . . the key terminology related to the principles of scientific research. Understand . . . the five characteristics of quality scientific research. Understand . . . how biases might influence the outcome of a study. Apply . . . the concepts of reliability and validity to examples. Analyze . . . whether anecdotes, authority figures, and common sense
2.1a
2.1b 2.1c 2.1d 2.1e
Does listening to classical music make you smarter? In January 1998, Governor Zell Miller of Georgia placed a $105 000 line in his state budget
dedicated to purchasing classical music CDs for children (Sack, 1998). He even paid the conductor of the Atlanta Symphony to select optimal pieces for this CD. Apparently, Georgia’s well-meaning governor and state legislature believed that providing young children with classical music would make them smarter. There were many reasons to believe this assumption might be true, starting with the observation that most people we know who listen to classical music seem intelligent and sophisticated. At around the same time that Georgia took this step, consumers were being bombarded with advertisements about “the Mozart effect,” the scientific finding that listening to Mozart improves intelligence. Suddenly the classical sections at music stores were dusted off and moved to the front of the store, with signs drawing customers’ attention to the intelligence-boosting effects of the CDs. Parents were told that it was never too early to start their children on a Mozart program, even as fetuses residing in the womb. In fact, part of the Georgia budget, as well as the budget in some other U.S. states, was dedicated to handing out classical CDs along with hospital birth certificates. Eventually, the enthusiasm toward the Mozart effect died down after other scientists were unable to replicate the results. It turns out that the hype surrounding the Mozart effect was based on the results of one study
(Rauscher et al., 1993). In this study, the twelve adult participants who listened to Mozart performed better than other adults on a test of spatial ability. These (temporary) differences in spatial intelligence were then inflated by the popular press to mean intelligence in general (a big difference!). Based on a single study, companies created a multi-million dollar industry, and the state of Georgia spent an extra $105 000.
This example is not meant to demonize the media or to mock Governor Miller. Rather, it highlights the need for greater scientific literacy in our society. The researchers did not make any unethical claims, the media were trying to present an interesting science-based story to their
are reliably truthful sources of information.
audience, and Governor Miller wanted to improve the well-being of the children in his state. But, because of a lack of scientific literacy and critical thinking, these events have now become a cautionary tale.
Focus Questions
1. We hear claims from marketers and politicians every day, but how can we evaluate them?
2. Can we evaluate evidence even if we are not scientists?
This chapter might be the most important one in the book. It will give you the training to become a critical consumer of scientific claims that are made by the media, corporations, politicians, and even scientists. Every time you open a news website, you encounter scientific topics such as how certain foods are linked with cancer risks or psychological issues, or you read about wonder drugs that will improve your grades. Some of this research is fantastic, but some is not. The goal of this chapter is to help you separate the good from the questionable, and to show you that asking tough questions about how research was designed and conducted is never a bad thing. Doing so prevents you from being tricked and manipulated . . . and from spending $105 000 on Mozart CDs.
What makes science such a powerful technique for examining behaviour? Perhaps the single most important aspect of scientific research is that it strives
for objectivity. Objectivity assumes that certain facts about the world can be observed and tested independently from the individual who describes them (e.g., the scientist). Everyone—not just the experts—should be able to agree on these facts given the same tools, the same methods, and the same context. Achieving objectivity is not a simple task, however.
As soon as people observe an event, their interpretation of it becomes
subjective, meaning that their knowledge of the event is shaped by prior beliefs, expectations, experiences, and even their mood. A scientific, objective approach
to answering questions differs greatly from a subjective one. Most individuals tend to regard a scientific approach as one that is rigorous and demands proof. In this module, we will discuss the key elements of this scientific approach, and how it can help us understand human behaviour.
Five Characteristics of Quality Scientific Research
During the past few centuries, scientists have developed methods to help bring us to an objective understanding of the world. The drive for objectivity influences how scientific research is conducted in at least five ways. Quality scientific research meets the following criteria:
1. It is based on measurements that are objective, valid, and reliable. 2. It can be generalized. 3. It uses techniques that reduce bias. 4. It is made public. 5. It can be replicated.
As you will soon read, these five characteristics of good research overlap in many ways, and they will apply to any of the methods of conducting research that you will read about in this textbook.
Scientific Measurement: Objectivity
The foundation of scientific methodology is the use of objective measurements , the measure of an entity or behaviour that, within an allowed margin of error, is consistent across instruments and observers. In other words, the way that a quality or a behaviour is measured must be the same regardless of who is doing the measuring and the exact tool being used. For example, weight is measured in pounds or kilograms. One kilogram in St. John’s is the same as one kilogram in Victoria—researchers don’t get to choose how much
mass a kilogram is worth. Similarly, your weight will be the same regardless of whether you’re using the scale in your bathroom or the scale in the change room
at the gym. However, your weight will vary slightly from scale to scale—this is the margin of error mentioned in the definition. Scientists in a given field have to agree upon how much variability is allowable. Most people will be comfortable if their weight differs by one or two kilograms depending on the scale being used. But, if you weigh 70 kg on one scale and 95 kg on the other, then you know one of your measurement tools is inaccurate.
In this example, weight would be considered a variable , the object, concept, or event being measured. Variables are a key part of the research described in all of the chapters in this book ranging from perceptual processes, to learning and memory, to how we interact with each other, and so on. Each of these variables can be described and measured. For most of psychology’s history, measurements involved observations of behaviour in different situations or examinations of how participants responded on a questionnaire or to stimuli presented on a computer. However, as technology advanced, so did the ability to ask psychological questions in new and interesting ways. High-tech equipment, such as functional magnetic resonance imaging (fMRI), allows researchers to view the brain and see which areas are activated while you perform different tasks such as remembering words or viewing emotional pictures. Other physiological measures might involve gathering samples of blood or saliva, which can then be analyzed for enzymes, hormones, and other biological variables that relate to behaviour and mental functioning. With this greater number of measurement options, it’s now possible to examine the same variable (e.g., anxiety) using a number of different techniques. Doing so strengthens our ability to understand the different elements of behaviour.
Regardless of the specific experimental question being asked, any method used by a researcher to measure a variable needs to include carefully defined terms. This isn’t always as easy as it sounds. How would you define personality, shyness, or cognitive ability? This is the type of question a researcher would want to answer very carefully, not only for planning and conducting a study, but also when sharing the results of that research. In order to do so, researchers must decide upon a precise definition that other researchers can understand.
These operational definitions are statements that describe the procedures (or operations) and specific measures that are used to record observations (Figure 2.1 ). For example, depression could be operationally defined as “a score of 20 or higher on the Beck Depression Inventory” (Beck & Steer, 1977), with the measure being a common and widely accepted clinical questionnaire.
Figure 2.1 Operational Definitions A variable, such as the level of intoxication, can be operationally defined in multiple ways. This figure shows operational definitions based on physiology, behaviour, and self-report measures.
The concept of operational definitions would have been helpful when the Georgia legislators considered implementing a state-wide program based on the Mozart effect. They should have asked, “How do the researchers define the outcome of
their study? Do they mean listening to classical music makes you smarter, or just that it helps you remember better? Do they claim the effect is permanent, or does it occur only while listening to Mozart?” If these elected officials had examined the science behind the Mozart effect, they would have found that the results were based primarily on studies of adults (not infants) and led to a small effect on spatial reasoning abilities, not overall intelligence. In fact, subsequent studies by a different group of researchers found the same type and size of effect after participants listened to a recording of a Stephen King horror novel, a result that companies producing Mozart-effect CDs clearly did not share with
consumers. These conclusions make a very strong argument against investing the time, money, and effort in writing policy that relies so heavily on the Mozart
effect. They also provide an important lesson to anyone making policy decisions that involve human behaviour: thoroughly examine the existing research
literature before you make any decisions.
Scientific Measurement: Reliability, and Validity
Once researchers have defined their terms, they then turn their attention toward the tools they plan to use to measure their variable(s) of interest. The behavioural measurements that psychologists make must be valid and reliable. Validity refers to the degree to which an instrument or procedure actually measures what it claims to measure. This seems like a simple task, but creating valid measures of complex behaviours is quite challenging. To go back to the depression example, researchers cannot simply ask people a few questions and then randomly decide that one score qualifies as depressed while another does not. Instead, for the measure to be valid, a particular score would have to differentiate depressed and non-depressed people in a way that accurately maps onto how these people actually feel (i.e., a depressed person would score differently than a non-depressed person). The creation of valid measures is therefore quite time-consuming and requires a great deal of testing and revising before the final product is ready for use.
In addition to being valid, a measurement tool must also be reliable. A measure
demonstrates reliability when it provides consistent and stable answers across multiple observations and points in time. There are actually a number of different types of reliability that affect psychological research (see Figure 2.2 ). Test-retest reliability examines whether scores on a given measure of behaviour are consistent across test sessions. If your scores on a test of depression vary widely each time you take the test, then it is unlikely that your test is reliable.
Alternate-forms reliability is a bit more complicated. This form of reliability examines whether different forms of the same test produce the same results. Why would you need multiple forms of a test? In many situations, a person will be tested on multiple occasions. For instance, individuals with brain damage might have their memory tested soon after they arrive at the hospital and then at one or more points during their rehabilitation. If you give these individuals the
exact same test, it is possible that any improvement is simply due to practice. By having multiple versions of a test that produce the same results (e.g., two equally difficult lists of words as stimuli for memory tests), researchers and hospital workers can test individuals on multiple occasions and know that their measurement tools are equivalent.
Figure 2.2 Test-Retest and Alternate-Forms Reliability Test-retest reliability assumes that if the same test is taken at two or more different times, the scores will be similar. Alternate-forms reliability assumes that if a person completed different versions of the same test (e.g., Version A and Version B), her scores would be similar.
A third type of reliability takes place when observers have to score or rate a behaviour or response. For example, psychologists might be interested in the effects of nonverbal behaviour when people interact, so they might videotape participants solving a problem and then have trained raters count the number of touches or the amount of eye contact that occurred during the experiment. As another example, participants might write down lengthy, open-ended responses to an experimenter’s questions; these responses would then be rated on different variables by laboratory personnel. The catch is that more than one person must do the rating; otherwise it is impossible to determine if the responses were accurately measured or if the results were due to the single rater. Having more
than one rater allows you to have inter-rater reliability, meaning that the raters agree on the measurements that were taken. If you design an experiment with
clear operational definitions and criteria for the raters, then it is likely that you will have high inter-rater reliability.
Reliability and validity are essential components of scientific research. In addition, it is usually very important that your results are not limited to a small group of people in a single laboratory. Instead, it is ideal for these results to relate to other groups and situations—in other words, to be generalizable.
Generalizability of Results
Although personal testimony can be persuasive and (sometimes) interesting,
psychologists are primarily interested in understanding behaviour in general. This involves examining trends and patterns that will allow us to predict how
most people will respond to different stimuli and situations. Generalizability
refers to the degree to which one set of results can be applied to other situations, individuals, or events. For example, imagine that one person you know claimed that a memory-improvement course helped her raise her grades. How useful is the course? Based on this information, you might initially view the course favourably. However, upon further reflection, you’d realize that a number of other factors could have influenced your friend’s improvement, not the least of which is that she is suddenly paying more attention to her grades! At this point, you would wisely decide to wait until you’ve heard more about the course before investing your hard-earned money. But, if you found out that several hundred people in your city had taken the same course and had experienced similar benefits, then these results will appear more likely to predict what would happen if you or other people took the course. They are generalizable.
As you can see from this example, one way to increase the possibility that research results will generalize is to study a large group of participants. By examining and reporting an average effect for that group, psychologists can get
a much better sense of how individuals are likely to behave. But how large of a group is it possible to study? Ideally, it would be best to study an entire population , the group that researchers want to generalize about. In reality, the task of finding all population members, persuading them to participate, and measuring their behaviour is impossible in most cases. Instead, psychologists
typically study a sample , a select group of population members. Once the sample has been studied, then the results may be generalized to the population as a whole.
It is important to note that how a sample is selected will determine whether your results are generalizable. If your sample for the memory-improvement course was limited to middle-aged male doctors in Edmonton, it would be difficult to generalize those results to all Canadians. Instead, researchers try to use a random sample , a sampling technique in which every individual of a population has an equal chance of being included. If you wanted to study the population of students at your school, for example, the best way to obtain a true random sample would be to have a computer generate a list of names from the entire student body. Your random sample—a subset of this population—would then be identified, with each member of the population having an equal chance of being selected regardless of class standing, gender, major, living situation, and other factors. Of course, it isn’t always possible to use random sampling. This is particularly true if you are hoping that your results generalize to a large population or to all of humanity. In these cases, researchers often have to settle
for convenience samples , samples of individuals who are the most readily available—for example, Introductory Psychology students.
In a random sample, all members of a population (e.g., Winnipeggers) would be equally likely to be selected to be part of a study. This type of sampling is not always possible. Instead, many psychologists test their hypotheses using a
convenience sample, such as psychology students. Ariel Skelley/Blend Images/Getty Images
In addition to generalizing across individuals, psychological research should generalize across time and location. Research should ideally have high ecological validity , meaning that the results of a laboratory study can be applied to or repeated in the natural environment. Sometimes this connection doesn’t seem obvious, such as computer-based studies testing your ability to pay attention to different stimuli on a computer screen, but such seemingly artificial situations are assessing human abilities that are used in very common situations such as driving or finding a friend in a crowded classroom.
Although generalizability and ecological validity are important qualities of good
research, we need to be careful not to over-generalize. For example, results from a convenience sample of university students might not predict how a group of elderly people would do on the same task. Conversely, in the Mozart effect example that began this module, most of the studies involved adults, yet companies and politicians assumed—with very little evidence—that the results would generalize to children, including infants. Therefore, scientific literacy also
involves thinking critically about when it is appropriate to generalize results to other groups, times, and locations.
Sources of Bias in Psychological Research
Of course, generalizability is only important if the experiment itself was conducted without bias. While creating objective, reliable, and valid measures is important in quality research, various types of bias can be unintentionally
introduced by the researchers; this is known as a researcher bias. For instance, the experimenter may treat participants in different experimental conditions differently, thus making it impossible to know if any differences were due to the experimental manipulation being tested or were instead due to the experimenter’s behaviour. It is also possible for the participants, including
animals, to introduce their own bias; these effects are known as subject biases or participant biases. Sometimes this bias will involve a participant trying to figure
out what the experimenters are testing or trying to predict the responses that the researchers are hoping to find.
Bias can also be introduced by the act of observation itself. A wonderful example of this tendency was provided by workers at the Western Electric Company’s Hawthorne Works, a Chicago-area factory in the 1920s. Researchers went to the factory to study the relationship between productivity and working conditions. When the researchers introduced some minor change in working conditions, such as an adjustment to the lighting, the workers were more productive for a period of time. When they changed another variable in a different study—such as having fewer but longer breaks—productivity increased again. What was not
obvious to the researchers was that any change in factory conditions brought about increased productivity, presumably because the changes were always
followed by close attention from the factory supervisors (Adair, 1984; Parsons, 1974). The results were due to the participants noticing that they were being observed rather than to the variables being manipulated. In honour of these
observations, a behaviour change that occurs as a result of being observed is now known as the Hawthorne effect .
In most psychological research, the participants are aware that they are being
observed. This presents a different form of problem, however. Participants may respond in ways that increase the chances that they will be viewed favourably by the experimenter and/or other participants, a tendency known as social desirability (or socially desirable responding). This type of bias is particularly relevant when the study involves an interview in which the researcher has face- to-face contact with the volunteers. As a result, many researchers now collect data using computers; this allows the participants to respond with relative anonymity, thereby reducing the desire to appear likeable.
In these situations, the participants can look for feedback—intentional or unintentional—and then adapt their responses to be consistent with what they think is expected of them. The potential biasing effects of social desirability show us a challenge faced by many psychologists: the need to limit the effect that they have on the results of their own study so that the results are due to the variables being studied rather than to the participants responding to cues from the
researcher. As you will read in the next section, this challenge is not as simple as it appears.
The Hawthorne Effect, named after the Western Electric Company’s Hawthorne Works in Chicago, states that individuals sometimes change their behaviour when they think they are being observed. Hawthorne Works Museum of Morton College.
Working the Scientific Literacy Model Demand Characteristics and Participant Behaviour
Results of psychological studies should provide uncontaminated views of behaviour. In reality, however, people who participate in psychological studies typically enter the research environment
with a curiosity about the subject of the study. Researchers need to withhold as much detail as possible (while still being ethical) to get the best, least biased results possible.
What do we know about how bias affects research participants?
When studying human behaviour, a major concern is demand characteristics , inadvertent cues given off by the experimenter or the experimental context that provide information about how participants are expected to behave. Early psychologists often thought of the people being tested as “subjects.” This term, still commonly used, assumes that individuals taking part in an experiment will follow instructions (within reason) and will not put too much thought into why certain stimuli are being presented or certain experimental manipulations are occurring. This view changed in the 1950s and 1960s, when psychologists began applying the scientific method to more cognitive topics. Researchers quickly realized that people are
active participants in psychological experiments (Orne, 1962). These participants examine their environment and attempt to
understand why certain stimuli and procedures are being used. As part of this attempt to “figure out” the study, participants will look to the behaviour of other people in that setting, including the experimenters. Sometimes, the actions, tone of voice, body language, or facial expressions of the experimenter can bias participants’ responses. These demand characteristics can range from very subtle to obvious influences on the behaviour of
research participants (Orne, 1962).
How can science test the effects of demand characteristics on behaviour? Some classic examples of how demand characteristics can influence results come from the research of Rosenthal and colleagues. In one study, researchers told teachers in 18 different classrooms that a group of children had an “unusual” potential for
learning, when in reality they were just a random selection of
students (Rosenthal & Jacobson, 1966). After eight months of schooling, the children singled out as especially promising showed significant gains not just in grades, but in intelligence test scores, which are believed to be relatively stable. Why would this occur if the students were randomly selected? The best explanation is that the observers (i.e., teachers) assumed those students would do well, and were therefore more likely to pay attention to those students and to give them positive and encouraging feedback. These positive experiences with the teachers likely motivated these students to improve themselves. In other words, the students changed their behaviour patterns in order to match up with the expectations of the teachers. It is easy to see how similar experimenter effects could occur in psychological research studies.
Experimenter bias can even be found when people work with animals. When research assistants were told they were handling “bright” rats, it appeared that the animals learned significantly faster than when the assistants were told they were handling “dull” rats. Because it is unlikely that the rats were influenced by demand characteristics—they were not trying to give the researchers what they wanted—the most likely explanation for this difference is that researchers made subtle changes in how they treated the animals, and in how they observed and recorded
behaviour (Rosenthal & Fode, 1963).
How can we critically evaluate the issue of bias in research? This issue of bias in research is very difficult to overcome. Very few researchers intentionally manipulate their participants; however, as you have read, many times these influences are subtle and accidental. In most cases, experimenters (often graduate students and undergraduate research assistants) complete rigorous training and follow careful scripts when explaining experimental procedures to par ticipants. These
precautions help reduce experimenter effects. Additionally, many studies include interviews or questionnaires at the end of the study asking participants what they thought the experiment was about. This information can then be used by the experimenters to determine if the data from that participant are due to the experimental manipulation or to demand characteristics.
One way to evaluate whether participants’ expectations are influencing the results is to create an additional manipulation in which the researchers give different groups of participants different expectations of the results. If the groups then differ when performing the same task, then some form of demand characteristic, in this case from the participant, might be influencing performance. Of course, it is not always practical to include an additional group in a study, and, when doing clinical research, manipulating expectations might not be ethical. But when researchers begin performing research on new topics or with new research methods, testing for demand characteristics would be a wise decision.
Why is this relevant? Demand characteristics and other sources of bias all have the potential to compromise research studies. Given the time, energy, and monetary cost of conducting research, it is critical that results are as free from contamination as possible. The science of psychology involves the study of a number of very sensitive topics; the results are often used to help policymakers make better-informed decisions. Producing biased results will therefore have negative effects upon society as a whole. Demand effects are particularly problematic when studying clinical populations or when performing experiments with different types of clinical treatments. The results of these studies affect what we know about different patient populations and how we can help them recover from their different conditions. Biased results could therefore affect the health care of vulnerable members of our
society.
The fact that demand characteristics can alter results is of particular importance for researchers investigating new drug treatments for different conditions. Patients enter treatment programs (and experiments) with a number of expectations. It turns out these expectations can produce their own unique effects.
Techniques That Reduce Bias
Although biases can be a threat to the validity and reliability of psychological research, experimenters have established a number of techniques that can reduce the impact of subject and researcher biases. One of the best techniques for reducing subject bias is to provide anonymity and confidentiality to the
volunteers. Anonymity means that each individual’s responses are recorded without any name or other personal information that could link a particular
individual to specific results. Confidentiality means that the results will be seen only by the researcher. Ensuring anonymity and confidentiality are important steps toward gathering honest responses from research participants. Participants are much more likely to provide information about sensitive issues like their sexual history, drug use, or emotional state if they can do so confidentially and anonymously.
Psych@ The Hospital: The Placebo Effect The demand effect that we know the most about is the placebo effect , a measurable and experienced improvement in health or behaviour that cannot be attributable to a medication or treatment. This term comes from drug studies, in which it is standard procedure for a group, unbeknownst to them, to be given an inactive substance (the placebo) so that this group can be compared to a group given the active drug. What often happens is that people in the placebo group report feeling better because they have the expectation that the drug will have
an effect on their brain and body. This effect has been reported time and again—not just with drugs, but with other medical treatments as well. Why do people receiving a placebo claim to feel better? The initial explanation was that the patients’ expectations caused them to simply convince themselves they feel better (i.e., it is “all in their head”). Other research noted that many people who are given a placebo show
physiological evidence of relief from pain and nausea (Hrobjartsson & Gotzsche, 2010). Research conducted at the Rotman Research Institute in Toronto suggests that both of these explanations have merit. Helen
Mayberg and colleagues (2002) found that people responding to placebos showed increased activity in several regions of the frontal
lobes. This activity may relate to the participants creating a new “mental set” of their current state; in other words, creating the belief that their pain was going to decrease. Interestingly, these researchers also noted a decrease in activity in a number of other brain regions that might represent changes in the sensitivity of pain pathways. These results suggest that there are multiple ways for placebos to affect our responses to pain. Placebos are an important part of experimental research in psychology and related fields, so it is important to recognize their potential influence on how research participants respond.
In a related issue, participant anxiety about the experiment—which often leads to changes in how people respond to questions—can be reduced if researchers provide full information about how they will eventually use the data. Many people assume that psychologists are “analyzing them”; in fact, if you mention at your next family gathering that you’re taking a psychology course, it is almost certain
that someone will make a joke about this. If volunteers know that the data will not be used to diagnose psychiatric problems, affect their grades, or harm them in some other way, then their concerns about the study will be less likely to affect their performance.
Another source of bias in psychological research involves participants’ expectations of the effects of a treatment or manipulation. We saw this tendency in the discussion of the placebo effect earlier. The critical element of the placebo effect is that the participants believe the pill or liquid they are consuming is
actually a drug. If they knew that they were receiving a sugar pill instead of a pain medication, they would not experience any pain relief. Therefore, it is important that experiments involving drugs (recreational or therapeutic) utilize
what are known as blind procedures. In a single-blind study , the participants do not know the true purpose of the study, or else do not know which type of treatment they are receiving (for example, a placebo or a drug). In this case, the subjects are “blind” to the purpose of the study. Of course, a researcher can introduce bias as well. This bias is not going to be overt. It is unlikely that a researcher will laugh and call the placebo group “suckers” and then play Pink Floyd albums and Spongebob cartoons for the people in the drug condition. But the researcher might unintentionally treat individuals in the two conditions differently, thus biasing the results. In order to eliminate this possibility,
researchers often use a technique known as a double-blind study , a study in which neither the participant nor the experimenter knows the exact treatment for any individual. To carry out a double-blind procedure, the researcher must arrange for an assistant to conduct the observations or, at the very least, the researcher must not be told which type of treatment a person is receiving until after the study is completed.
Double-blind procedures are also sometimes used when researchers are testing groups that differ on variables such as personality characteristics or subtle demographic factors such as sexual orientation. If the experi menter knows that a participant has scored high on a test of psychopathy, she might treat him differently than she treated a person who scored low on the same test. Keeping the experimenter (and participants) blind to these results allows the research to remain objective. Therefore, researchers should use these techniques whenever possible.
Sharing The Results
Once a group of researchers has designed and conducted an objective experiment that is free of bias, it is important to communicate their findings to other scientists. Psychology’s primary mode of communication is through academic journals. Academic journals resemble magazines in that they are usually soft-bound periodicals with a number of articles by different authors
(online formats are typically available as well). Unlike magazines, however, journal articles represent primary research or reviews of multiple studies on a single topic. When scientists complete a piece of research, they may write a detailed description of the theory, hypotheses, measures, and results and submit the article for possible publication. You will not find journals or research books in your average mall bookstore because they are too technical and specialized for the general market (and are not exactly page-turners), but you will find thousands of them in your university library.
However, only a fraction of the journal articles that are written eventually get published. Rather, before research findings can be published, they must go
through peer review , a process in which papers submitted for publication in scholarly journals are read and critiqued by experts in the specific field of study. In the field of psychology, peer review involves two main tasks. First, an editor receives the manuscript from the researcher and determines whether it is appropriate subject matter for the journal (for example, an article on 17th-century
Italian sculpture would not be appropriate for publication in the Journal of Cognitive Neuroscience, which is focused on biological explanations for memory, thinking, language, and decision making). Second, the editor sends copies of the manuscript to a select group of peer reviewers—“peer” in this case refers to another professional working within the same field of study. These reviewers critique the methods and results of the research and make recommendations to the editor regarding the merits of the research. In this process, the editors and reviewers serve as gatekeepers for the discipline, which helps increase the likelihood that the best research is made public.
Replication
Once research findings have been published, it is then possible for other researchers to build upon the knowledge that you have created; it is also possible for researchers to double check whether or not your results simply occurred by chance (which does happen). Science is an ongoing and self- correcting process. The finest, most interesting published research study can
quickly become obsolete if it cannot be replicated. Replication is the process of repeating a study and finding a similar outcome each time. As long as an
experiment uses sufficiently objective measurements and techniques, and if the
original hypothesis was correct, then similar results should be achieved by later researchers who perform the same types of studies.
Results are not always replicated in subsequent investigations, however. Psychology, like many other scientific fields, is experiencing what the media call
a “replication crisis.” In 2015, the influential journal Science published a paper describing the efforts of a group of researchers—known as the Open Science Collaboration (OSC)—to replicate 100 studies that had been published in three
well-known journals (OSC, 2015). Although one would hope that the vast majority of these studies would replicate, the results showed the opposite. Depending upon the statistical cut-offs used, only 36 to 47% of the studies were successfully replicated. This result was quite upsetting for most psychologists, as it implied that our field has some serious methodological problems. However, before assuming that psychology should be tossed aside, it is worth thinking about this issue in more detail. Psychology, like all sciences, has a publication bias in which successful and novel results are published and studies that showed no effects are not. Indeed, this bias is why replication is so important—it helps us determine if these published studies are simply statistical flukes. However, if a single replication attempt is unsuccessful, which result should we believe—the original published experiment or the failed attempt to replicate it? This dilemma
was not only pointed out by critics of the original OSC paper (Gilbert et al., 2016), but was noted by some of the OSC researchers themselves. The solution appears to involve performing the same study a number of times to see if it generally produces similar results. Such a strategy was used by the Many Labs Project (MLP). (It is unclear why these replication teams give themselves catchy “squad names.”) These researchers performed the same studies over 30 times
and found that 10 of the 13 studies they critiqued were replicable (Klein et al., 2014). Regardless of the specific number of studies that can be replicated, however, these efforts send an important message to both researchers and students: replication is important and makes science better.
Incidentally, researchers have had a difficult time replicating the Mozart effect
(Steele et al., 1997), the example describing at the beginning of this module. These results likely had Georgia Governor Zell Miller singing the blues.
Module 2.1a Quiz:
Five Characteristics of Quality Scientific Research
Know . . . 1. The degree to which an instrument measures what it is intended to
measure is known as . A. validity B. generalizability C. verifiability D. reliability
2. When psychologists question how well the results of a study apply to other samples or perhaps other situations, they are inquiring about the
of the study. A. validity B. generalizability C. verifiability D. reliability
Understand . . . 3. In a single-blind study, the participants do not know the purpose of the
study or the condition to which they are assigned. What is the difference in a double-blind study?
A. The researcher tells the participants the purpose and their assigned conditions in the study.
B. The participants also do not know when the actual study begins or ends.
C. The researcher also does not know which condition the participants are in.
D. The participants know the condition to which they have been assigned, but the researcher does not.
Apply . . .
4. Dr. Rose gives a standardized personality test to a group of psychology majors in January and again in March. Each individual’s score remains nearly the same over the two-month period. From this, Dr. Rose can infer
that the test is . A. reliable B. generalizable C. objective D. verified
Five Characteristics of Poor Research
In the preceding section, you read about for the characteristics of quality research. It is generally safe to assume that the opposite characteristics detract from the quality of research. Good research uses valid, objective measures; poor research uses measures that are less valid, less reliable, and, therefore, less likely to be replicable. However, other issues must also be scrutinized if you hear someone make a scientific-sounding claim. Most claims are accompanied by what might sound like evidence, but evidence can come in many forms. How can we differentiate between weak and strong evidence? Poor evidence comes most often in one of five varieties: untestable hypotheses, anecdotes, a biased selection of available data, appeals to authority, and appeals to (so-called) common sense.
Perhaps the most important characteristic of science is that its hypotheses are
testable. For a hypothesis to be testable, it must be falsifiable , meaning that the hypothesis is precise enough that it could be proven false. If a hypothesis is not falsifiable, that means that there is no pattern of data that could possibly prove that this view is wrong; instead, there is always a way to reinterpret the results to make the hypothesis match the data. If you cannot disconfirm a hypothesis, then there is no point in testing it. There are very few examples of unfalsifiable hypotheses in modern psychology. However, early personality work by Freud did suffer from this problem (although, to be fair, he wasn’t trying to create a testable theory). Briefly, Freud believed that our personality consisted of
three components: the id (which was focused on pleasure), the superego (which was based on following rules), and the ego (which attempted to balance the two opposing forces). Although this theory provided wonderful metaphors for behaviour, it is impossible to test. If a person does not behave in the predicted fashion, the analyst can simply say that the other personality component (e.g., the id) was more involved at that moment. There would be no way to prove him wrong. Luckily, researchers have built upon Freud’s pioneering work and have created much more scientific (and falsifiable) theories of personality.
A second characteristic of poor research is the use of anecdotal evidence , an individual’s story or testimony about an observation or event that is used to make a claim as evidence. For example, a personal testimonial on a product’s webpage might claim that a man used subliminal weight-loss recordings to lose 50 pounds in six months. But there is no way of knowing whether the recordings were responsible for the person’s weight loss; the outcome could have been due to any number of things, such as a separate physical problem or changes in food intake and lifestyle that had nothing to do with the subliminal messages. In fact, you do not even know if the anecdote itself is true: The “before” and “after” photos could easily be doctored. Therefore, we must be wary of such anecdotal claims. If they are not backed up by a peer-reviewed scientific study, then we should view the claims with caution.
However, we still need to be careful even if a scientific claim is backed up by published data. It is possible that some individuals—particularly politicians and corporations—might present only the data that support their views. A beautiful
example of this data selection bias is shown in the debate over whether human behaviour is a major cause of climate change. A climate-change denier could point out that 24 peer-reviewed scientific studies cast doubt on whether human behaviour is a cause of global warming. Twenty-four sounds like a large body of research. However, James Powell, a member of the U.S. National Science Board, carefully examined all of the climate-change data from 1991–2012 and
found 13 926 papers supporting this view (see Figure 2.3 ). Therefore, a very selective slice of the data would present one (biased) result, but a thorough and scientific representation of the data would present an entirely different view of the same issue.
Figure 2.3 Data Selection Bias People with a particular political or economic agenda can still make claims that appear scientific if they perform a biased selection of the available data. Groups opposed to the idea that human activity is playing a role in global warming often point to published research supporting their view. However, when one examines
all of the data on global warming, it appears that negative findings make up less than 1% of the results, suggesting that these individuals are full of hot air. Source: 1991-2012 Pie Chart, Retrieved from http://www.jamespowell.org. Reprinted with permission of James Powell.
The fourth kind of questionable evidence is the appeal to authority —the belief in an “expert’s” claim even when no supporting data or scientific evidence is present. Expertise is not actually evidence; “expert” describes the person making the claim, not the claim itself. It is entirely possible that the expert is mistaken, dishonest, or misquoted. True experts are good at developing evidence, so if a claim cites someone’s expertise as evidence, then you should see whether the expert offers the corresponding data to support the claim. It is not unusual for people to find that an expert’s claim actually has no evidence backing it, but rather that it is simply an opinion. It is also possible that that the experts have a hidden agenda or a conflict of interest, such as when scientists funded by the oil industry produce research that says human behaviour has no effect on the climate.
Finally, the evidence may consist of an appeal to common sense , a claim that appears to be sound, but lacks supporting scientific evidence. For example, many people throughout history assumed the world was the stationary centre of the universe. The idea that the Earth could orbit the sun at blinding speeds was deemed nonsense—the force generated would seemingly cause all the people and objects to be flung into space!
In addition to common sense, beliefs can originate from other potentially
unreliable sources. For example, appeals to tradition (“We have always done it this way!”) as well as their opposite, appeals to novelty (“It is the latest thing!”), can lead people to believe the wrong things. Claims based on common sense, tradition, or novelty may be worthy of consideration, but whether something is true cannot be evaluated by these standards alone. Instead, what we need is careful and objective testing. What we need is science.
Module 2.1b Quiz: Five Characteristics of Poor Research
Know . . .
1. Claiming that something is true because “it should be obvious” is really just .
A. anecdotal evidence B. an appeal to common sense C. an appeal to authority D. generalizability
Understand . . .
2. Appeals to authority do not qualify as good evidence because A. they always lack common sense. B. authority figures are quite likely to distort the truth. C. authority does not mean that there is sound, scientific evidence.
D. authority is typically based on anecdotal evidence.
Apply . . .
3. Ann is convinced that corporal punishment (e.g., spanking) is a good idea because she knows a child whose behaviour improved because of it. Whether or not you agree with her, Ann is using a flawed argument. Which type of evidence is she using?
A. Anecdotal B. Objective C. Generalizable D. Authority-based
Module 2.1 Summary
anecdotal evidence
appeal to authority
appeal to common sense
convenience samples
demand characteristics
double-blind study
ecological validity
falsifiable
generalizability
Hawthorne effect
objective measurements
Know . . . the key terminology related to the principles of scientific research.
2.1a
operational definitions
peer review
placebo effect
population random sample
reliability
replication
sample
single-blind study
social desirability
validity
variable
These characteristics include that (1) measurements are objective, valid, and reliable; (2) the research can be generalized; (3) it uses techniques that reduce bias; (4) the findings are made public; and (5) the results can be replicated. For example, objective, valid, and reliable measurements make it possible for other scientists to test whether they could come up with the same results if they followed the same procedures. Psychologists typically study samples of individuals; their goal is usually to describe principles that generalize to a broader population. Single- and double-blind procedures are standard ways of reducing bias. Finally, the process of publishing results is what allows scientists to share information, evaluate hypotheses that have been confirmed or refuted, and, if needed, replicate other researchers’ work.
Demand characteristics affect how participants respond in research studies— understandably, they often attempt to portray themselves in a positive light, even
Understand . . . the five characteristics of quality scientific research.2.1b
Understand . . . how biases might influence the outcome of a study.2.1c
if that means not answering questions or behaving in a fully truthful manner. Researchers can also influence the outcomes of their own studies, even unintentionally.
Try this activity to see how well you can apply these concepts.
Apply Activity
Read the following descriptions and determine whether each scenario involves an issue with reliability or validity.
1. Dr. Williams is performing very standard physio logical recording techniques on human participants. Each morning he checks whether the instruments are calibrated and ready for use. One day he discovers that although the instruments are still measuring physiological activity, their
recordings are not as sensitive as on previous testing days. Would this affect the reliability or validity of his research? Explain.
2. Dr. Nielson uses a behavioural checklist to measure happiness in the children he studies at an elementary school. Every time he and his associates observe the children, they reach near-perfect agreement on what they observed. Another group of psychologists observes the same children in an attempt to identify which children are energetic and which seem tired and lethargic. It turns out that the same children whom Dr. Nielson identifies as happy, using his checklist, are also the children
whom the second group of psychologists identify as energetic. It appears there may be a problem with Dr. Nielson’s measure of happiness. Do you think it is a problem of reliability or validity? Explain.
To evaluate evidence, you should ask several questions. First, is someone supplying anecdotal evidence? As convincing as a personal testimony may be,
Apply . . . the concepts of reliability and validity to examples.2.1d
Analyze . . . whether anecdotes, authority figures, and common sense are reliably truthful sources of information.
2.1e
anecdotal evidence is not sufficient for backing any claim that can be scientifically tested. Second, is support for the claim based on the words or endorsement of an authority figure? Endorsement by an authority figure is not necessarily a bad thing, as someone who is an authority at something should be able to back up the claim. But the authority of the individual alone is not satisfactory, especially if data gathered through good scientific methods do not support the claim. Finally, common sense also has its place in daily life, but by itself is insufficient as a final explanation for anything. Explanations based on good scientific research should override those based on common sense.
Module 2.2 Scientific Research Designs
Andersen Ross/Blend Images/Getty Images
Learning Objectives
Know . . . the key terminology related to research designs. Understand . . . what it means when variables are positively or negatively correlated. Understand . . . how experiments help demonstrate cause-and-effect relationships.
2.2a 2.2b
2.2c
Can your attitude affect your health? This is the old question of “mind over matter,” and psychologist Rod Martin from Western University in London, ON, thinks the answer is definitely yes. He says that if you can laugh in the face of stress, your psychological and physical health will benefit. Martin has found several interesting ways to build evidence for
this argument (Martin, 2002, 2007). For example, he developed a self- report instrument that measures sense of humour. People who score high on this measure—those who enjoy a good laugh on a regular basis— appear to be healthier in a number of ways. As interesting as this evidence is, it simply illustrates that humour and health are related—there is no guarantee that one causes the other. To make such a claim, researchers would have to use the experimental method, one of the many research designs discussed in this module.
Focus Questions
1. What are some of the ways researchers make observations? 2. Do some research techniques provide stronger evidence than
others?
Psychologists always begin their research with a research question, such as “What is the most effective way to study?”, “What causes us to feel hungry?”, or “How does attitude affect health?” In most cases, they also make a prediction about the outcome they expect—the hypothesis. Psychologists then create a research design , a set of methods that allows a hypothesis to be tested. Research designs influence how investigators (1) organize the stimuli used to test the hypothesis, (2) make observations, and (3) evaluate the results.
Apply . . . the terms and concepts of experimental methods to research examples. Analyze . . . the pros and cons of descriptive, correlational, and experimental research designs
2.2d
2.2e
Because several types of designs are available, psychologists must choose the one that best addresses the research question and that is most suitable to the subject of their research. Before we examine different research designs, we should quickly review the characteristics that all of them have in common.
Variables. A variable is a property of an object, organism, event, or something else that can take on different values. How frequently you laugh is a variable that could be measured and analyzed.
Operational definitions. Operational definitions are the details that define the variables for the purposes of a specific study. For sense of humour, this definition might be “the score on the Coping Humour Scale.”
Data. When scientists collect observations about the variables of interest, the information they record is called data. For example, data might consist of the collection of scores on the Coping Humour Scale from each individual in the sample.
These characteristics of research designs are important regardless of the design that is used. However, a number of other factors will guide the researchers as they select the appropriate research design for their topic of interest.
Descriptive Research
The beginning of any new line of research must involve descriptive data. Descriptive research answers the question of “what” a phenomenon is; it describes its characteristics. Once these observations have been performed and the data examined, they can be used to inform more sophisticated future studies that ask “why” and “how” that phenomenon occurs.
These descriptions can be performed in different ways. Qualitative research
involves examining an issue or behaviour without performing numerical measurements of the variables. In psychology, qualitative research often takes the form of interviews in which participants describe their thoughts and feelings
about particular events or experiences (Madill & Gough, 2008). For example,
researchers at St. Francis Xavier University in Nova Scotia performed a qualitative study of how males and females experienced “friends with benefits”
relationships (Weaver et al., 2011). As you likely know, “friends with benefits” refers to sexual activity that occurs between partners who do not view the relationship as being romantic. In this study, the researchers performed a semi- structured interview with 16 female and 10 male students. Although the interview contained six primary questions that would be asked over the course of the meeting, the interviews varied widely from person to person, as each individual had a different experience with their friends-with-benefits relationship. In this case, the fact that the researchers weren’t restricted to numerical data helped them answer their research question.
Quantitative research , on the other hand, involves examining an issue or behaviour by using numerical measurements and/or statistics. The majority of psychological studies are quantitative in nature. These designs can involve complex manipulations (discussed later in this module); but, it is also possible to perform more descriptive studies using numbers. For instance, if you wanted to examine friends with benefits quantitatively, you could conduct an interview or survey in which participants provided specific responses to questions (e.g., “On a scale of 1 (sad) to 7 (happy), how did you feel when your friends-with-benefits relationship ended?”).
Here are a few other examples of descriptive research questions:
How many words can the average 2-year-old speak? How many hours per week does the typical university student spend on homework?
What proportion of the population will experience depression or an anxiety disorder at some point in their lives?
As you can see, research questions can address the appearance of a behaviour, its duration or frequency, its prevalence in a population, and so on. To answer these questions, researchers usually gather data using one or more of the
following designs: case studies, naturalistic observation, and surveys and questionnaires.
Case Studies
A case study is an in-depth report about the details of a specific case. Rather than developing a hypothesis and then objectively testing it on a number of different individuals, scientists performing a case study describe an individual’s history and behaviour in great detail. Of course, case studies are not performed on just anyone. They are generally reserved for individuals who have a very uncommon characteristic or have lived through a very unusual experience.
Perhaps the most famous case study in psychology (and neurology) is that of Phineas Gage (1823–1860). Gage was a foreman working for the Rutland and Burlington Railroad Company in the northeastern U.S. state of Vermont. On September 13, 1848, 25-year-old Gage was helping his crew blast through a rocky outcrop near the town of Cavendish and was involved in an accident that caused an iron rod to be propelled upwards underneath Gage’s eye and through
his head. According to the original medical report of the incident (Harlow, 1848; available online for interested readers), the iron rod was found 25 m away, suggesting that it was travelling very quickly as it tore through Gage’s brain.
Amazingly, Gage survived the accident, although his physical recovery took most
of a year (Bigelow, 1850; Harlow, 1849). However, it quickly became apparent that Gage’s injuries were not limited to physical damage; his mental state had also been affected. Reports indicate that while he had been a reputable citizen prior to the accident, afterward he became much more impulsive, inconsiderate,
indecisive, and impatient. Harlow (1868) reported that Gage’s friends claimed that the changes were so pronounced that he “was no longer Gage.” The doctors treating Gage rightfully concluded that these sudden changes were due to the brain damage that he had suffered. Examination at the time of the accident— which involved Dr. Harlow sticking his finger into the hole in Gage’s head— suggested that this damage was located in the frontal lobes of the brain, a region now known to be involved in a number of complex behaviours including decision
making and emotional regulation (see Modules 8.2 and 11.4 ). Because Gage’s case was documented in a series of detailed case-study reports, it was possible for future doctors and researchers to use this information to gain a
better understanding of the role of the frontal lobes and the problems that emerge when this brain area is damaged.
Phineas Gage proudly holding the tamping iron that nearly killed him, and that made him one of the most famous names in the history of psychology and neuroscience. The information learned from case studies of Gage led to hundreds of subsequent scientific studies that have helped researchers learn a great deal about the frontal lobes of the brain. Interestingly, over the course of a few years, Gage slowly recovered enough of his self-control to hold down different jobs, including one as a long-distance stagecoach driver in South
America (Macmillan, 2008); however, he never did recover all of his self-control. Had doctors paid more attention to this partial recovery, it would have been one of the first reported cases of the brain’s ability to compensate and repair itself after injury. Warren Anatomical Museum in the Francis A. Countway Library of Medicine. Gift of Jack and Beverly Wilgus.
The case of Phineas Gage is obviously quite striking. However, although case
studies tell us a lot about an individual’s condition, is it really science? Different researchers have different opinions about the merit of such reports, with some viewing them as important scientific contributions and others viewing them as simply interesting stories.
Working the Scientific Literacy Model Case Studies as a Form of Scientific Research
Case studies allow the clinician or researcher to present more details about an individual than would be possible in a research report involving a number of participants; however, this detail comes at a price. Is a thorough description of a single individual still a form of science or is it simply an example of anecdotal evidence?
What do we know about using case studies as a form of scientific research? Case studies have been a form of psychological research for over a century. Freud used case studies of unique patients when he initially described many of his theories of personality and development. Case studies have also been critical for our understanding of the brain. Phineas Gage was just one of many unique neurological patients who have taught us how different areas of the brain influence particular behaviours. In each situation, the researchers described their patient in great detail so the case study could improve the treatment of similar patients in the future.
Case studies can also be useful in describing symptoms of psychological disorders and providing detailed descriptions about specific successes or failures in their treatment. One recently
published example of a case study did both (Elkins & Moore, 2011). The authors of this study described the experience of a
certain type of anxiety disorder and the steps used in therapy to treat the anxiety over a 16-week period. They were able to document how and when changes occurred and the effects of the treatment on other aspects of the individual’s life. This level of detail would not be available if the authors had not focused on a single case. However, as case studies only describe a single individual, there is no guarantee that the findings can be generalized to other people and situations.
How can science test the usefulness of case studies? Although it is tempting to view case studies as simply being descriptions of an individual, they can also serve another important scientific function: They can be used to test an existing hypothesis. For example, until a couple of years ago, researchers thought that the amygdala—a fear centre in the brain—was essential for emotional information to grab our attention (e.g., the way your attention is almost always drawn to a spider walking across your ceiling). It made sense that a fear centre would be a necessary part of a fear response. Brain-imaging studies showed that this structure was active when these types of images were displayed to healthy participants. But, what would happen if someone with no amygdala on either side of her brain was put in this situation? A case study with one such patient (there are fewer than 300 worldwide) found that her attention was still
grabbed by emotional stimuli (Tsuchiya et al., 2009). This told researchers that their models of how emotion and attention work together were too simplistic, and forced them to look at other brain structures that could be influencing these processes. In other words, the case study was used not to generate hypotheses, but to actually test an existing scientific theory.
How can we critically evaluate the role of case studies in research? The above section demonstrates that case studies can help guide our understanding of existing scientific theories. Case studies can
also be used to help scientists form hypotheses for future research studies. Take Phineas Gage, for example. Although there are very few, if any, other reports of individuals experiencing a tamping rod shooting through their frontal lobes, patients who suffered damage to the frontal lobes after car accidents and strokes have noted impairments similar to those suffered by Gage. Specifically, these individuals became more impulsive and risk-prone than they had been before their accident
(Bechara et al., 1994; Damasio, 1994). Researchers have also created lesions similar to Phineas Gage’s in animal subjects
(e.g., laboratory rats) and observed similar tendencies (Quirk & Beer, 2006).
Researchers can also use computer simulations to model the effects of this form of brain damage. In one study—cheekily entitled “Spiking Phineas Gage”—Brandon Wagar and Paul
Thagard (2004) of the University of Waterloo created a computerized neural network that used both cognitive and emotional information to produce simple decisions. After the network “learned” the task, the researchers altered its parameters so that the frontal lobe node of the network did not function properly. As predicted, this network’s responses quickly became more dependent upon emotional impulses, just like patients with frontal-lobe damage such as Phineas Gage.
Why is this relevant? These studies demonstrate that case studies are not simply anecdotes that scientists tell each other when they sit around the campfire. The case study of a single patient who somehow survived a terrifying brain injury has stimulated hundreds of scientific research papers leading to improvements in our understanding of how the brain works. Fittingly, such information will be essential in the treatment of any modern-day Phineas Gages. As you continue reading this textbook, you’ll be introduced to a number of unique individuals whose stories have
informed and guided psychological science for over a century. Without them, our understanding of topics ranging from vision to memory to language to emotions would not be as sophisticated as it has become. These topics would also lack the story-like narratives that make psychology so compelling.
Of course, case studies are often limited to individuals with unique conditions or experiences. They cannot be used to answer all types of research questions. For instance, there are times when a researcher might be interested in how groups of people or animals behave in environments outside of the controlled laboratory setting or interview room. In these situations, an entirely different form of descriptive research is necessary to examine psychological behaviours.
Naturalistic Observation
An alternative form of descriptive research is to observe people (or animals) in
their natural settings. When psychologists engage in such naturalistic observations , they unobtrusively observe and record behaviour as it occurs in the subject’s natural environment. The key word here is “unobtrusively”; in other words, the individuals being observed shouldn’t know that they are being observed. Otherwise, the mere act of observation could change the participants’ behaviours (imagine how your conversations with friends would change if you knew a psychologist was listening and taking notes). Most students have seen television programs about scientists in search of chimpanzees in a rain forest or driving a Range Rover in pursuit of a herd of elephants. This certainly is a form of observation, but there is more to it than just watching animals in the wild. When a scientist conducts naturalistic observation research, she is making systematic observations of specific variables according to operational definitions. By having a very precise definition of what a variable is and how it will be measured, researchers using naturalistic observations can ensure that their results are objective and that different people observing the same environment would score the behaviours in the same way (e.g., two observers would both call the same movement by a chimpanzee a grooming behaviour).
Although it may appear that naturalistic observation is only useful for animal studies or nature programs on TV, there have been a number of interesting human-focused naturalistic observation studies conducted as well. For example, a study conducted by psychologists at Carleton University in Ottawa measured
the behaviour of spectators at youth hockey games (Bowker et al., 2009). These researchers were specifically interested in the types of comments made by spectators—the intensity of the remarks, who made them (male vs. female), and who they were directed toward (players, other spectators, or everyone’s favourite target, the referees), among other variables. They also examined whether the observed trends changed depending upon whether the game was in a highly competitive or a more recreational league. The researchers found that females made more comments than males; these comments were largely positive and directed toward the players. Males tended to make more negative comments as well as directions on how to improve play (e.g., “Skate faster!”). Both female and male spectators made more negative comments when watching competitive, as opposed to recreational, leagues; these comments were largely directed toward the referees. Based on these observations, which involved five observers attending 69 hockey games, the researchers concluded that the behaviour of spectators is not as negative and unsettling as is often reported in the media
(Bowker et al., 2009).
Thus, naturalistic observations can occur anywhere that behaviours occur, be it
in “nature,” in a hockey rink, or even in a bar (Graham & Wells, 2004). The key point is that the researchers must pay attention to specific variables and use operational definitions. However, naturalistic observations may not always provide researchers with the specific types of information they are after. In these cases, researchers may need to adopt a different research strategy in order to describe a given behaviour.
Surveys and Questionnaires
Another common method of descriptive research used by psychologists is self- reporting , a method in which responses are provided directly by the people who are being studied, typically through face-to-face interviews, phone surveys,
paper and pencil tests, and web-based questionnaires. These methods allow researchers to assess attitudes, opinions, beliefs, and abilities. Despite the range in topics and techniques, their common element is that the individuals speak for themselves. Surveys and questionnaires are still a method of observation, but the observations are provided by the people who are being studied rather than by the psychologist.
Although this method initially sounds simple, the creation of objective survey and questionnaire items is extremely challenging. Care must be taken not to create biased questions that could affect the results one way or another. If you’re interested in studying emotional sensitivity, you can’t ask, “Given that men are drooling pigs, how likely are they to notice someone is unhappy?” Similarly, if you’re studying a subject that some individuals might not want to openly discuss, it is important to develop questions that touch on the issue without being too off- putting. For example, asking people, “How depressed are you?” and giving them a 7-point scale might not work, as some respondents might not want to state that they are depressed. But, questionnaires can tap into the symptoms of depression by asking questions about energy levels, problems with sleeping, problems concentrating, and changes in one’s mood. The researchers could then use the responses for these questions to determine if a respondent was depressed.
This leads to an important question: How do researchers figure out if their questions are valid? For clinical questionnaires, the researchers can compare results to a participant’s clinical diagnosis. For questionnaires examining other phenomena, researchers perform a large amount of pretesting in order to
calculate norms, or average patterns of data. Almost all of the questionnaires that you will encounter as a psychology student will have undergone prior testing to establish norms and to confirm that the research tool is both valid and reliable. This testing will involve hundreds or even thousands of participants; their efforts help ensure that self-report measures such as questionnaires are a useful tool in psychology’s quest to understand different behaviours.
Module 2.2a Quiz:
Descriptive Research
Know . . . 1. When psychologists observe behaviour and record data in the
environment where it normally occurs, they are using . A. case studies B. naturalistic observation C. the supervisory method D. artificial observation
2. Any property of an organism, event, or something else that can take on different values is called .
A. an operational definition B. data C. a variable D. a case study
Apply . . . 3. A psychologist is completing a naturalistic observation study of children’s
aggressive behaviour on a playground. She says that aggression is “any verbal or physical act that appears to be intended to hurt or control another child.” She then goes on to list specific examples. It appears that the psychologist is attempting to establish a(n)
A. good relationship with the children. B. variable. C. observational definition. D. operational definition.
Correlational Research
Psychologists performing descriptive research almost always record information about more than one variable when they are collecting data. In these situations, the researchers may look for an association among the variables. They will ask
whether the variables tend to occur together in some pattern, or if they tend to
occur at opposite times. Correlational research involves measuring the degree of association between two or more variables. For example, consider these two questions:
What is the average education level of Canadians over the age of 30? What is the average income of Canadians over the age of 30?
These two questions ask for different types of information, but their answers may be related. Is it likely that people with higher education levels also tend to have higher income levels? By asking two or more questions—perhaps through a survey—researchers can start to understand the associations among variables.
Correlations can be visualized when presented in a graph called a scatterplot, as shown in Figure 2.4 . In scatterplot (a), you can see the data for education and income. Each dot represents one participant’s data; when you enter dots for all of the participants, you often see a pattern emerge. In this case, the dots show a pattern that slopes upward and to the right, indicating that people with higher education levels tend to have a higher average income. That correlation is not surprising, but it illustrates one of the two main characteristics that describe correlations:
Direction: The pattern of the data points on the scatterplot will vary based on the relationship between the variables. If correlations are positive (see Figure 2.4 a), it means that the two variables change values in the same direction. So, if the value of one variable increases, the value of the other variable also tends to increase, and if the value of one variable decreases, the value of the other variable decreases. For example, education levels and average income both tend to rise and fall together, with educated people
tending to be wealthier. In contrast, if correlations are negative (see Figure 2.4 b), it means that as the value of one variable increases, the value of the other variable tends to decrease. For instance, if you get a lot of sleep, you are less likely to be irritable; but, if you don’t get much sleep, then you will be more likely to be irritable.
Magnitude (or strength): This refers to how closely the changes in one
variable are linked to changes in another variable (e.g., if variable A goes up one unit, will variable B also go up one unit?). This magnitude is described in
terms of a mathematical measure called the correlation coefficient. A correlation coefficient of zero means that there is no relationship between the
two variables (see Figure 2.4 c). A coefficient of +1.0 means that there is a very strong positive correlation between the variables (+1.0 is the most positive correlation coefficient possible). A coefficient of −1.0 means that there is a very strong negative correlation between the variables (−1.0 is the most negative correlation coefficient possible). Importantly, +1.0 and −1.0 coefficients have an equal magnitude or strength; however, they have a different direction.
Figure 2.4 Correlations Are Depicted in Scatterplots Here we see two variables that are positively correlated (a) and negatively correlated (b). In the example of a zero correlation (c), there is no relationship between the two variables.
Myths in Mind Beware of Illusory Correlations Chances are you have heard the following claims:
Crime and emergency room intakes suddenly increase when there is a full moon.
Opposites attract. Competitive basketball players (and even gamblers) get on a “hot streak” where one success leads to the next.
Many common beliefs such as these are deeply ingrained in our culture. They become even more widely accepted when they are repeated frequently. It is difficult to argue with a hospital nurse or police officer who
swears that full-moon nights are the busiest and craziest of all. The conventional, reserved, and studious man who dates a carefree and
spirited woman confirms that opposites attract. And, after Kyle Lowry has hit a few amazing jump shots for the Raptors, of course his chances of success just get better and better as the game wears on.
But do they? Each of these three scenarios is an example of what are
called illusory correlations —relationships that really exist only in the mind, rather than in reality. It turns out that well-designed studies have found no evidence that a full moon leads to, or is even related to, bizarre
or violent behaviour (Lilienfeld & Arkowitz, 2009). People who are attracted to each other are typically very similar (Buston & Emlen, 2003). Also, although some games may be better than others, overall the notion of a “hot streak” is not a reality in basketball or in blackjack
(Caruso et al., 2010; Gilovich et al., 1985).
Why do these illusory correlations exist? Instances of them come to mind easily and are more memorable than humdrum examples of “normal” nights in the ER, perfectly matched couples, and all of the times Kyle Lowry missed a shot, even in his best games. However, just because examples are easy to imagine, it does not mean that this is what typically occurs.
Contrary to very popular belief, a full moon is statistically unrelated to unusual events or increased emergency room visits. Shutterstock
Florian Franke/Corbis
You will encounter many correlations in this text, and it will be important to keep in mind the direction of the relationship—whether the variables are positively or negatively associated. One key point to remember is that the correlation
coefficient is a measure of association only—it is not a measure of causality. In other words, correlation does not equal causation. This is an extremely important point!
In many cases, a correlation gives the impression that one variable causes the other, but that relationship cannot be determined from correlational research. For example, we noted in the beginning of the module that a sense of humour is associated with good health—this is a positive correlation. But this does not
mean that humour is responsible for the good health. Perhaps good health leads to a better sense of humour. Or perhaps neither causes the other, but rather a third variable causes both good health and good sense of humour. This
possibility is known as the third variable problem , the possibility that a third, unmeasured variable is actually responsible for a well-established correlation between two variables. Consider the negative correlation between sleep and
irritability shown in scatterplot (b) of Figure 2.4 . Numerous third variables could account for this relationship. Stress, depression, diet, and workload could
cause both increased irritability and lost sleep. As you can see, correlations must be interpreted with caution.
Module 2.2b Quiz: Correlational Research
Know . . .
1. Which of the following correlation coefficients shows the strongest relationship between two variables?
A. +.54 B. −.72 C. +10.1 D. +.10
Understand . . .
2. What does it mean to say that two variables are negatively correlated? A. An increase in one variable is associated with a decrease in the
other.
B. An increase in one variable is associated with an increase in the other.
C. A decrease in one variable is associated with a decrease in the other.
D. The two variables have no relationship.
Analyze . . .
3. Imagine Dr. Martin finds that sense of humour is positively correlated with psychological well-being. From this, we can conclude that
A. humour causes people to be healthier. B. health causes people to be funnier.
C. people who have a good sense of humour tend to be healthier. D. people who have a good sense of humour tend to be less
healthy.
Experimental Research
Experimental designs improve on descriptive and correlational studies because they are the only designs that can provide strong evidence for cause-and-effect relationships. Like correlational research, experiments have a minimum of two variables, but there are two key differences between correlational research and experiments: the random assignment of the participants and the experimenter’s control over the variables being studied. As you will see, these unique features are what make experimental designs so powerful.
The Experimental Method
Imagine you were conducting an experiment testing whether seeing photographs of nature scenes would reduce people’s responses to stressful events. You carefully created two sets of images—one of peaceful images of the B.C. rain forests, Lake Louise, Algonquin Park in Ontario, and rugged Maritime coastlines —and another of neutral images such as houses. When the first two participants arrive at the laboratory for your study, one is wearing a t-shirt supporting a local environmental organization and the other is wearing a t-shirt emblazoned with an oil sands company logo. Which participant gets assigned to the nature scene condition and which gets assigned to the neutral condition? If you are conducting an objective, unbiased study, the answer to this question is that either participant is equally likely to be assigned to either condition. Indeed, a critical element of
experiments is random assignment , a technique for dividing samples into two or more groups in which participants are equally likely to be placed in any condition of the experiment. Random assignment allows us to assume the two groups will be roughly equal (Figure 2.5 ).
Figure 2.5 Elements of an Experiment If we wanted to test whether exposure to nature-related images causes a reduction in stress (as is assumed by people who have nature scenes as their computer’s wallpaper), we would first need to randomly assign people in our sample to either the experimental or control condition. The dependent variable, the stress levels, would be measured following exposure to either nature-related or neutral material. To test whether the hypothesis is true, the average stress scores in both groups would be compared.
If we assigned anyone who looked like they were nature lovers to the nature scene condition, then our experiment might not be telling us about the effects of
the images. Instead, some other confounding variable —a variable outside of the researcher’s control that might affect or provide an alternative explanation for the results—could potentially enter the picture. In our example, the variables of political awareness or tendency to be “outdoorsy” might play an even larger role in the study than the stimuli you worked so hard to create. Randomly assigning participants to the different experimental conditions also allows the researcher to assume that other sources of variability such as mood and personality are evenly spread across the different conditions. This allows you to infer that any differences between the two groups are because of the variable you are testing.
In this experiment, we are manipulating one variable (the types of images being
viewed) and measuring another variable (stress response). The variable that the
experimenter manipulates to distinguish between two or more groups is known as the independent variable . The participants cannot alter these variables, as they are controlled by the researcher. In contrast, the dependent variable
is the observation or measurement that is recorded during the experiment and subsequently compared across all groups. The levels of this variable are dependent upon the participants’ responses or performance. In our example, the type of images being viewed is the independent variable and the participants’ stress response is the dependent variable.
This experiment is an example of a between-subjects design , an experimental design in which we compare the performance of participants who are in different groups. One of these groups, the experimental group , is the group in the experiment that receives a treatment or the stimuli targeting a specific behaviour, which in this specific example would be exposure to nature scenes. The experimental group always receives the treatment. In contrast, the control group is the group that does not receive the treatment or stimuli targeting a specific behaviour; this group therefore serves as a baseline to which the experimental group is compared. In our example, the control group would not be exposed to nature photographs. What if the experimental group showed reduced stress compared to the control group? Assuming that the experiment was well designed and all possible confounds were accounted for, the researchers could conclude that the independent variable—exposure to images of nature—is responsible for the difference.
A between-subjects design allows the researcher to examine differences between groups; however, it is also open to criticism. What if the two groups were different from each other simply by chance? That would make it more difficult to detect any differences caused by your independent variable. In order
to reduce this possibility, researchers often use within-subjects designs , an experimental design in which the same participants respond to all types of stimuli or experience all experimental conditions. In the experiment we’ve discussed in this section, a within-subjects design would have involved participants viewing all of the images from one condition (e.g., nature photographs) before being tested, and then viewing all of the images from the other condition (e.g., neutral photographs) before being tested again. In this case, the order of the conditions
would be randomly assigned for each participant.
As you can see, designing an experiment requires the experimenter to make many decisions. However, in some cases, some of these decisions are taken out of the researchers’ hands.
The Quasi-Experimental Method
Random assignment and manipulation of a variable are required for experiments. They allow researchers to make the case that differences between the groups originate from the independent variable. In some cases, though,
random assignment is not possible. Quasi-experimental research is a research technique in which the two or more groups that are compared are selected based on predetermined characteristics, rather than random assignment. For example, you will read about many studies in this text that compare men and women. Obviously, in this case one cannot flip a coin to randomly assign people to one group or the other. Also, if you gather one sample of men and one sample of women, they could differ in any number of ways that are not necessarily relevant to the questions you are studying. As a result, all sorts of causes could account for any differences that would appear: genetics, gender roles, family history, and so on. Thus, quasi-experiments can point out relationships among pre-existing groups, but they cannot determine what it is about those groups that leads to the differences.
Converging Operations
An underlying theme of this module has been that each method of studying
behaviour has benefits as well as limitations (see Table 2.1 ). For example, naturalistic observation research allows psychologists to see behaviour as it normally occurs, but it makes experimental control very difficult—some would argue impossible. Conversely, to achieve true random assignment while controlling for any number of confounding variables and outside influences, the situation may be made so artificial that the results of an experiment do not apply to natural behaviour. Luckily, psychologists do not have to settle on only one method of studying behaviour. Most interesting topics have been studied using a
variety of possible designs, measures, and samples. In fact, when a theory’s predictions hold up to dozens of tests using a variety of designs—a perspective
known as converging operations—we can be much more confident of its accuracy, and are one step closer to understanding the many mysteries of human (and animal) behaviour.
Table 2.1 Strengths and Limitations of Different Research Designs
Method Strengths Limitations
Case studies Yields detailed
information, often of
rare conditions or
observations
Focus on a single subject limits
generalizability
Naturalistic observation Allows for detailed
descriptions of subjects
in environments where
behaviour normally
occurs
Poor control over possibly
influential variables
Surveys/questionnaires Quick and often
convenient way of
gathering large
quantities of self-report
data
Poor control; participants may
not answer honestly, written
responses may not be truly
representative of actual
behaviour
Correlational study Shows strength of
relationships between
variables
Does not allow researcher to
determine cause-and-effect
relationships
Experiment Tests for cause-and-
effect relationships;
offers good control over
influential variables
Risk of being artificial with
limited generalization to real-
world situations
Module 2.2c Quiz:
Experimental Research
Know . . . 1. If each participant in an experiment has an equal chance of being
assigned to the experimental group or the control group, we can assume
that this study involves . A. a correlational design B. a quasi-experimental design C. the random assignment of participants D. the experimental selection of participants
Understand . . . 2. A researcher sets up an experiment to test a new antidepressant
medication. One group receives the treatment and the other receives a placebo. The researcher then measures depression using a standardized self-report measure. What is the independent variable in this case?
A. Whether the individuals scored high or low on the depression measure
B. Whether the individuals received the treatment or a placebo C. Whether the individuals were experiencing depression before the
study began
D. Whether the individuals’ depression decreased or increased during the study period
Apply . . . 3. A researcher compares a group of Conservatives and a group of Liberals
on a measure of beliefs about poverty. What makes this a quasi- experimental design?
A. The researcher is comparing pre-existing groups, rather than randomly assigning people to them.
B. You cannot be both a Conservative and a Liberal at the same time.
C. There are two independent variables. D. There is no operational definition for the dependent variable.
Analyze . . . 4. A researcher is able to conduct an experiment on study habits in his
laboratory and finds some exciting results. What is one possible limitation of using this method?
A. Results from laboratory experiments do not always generalize to real-world situations.
B. Experiments do not provide evidence about cause-and-effect relationships.
C. It is not possible to conduct experiments on issues such as study habits.
D. Laboratory experiments do not control for confounding variables.
Module 2.2 Summary
between-subjects design
case study
confounding variable
control group
correlational research
dependent variable
experimental group
illusory correlations
independent variable
naturalistic observation
Know . . . the key terminology related to research designs.2.2a
qualitative research
quantitative research
quasi-experimental research
random assignment
research design
self-reporting
third variable problem
within-subjects design
When two or more variables are positively correlated, their relationship is direct —they increase or decrease together. For example, income and education level are positively correlated. Negatively correlated variables are inversely related— as one increases, the other decreases. Substance abuse may be inversely related to cognitive performance—higher levels of substance abuse are often associated with lower cognitive functioning.
Experiments rely on randomization and the manipulation of an independent variable to show cause and effect. At the beginning of an experiment, two or more groups are randomly assigned—a process that helps ensure that the two groups are roughly equivalent. Then, researchers manipulate an independent variable; perhaps they give one group a drug and the other group a placebo. At the end of the study, if one group turns out to be different, that difference is most likely due to the effects of the independent variable.
Understand . . . what it means when variables are positively or negatively correlated.
2.2b
Understand . . . how experiments help demonstrate cause-and-effect relationships.
2.2c
Apply . . . the terms and concepts of experimental methods to2.2d
Here are two examples for practice.
Apply Activity 1. Dr. Vincent randomly assigns participants in a study to exercise versus
no exercise conditions and, after 30 minutes, measures mood levels. In
this case, exercise level is the variable and mood is the variable.
2. Dr. Harrington surveyed students on multiple lifestyle measures. He discovered that as the number of semesters that university students complete increases, their anxiety level increases. If number of semesters
and anxiety increase together, this is an example of a(n) correlation. Dr. Harrington also found that the more time students spent socializing, the less likely they were to become depressed. The increase
in socializing and decrease in depression is an example of a(n) correlation.
Descriptive methods have many advantages, including observing naturally occurring behaviour and providing detailed observations of individuals. In addition, when correlational methods are used in descriptive research, we can see how key variables are related. Experimental methods can be used to test for cause-and-effect relationships. One drawback is that laboratory experiments might not generalize to real-world situations.
research examples.
Analyze . . . the pros and cons of descriptive, correlational, and experimental research designs.
2.2e
Module 2.3 Ethics in Psychological Research
Bettmann/Getty Images
Learning Objectives
Know . . . the key terminology of research ethics. Understand . . . the importance of reporting and storing data. Understand . . . why animals are often used in scientific research. Apply . . . the ethical principles of scientific research to examples.
2.3a 2.3b 2.3c 2.3d
In the early 1950s, the United States’ Central Intelligence Agency (CIA) became involved in the field of psychology. After hearing that their enemies in the Soviet Union, China, and North Korea had tried to use mind-control techniques—including mind-altering drugs—on U.S. prisoners of war, the CIA felt it had no choice but to research these techniques themselves. Project MKUltra began. After recruiting former Nazi scientists who had studied torture and “brainwashing” during World War II (and who had been prosecuted as war criminals), the CIA secretly poured tens of millions of dollars into research laboratories at hospitals and universities in order to study mind-control techniques that would alter people’s personalities, memories, and ability to control themselves while being interrogated. At least one of these institutions was in Canada.
Scottish psychiatrist Donald Ewen Cameron used CIA funds (as well as $500 000 from the Canadian government) to perform terrifying experiments at the Allan Memorial Institute of McGill University from 1957 to 1964. Patients who were admitted to the institute for fairly minor problems such as anxiety disorders or depression were—without giving proper consent or being informed of the reason for the “treatment”— subjected to manipulations that can only be called torture. These patients received drugs that caused temporary paralysis or even coma, electroconvulsive therapy set at more than 30 times the recommended strength, constant noises, and even looped tapes repeating messages
(Klein, 2007). These treatments led to amnesia, confusion, and anxiety; participants in these programs were never the same (Collins, 1988).
Project MKUltra was officially ended in 1973. The experi ments are now generally accepted as being among the most unethical studies in the history of science. In the 1980s, the Canadian government paid $100 000 to each of the 127 victims of Cameron’s unauthorized research program. For several decades, the CIA’s interrogation manual referred to “studies
at McGill University” (McCoy, 2006).
Analyze . . . the role of using deception in psychological research.2.3e
Focus Questions
1. Which institutional safeguards are now in place to protect the well-being of research participants?
2. Does all research today require that people be informed of risks and consent to participate in a study?
The topics that psychologists study deal with living, sensing organisms, which raises a number of ethical issues that must be addressed before any study begins. These concerns include protecting the physical and mental well-being of participants, obtaining consent from them, and ensuring that their responses remain confidential. The procedures discussed in the next section have been developed as protections for participants; they are critical not only to ensure the individual well-being of the study participants, but also to maintain a positive and trustworthy image of the scientists who conduct research.
Promoting the Welfare of Research Participants
The CIA mind-control research program certainly is an extreme case—extreme in the harm done to the volunteers, the disregard for their well-being, and its secretive nature. Today, most research with human participants involves short- term, low-risk methods, and there are now ethical guidelines and procedures for ensuring the safety and well-being of all individuals involved in research. In Canada, all institutions that engage in research with humans, including colleges
and universities, are required to have a research ethics board (REB) , a committee of researchers and officials at an institution charged with the protection of human research participants. (If you read a research report from an American institution, they will refer to Institutional Review Boards [IRBs]; these are the same thing as REBs.) REBs help ensure that researchers abide by the
ethical rules set out in the Tri-Council Policy Statement: Ethical Conduct for
Research Involving Humans (2nd edition), a set of requirements created by the Government of Canada’s Panel of Research Ethics. The REBs are intended to protect individuals in two main ways: (1) The committee weighs potential risks to the volunteers against the possible benefits of the research, and (2) it requires that volunteers agree to participate in the research (i.e., they give informed consent).
Weighing the Risks and Benefits of Research
The majority of psychological research, such as computer-based studies of perception or questionnaires studying personality traits, involves minimal exposure to physical or mental stress. Even so, great care is taken to protect participants. Some research involves more risk, such as exposing individuals to brief periods of stress, inducing a negative mood, asking about sensitive topics, or even asking participants to engage in brief periods of exercise. Some studies have even exposed humans to the virus that causes the common cold, or made small cuts to the skin to study factors that affect healing. The benefits that this type of research provides in promoting health and well-being must be weighed against the short-term risks to the people who consent to participate in these studies.
It must be stressed that physical risks are rare in psychological research. More common are measures that involve possible cognitive and emotional stress. Here are a couple of examples:
Mortality salience. In this situation participants are made more aware of death, which can be done in a number of ways. For example, participants may be asked to read or write about what happens to a human body after death.
Writing about upsetting or traumatic experiences. People who have experienced recent trauma such as the death of a loved one or being laid off from a long-term job might be asked to write about that experience in great detail, sometimes repeatedly.
Another source of risk is related to the fact that some studies ask participants to
provide the experimenter with sensitive and/or personal information. Think about all the topics in psychology that people might want to keep to themselves: opinions about teachers or supervisors, a history of substance abuse, criminal records, medical records, Internet search history, and so on. Disclosing this information is a potential threat to a person’s reputation, friends, and family. Psychologists must find ways to minimize these risks so that participants do not suffer any unintended consequences of participating in psychological research.
Indeed, everyone involved in the research process—the researcher, the REB, and the potential volunteer—must determine whether the study’s inherent risks are worth what can potentially be learned if the research goes forward. Consider again the stressors mentioned previously:
Mortality salience. The stress tends to be short term, and psychologists learn how decisions are influenced by recent events in a person’s life, such as the loss of a loved one or experiencing a major natural disaster. These decisions range from making charitable donations to voting for or against going to war.
Writing about upsetting experiences. Although revisiting a stressful experience can be difficult, researchers learn how coping through expression can help emotional adjustment and physical health. In fact, participants who write about stress tend to be healthier—emotionally and physically—than those who write about everyday topics (such as describing their dorms or apartments).
These stressful situations have potential benefits that can be applied to other people. The psychologists who undertake such research tend to be motivated by several factors—including the desire to help others, the drive to satisfy their intellectual curiosity, and even their own livelihood and employment. The REB serves as a third party that weighs the risks and benefits of research without being personally invested in the outcome. Under today’s standards, there is no chance that the CIA mind-control studies would have been initiated, except in secrecy outside of the public process of science. The danger to the participants
in that study—victims might be a better term—far outweighed any scientific benefit gained from the experiments, even if the participants had known what
they were getting into. Today, it is mandatory that research participants be informed of any risks to which they may be exposed and willfully volunteer to take part in a study.
Obtaining Informed Consent
In addition to weighing the risks versus the benefits of a study, researchers must
ensure that human volunteers truly are volunteers. This may seem redundant, but it is actually a tricky issue. Recall that the human subjects in the CIA mind- control studies were volunteers only in the sense that they voluntarily sought treatment from the researchers. But did they volunteer to undergo procedures that were very close to being torture? Had the men and women known the true nature of the study, it is doubtful that any would have continued to participate. Currently, participants and patients have much more protection than they did in the 1950s and 1960s. Before any experimental procedures begin, all participants
must provide informed consent : A potential volunteer must be informed (know the purpose, tasks, and risks involved in the study) and give consent (agree to participate based on the information provided) without pressure.
To be truly informed about the study, volunteers should be told, at minimum, the
following details (see also Figure 2.6 ):
The topic of the study The nature of any stimuli to which they will be exposed (e.g., images, sounds, smells)
The nature of any tasks they will complete (e.g., tests, puzzles) The approximate duration of the study Any potential physical, psychological, or social risks involved The steps that the researchers have taken to minimize those risks
Ethical practices often involve resolving conflicting interests, and in psychological research the main conflict is between the need for informed consent and the
need for “blinded” volunteers. (Recall from Module 2.1 that in the best experimental designs the participants do not know exactly what the study is about, because such information may lead to subject bias.) Consider the
mortality salience example. If a researcher told a participant, “We are going to test how a recent stressor you have experienced has affected your behaviour,” then the experiment probably would not work. In these cases, researchers use deception — misleading or only partially informing participants of the true topic or hypothesis under investigation. In psychological research, this typically amounts to a “white lie” of sorts. The participants are given enough information to evaluate their own risks. In medical research situations, however, deception can be much more serious. For example, patients who are being tested with an experimental drug may be randomly chosen to receive a placebo. Importantly, in both cases, the deception is only short-term; once the experiment is over, the participants are informed of the true nature of the study and why deception was necessary. Additionally, if a treatment was found to be effective for the experimental group, it will often be made available to participants in the control
group at the end of the experiment. This helps to ensure that anyone who could benefit from the study does benefit from the study.
Figure 2.6 Informed Consent Research participants must provide informed consent before taking part in any study. As shown here, the participant must be made aware of the basic topic of the study as well as any possible risks.
Once participants are informed, they must also be able to give consent. Again, meeting this standard is trickier than it sounds. To revisit the mind-control studies, the patients were emotionally vulnerable people seeking help from a noted psychiatrist (Dr. Cameron was the president of both the Canadian and American Psychiatric Associations) at a world-class university. They were not told of the treatments they would receive; in some cases, the patients were not informed that they were part of a study at all! Clearly, informed consent was not provided by these research participants. Based on the ethical issues arising from this and many other disturbing studies, modern psychological (and psychiatric and neurological) research includes the following elements in determining whether full consent is given:
Freedom to choose. Individuals should not be at risk for financial loss, physical harm, or damage to their reputation if they choose not to participate.
Equal opportunities. Volunteers should have choices. For example, if the volunteers are introductory psychology students seeking course credit, they must have non-research alternatives available to them for credit should they choose not to participate in a study.
The right to withdraw. Volunteers should have the right to withdraw from the study, at any time, without penalty. The right to give informed consent stays with the participants throughout the entire study.
The right to withhold responses. Volunteers responding to surveys or interviews should not have to answer any question that they feel uncomfortable answering.
Usually, these criteria are sufficient for ensuring full consent. Sometimes, however, psychologists are interested in participants who cannot give their consent that easily. If researchers are studying children or individuals with mental disabilities, some severe psychiatric disorders, or certain neurological
conditions, then a third party must give consent on behalf of the participant. This usually amounts to a parent or next-of-kin and, of course, all the rules of informed consent still apply.
After participating in the research study, participants must undergo a full debriefing , meaning that the researchers should explain the true nature of the study, and especially the nature of and reason for any deception. Although the debriefing of subjects might sound like some kind of military term, it is actually a very important part of the scientific process. You’ve already read how it is used when deception (or a placebo) is part of a study. But, even in more straightforward experiments, debriefing is necessary to ensure that the participants understand why their time and effort was necessary. This results in the participants leaving the experiment better-informed about your topic of study as well as about the many considerations involved in creating a psychology experiment. In short, it helps them become more scientifically literate.
The Right to Anonymity and Confidentiality
A final measure of protection involves anonymity and confidentiality. Anonymity means that the data collected during a research study cannot be connected to individual participants. In many cases, volunteers can respond on a survey or through a computer-based experimental task without recording their name. This setup is ideal because it reduces both methodological problems (socially desirable responding) and the social risks to participants. If pure anonymity is not possible—for example, when a researcher must watch the participant perform a
task—then confidentiality is a reasonable substitute. Confidentiality includes at least two parts. First, researchers cannot share specific data or observations that can be connected with an individual. Second, all records must be kept secure (for example, in a password-protected database or locked filing cabinet) so that identities cannot be revealed unintentionally.
The Welfare of Animals in Research
Many people who have never taken a psychology course view psychology as the
study of human behaviour, possibly because most psychological research does
involve humans. But research with animals is just as important to psychological science for a number of reasons. The simplest and perhaps most obvious is that
the study of psychology does include the behaviour of animals. However, the most significant reason is that scientists can administer treatments to animals that could never be applied to humans, such as lesioning (damaging) specific areas of the brain in order to examine the resulting behavioural impairments. In addition, genetic research requires species with much shorter life spans than our own so that several successive generations can be observed. Finally, scientists can manipulate the breeding of laboratory animals to meet the needs of their experimental procedures. Selective breeding allows researchers to study highly similar groups of subjects, which helps control for individual differences based on genetic factors.
These forms of animal-based experimentation have improved our understanding of a number of different areas of behaviour. The research area that has benefited most from the use of animal subjects is the study of different brain-related diseases. This leads to an ethical dilemma, however: Is it ethically acceptable to create disease-like symptoms in animals if it could lead to discoveries that could help thousands—or sometimes millions—of people?
Many psychologists use animals in their research, so ethical codes have been extended to cover nonhuman species. Mona Lisa Production/Photo Researchers, Inc./Science Source
Working the Scientific Literacy Model Animal Models of Disease
MPTP (1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine) was accidentally discovered in 1976 by a 23-year-old chemistry graduate student who was attempting to create MPPP, a synthetic drug that produces morphine-like effects. Three days after injecting himself with what he thought would be a pleasure- inducing drug, he began to show symptoms of Parkinson’s disease, including tremors and difficulties initiating movements. Six years later, seven young people in Santa Clara County, California, were diagnosed with Parkinson’s disease, which typically develops in older adults. Again, these individuals had injected doses of MPPP that were contaminated with MPTP. Based on these cases, neurologists realized that the compound MPTP could prove useful as a model of Parkinson’s disease
(Langston et al., 1983). Animals receiving injections of MPTP quickly develop Parkinsonian symptoms; it is therefore possible to use these animals to test possible treatments of this disorder. MPTP is now the toxin most frequently used for animal models of
Parkinson’s disease (Blesa et al., 2012). This leads to interesting questions, however. Are animal models valid and useful tools for researchers trying to find treatments and cures for diseases? Is this process ethical?
What do we know about animal models of diseases? MPTP is just one of hundreds of techniques for modelling different diseases. There are animal models for Alzheimer’s
disease, depression, schizophrenia, autism, stroke, Huntington’s disease, epilepsy, and drug addiction, among many others
(Nestler & Hyman, 2010; Virdee et al., 2012). Not all diseases or conditions can be modelled in the same way, however. Depending upon the underlying cause of the disorder and the brain areas that are likely involved, there are at least four methods scientists can use to create an animal model. First, if a disease is associated with a specific brain area, researchers could anesthetize an animal and remove or damage that part of its brain. Brain damage could also occur by introducing a toxic substance, as occurred in the MPTP patients. Second, scientists could introduce a substance that increased or decreased the
levels of certain brain chemicals known as neurotransmitters in the brain (see Module 3.2 ). Parkinson’s disease is caused by a loss of the neurotransmitter dopamine; therefore, a drug that reduced dopamine levels could simulate the symptoms of Parkinson’s. Third, researchers could create animal models of certain disorders by altering the environments of the animals. For instance, placing animals in an environment that is physically or socially stressful can cause them to behave similarly to
individuals with anxiety disorders (Willner et al., 1987). Finally, scientists can manipulate the genetic make-up of animals. While earlier research was limited to selectively breeding animals so that they became more prone to a disease, it is now possible to directly alter the genetic codes of animals so that particular traits
and physical structures are altered (Spires-Jones & Knafo, 2012). However, despite the enormous possibilities associated with animal models, these techniques are only as good as the scientists who use them.
How can science test animal models of diseases? The primary goal of developing animal models of a neurological condition, such as the MPTP model of Parkinson’s disease, is to simulate the characteristics of a disease so that researchers can test possible treatments without harming humans. Although this
may sound unethical at first, there is a logic behind the use of animal models. In order to find treatments for a disease, scientists need a very large number of individuals with the disease to use as test subjects. Any given treatment that is currently available to humans underwent testing with thousands —sometimes tens of thousands—of animals in order to test different chemical compounds and doses to ensure that the side effects of the treatment did not outweigh its benefits. There are simply not enough people with some diseases for this type of trial-and-error testing to occur. Any study that could take place would require the cooperation of universities and hospitals across the world. And, if that single attempt did not work, it would be difficult to find patients who had not already been tested to use in subsequent treatment attempts. Therefore, the use of animal models was a product of necessity.
Importantly, animal models are not developed in a random fashion. Instead, each animal model of a disease must have the
following characteristics (Dzirasa & Covington III, 2012). First, it must share the same physiological and behavioural features of the disease as appear in humans. An animal model of depression would not be accepted if the animals were energetic and playful; instead, the animals’ behaviours must resemble the behaviours of humans with depression. Second, both the animal model and the “real” disorder must involve similar brain structures; otherwise, researchers would be comparing apples and oranges. Third, the tests used to measure the behaviours must be valid. For depressed humans, laboratory tests often involve questionnaires or computer-based tests; these are obviously not useful research methods when testing rats or mice. Instead, the researcher must use an indirect test to try to tap into the same underlying symptom. For example, one symptom of depression is
anhedonia, the tendency to get less pleasure out of life than one previously did. To test anhedonia in rats, scientists use a sucrose preference test, a task in which rats have the opportunity to seek
out a pleasurable taste (sugar!) if they are motivated to do so. The assumption is that “depressed” rats, just like depressed
humans, would be less likely to seek out such stimuli (Cryan et al., 2002).
How can we critically evaluate these models? The easiest criticism of animal models of disease is that animal brains are not human brains. Human brains are obviously more complex; therefore, how valid is it to assume that treatments that change an animal’s behaviour will benefit humans? And, if this isn’t guaranteed, is it ethical to use animal subjects in this way? A second criticism is that researchers are only beginning to understand the specific brain areas involved with a number of different conditions. Oftentimes, a large number of interacting brain areas are involved with a disorder. So, if we are unclear of the biology involved in the human version of the disease, how accurate can the resulting animal models really be? Additionally, it is fairly easy to test the validity of animal models of neurological diseases that have clear, observable symptoms (e.g., Parkinson’s disease and epilepsy); animals modelling epilepsy will have seizures that you can see. However, models of psychological conditions like depression and schizophrenia present a greater challenge, as the symptoms are often thought-based and subjective. The rat can’t explain what he is seeing or feeling. Instead, the researchers must infer that these mental states are occurring (in one form or another) in the animal subjects being tested. Finally, is an animal with limited cognitive abilities even
capable of serving as a model for a disorder that involves impairments of higher-order cognitive abilities (Nestler & Hyman, 2010)? For example, how can you tell if a laboratory rat is having a hallucination?
These are all valid criticisms and highlight the importance of meeting the conditions of a good model discussed in the previous section. Our confidence in an animal model will also increase if
other lines of research produce similar results. So, if brain- imaging tests in humans find problems in the same brain areas being manipulated in an animal model, that model will become more valid. Through the use of converging operations—using multiple research methods to analyze the same question—it is possible to create effective animal models.
Why is this relevant? Anyone who has watched an elderly relative become a shadow of his or her former self as a result of a neurological disease such as Alzheimer’s or Parkinson’s disease can likely understand the usefulness of animal models. It is impossible to perform large- scale research investigating these disorders and their possible treatment without the use of these experiments. Therefore, the animals used in these studies are helping to reduce the suffering of millions of people around the world. Whether you agree that it is appropriate to use animals in this fashion is a personal decision that you will have to make on your own. It is important to note that the researchers who perform this type of research also think about these issues. They certainly don’t take their ethical responsibilities lightly; every university and research hospital has extremely strict requirements for the treatment of laboratory animals and the well-being of all animals is monitored by laboratory technicians and veterinarians. Importantly, all of these activities are closely monitored by the institution’s REB.
Rebs for Animal-Based Research
Many ethical standards for animal research were developed at the same time as those for human research. In fact, hospitals and universities have established committees responsible for the ethical treatment of animals, which are in some ways similar to REBs that monitor human research. To be sure, there are
differences in standards applied to human research and animal research. For example, we obviously do not ask for informed consent from animals. Nevertheless, similar procedures have been put in place to ensure that risk and discomfort are managed in a humane way, and that the pain or stress an animal may experience can be justified by the potential scientific value of the research.
Three main areas of ethical treatment are emphasized by researchers and animal welfare committees. The first is the basic care of laboratory animals—that is, providing appropriate housing, feeding, and sanitation for the species. The second is minimization of any pain or discomfort experienced by the animals.
Third, although it is rare for a study to require discomfort, when it is necessary, the researchers must ensure that the pain can be justified by the potential benefits of the research. The same standards apply if animals are to be sacrificed for the research.
Module 2.3a Quiz:
Promoting the Welfare of Research Participants
Know . . . 1. The Research Ethics Board (REB) is the group that determines
A. whether a hypothesis is valid. B. whether the benefits of a proposed study outweigh its potential
risks.
C. whether a study should be published in a scientific journal. D. whether animal research is overall an ethical practice.
Understand . . . 2. Which of the following is not a requirement for informed consent?
A. Participants need to know the nature of the stimuli to which they will be exposed.
B. Participants need to understand any potential physical, psychological, or social risks involved in the research.
C. Participants need to have a face-to-face meeting with the researcher before volunteering.
D. Participants need to know the approximate duration of the study.
Analyze . . . 3. In a memory study, researchers have participants study a list of words
and then tell them it was the wrong list and that they should forget it. This deception is meant to see how effectively participants can forget something they have already studied. If the researchers plan to debrief the participants afterward, would this design meet the standards of an ethical study?
A. No, it is not okay to mislead individuals during the course of a study.
B. Yes, given that the participants are not at risk and that they will be debriefed, this seems to be an ethical study.
C. No, because the researchers should not debrief the participants. D. Yes, because the participants fully understood all aspects of the
study.
Ethical Collection, Storage, and Reporting of Data
Ethical research does not end when the volunteers go home. Researchers have continuing commitments to the participants, such as the requirement to maintain the anonymity, confidentiality, and security of the data. Once data are reported in a journal or at a conference, they should be kept for a reasonable amount of time —generally, three to five years is acceptable. The purpose of keeping data for a lengthy period relates to the public nature of good research. Other researchers may request access to the data to reinterpret it, or perhaps examine the data before attempting to replicate the findings. It might seem as though the confidentiality requirement conflicts with the need to make data public, but this is not necessarily true. For example, if the data are anonymous, then none of the participants will be affected if and when the data are shared.
In addition to keeping data safe, scientists must be honest with their data. Some
researchers experience great external pressure to obtain certain results. These pressures may relate to receiving tenure at a university; gaining funding from a governmental, industrial, or nonprofit agency; or providing evidence that a product (for example, a medical treatment for depression) is effective.
Unfortunately, cases of scientific misconduct sometimes arise when individuals fabricate or manipulate their data to fit their desired results. For instance, in 1998, British researcher Andrew Wakefield and his colleagues published a paper
in the highly influential medical journal The Lancet describing a link between the vaccine for measles, mumps, and rubella and the incidence rate of autism
(Wakefield et al., 1998). The response was immediate—many concerned parents stopped having their children vaccinated out of fear that their kids would then develop autism. Panic was increased by sensationalistic media reports of the study as well as by an anti-vaccine media campaign launched by celebrity personality (and, apparently, amateur developmental neurobiologist) Jenny McCarthy. Vaccine rates plummeted. However, autism rates did not change; what did change were the incidence rates of the diseases the vaccines would have prevented. Hundreds of preventable deaths occurred because children were not vaccinated. Then something interesting happened: Numerous institutions in several different countries reported that they were unable to replicate Wakefield’s results. As his data received more attention, it became clear that some of it had been manipulated to fit his theory. Additional investigations uncovered the fact that Wakefield planned to develop screening kits to test for stomach problems associated with the vaccine; in other words, he had a financial motivation for creating a controversy related to the vaccine. Luckily, such cases of misconduct seem to be rare and, as occurred in this instance, other scientists are likely to find that the study cannot be replicated in such instances.
The chances of fraudulent data being published can also be decreased by requiring researchers to acknowledge any potential conflicts of interest, which might include personal financial gain from an institution or company that funded the work. If you look at most published journal articles, you will see a footnote indicating which agency or organization provided the funds for the study. This annotation is not just a goodwill gesture; it also informs the public when there is
the potential for a company or government agency to influence research. Incidentally, the CIA was not mentioned in any published work resulting from the mind-control studies discussed at the beginning of this module. Dr. Cameron’s family destroyed all of his papers upon his death in 1967.
Module 2.3b Quiz: Ethical Collection, Storage, and Reporting of Data
Understand . . .
1. Researchers should store their data after they present or publish it because
A. other researchers may want to examine the data before conducting a replication study.
B. other researchers may want to reinterpret the data using different techniques.
C. the process of informed consent requires it. D. both a and b are true.
Apply . . .
2. After completing a naturalistic observation study, a researcher does not have quite enough evidence to support her hypothesis. If she decides to go back to her records and slightly alters a few of the observations to fit
her hypothesis, she is engaged in . A. informed forgery B. scientific misconduct C. correcting the data D. ethical behaviour
Module 2.3 Summary
Know . . . the key terminology of research ethics.2.3a
debriefing
deception
informed consent
research ethics board (REB)
Making data public allows scientific peers as well as the general public to have access to the details of research studies. This information includes details about participants, the procedures they experienced, and the outcome of the study. Furthermore, the requirement that data be stored allows fellow researchers to verify reports as well as to examine the study for any possible misconduct. Fortunately, such cases are rare.
First, many research questions that affect medical and public health cannot be answered without animal testing. Second, obvious ethical considerations may not allow such research to be conducted on human subjects. Third, by working with animal models, scientists can control genetic and environmental variables that cannot be controlled with humans.
For practice, read the following two scenarios and identify why they may fail to meet ethical standards.
Apply Activity
1. Dr. Nguyen wants to expose individuals first to a virus that causes people to experience colds, and then to varying levels of exercise to test whether exercise either facilitates or inhibits recovery. She is concerned that people will not volunteer if they know they may experience a cold, so she wants to give them the informed consent form after completing the study.
Understand . . . the importance of reporting and storing data.2.3b
Understand . . . why animals are often used in scientific research.2.3c
Apply . . . the ethical principles of scientific research to examples.2.3d
2. Researchers set up a study on sexuality that involves answering a series of questions in an online survey. At the end of each page of the survey, the software checks whether all of the questions are answered; it will not continue if any questions are left blank. Students cannot advance to the end of the survey and receive credit for participation until they answer all the questions.
It is often the case that fully disclosing the purpose of a study before people participate in it would render the results useless. Thus, specific details of the study are not provided during informed consent (although all potential risks are disclosed). When deception of any kind is used, researchers must justify that the benefits of doing so outweigh the costs.
Analyze . . . the role of using deception in psychological research.2.3e
Module 2.4 A Statistical Primer
Image Source/Glow Images
Learning Objectives
Would you be surprised to learn that even infants and toddlers can think
about probability, the foundation of statistics? Dr. Allison Gopnik (2010)
Know . . . the key terminology of statistics. Understand . . . how and why psychologists use significance tests. Apply . . . your knowledge to interpret the most frequently used types of graphs. Analyze . . . the choice of central tendency statistics based on the shape of the distribution.
2.4a 2.4b 2.4c
2.4d
writes about some interesting experiments showing just how statistically minded young children are. For example, consider the illustration below. If a researcher reached in and randomly selected five balls, would you be more surprised if they were all red or all white? Given that the white balls outnumber the red, you would be much more surprised if the researcher pulled out five red balls. Interestingly, infants show the same response. In another experiment, Gopnik’s research team placed blue or yellow blocks into a fancy contraption. Yellow blocks appeared to make the machine light up two out of three times (67% of the time), whereas the blue blocks only seemed to work two out of six times (33% of the time). When asked to “make the machine light up,” preschoolers selected the yellow blocks, which had a higher probability of working. If eight-month-olds and preschoolers can think statistically, adults should also be able to do so!
Focus Questions
1. How do psychologists use statistics to describe their observations?
2. How are statistics useful in testing the results of experiments?
Statistics initially seem scary to a lot of people. But, they don’t have to be. Statistics can be boiled down to two general steps. First, we need to organize the numbers so that we can get a “big picture” view of the results; this process is helped by the creation of tables or graphs. Second, we want to test to see if any differences between groups or between experimental conditions are meaningful.
Once these steps have been completed, it is possible to determine whether the data supported or refuted our hypothesis. In order to keep statistics simple, this module is organized around these two general steps.
Descriptive Statistics
Once research data have been collected, psychologists use descriptive statistics , a set of techniques used to organize, summarize, and interpret data. This gives you the “big picture” of the results. In most research, the statistics used to describe and understand the data are of three types: frequency, central tendency, and variability.
Frequency
Imagine that you asked a group of students who had just taken the Graduate Record Exam (GRE), a standardized test taken by people who want to go to graduate school, how well they did on the exam. Assuming they were honest, you would likely find scores ranging from the 300s up to the high 600s. What you would want to know is (1) whether some scores occurred more often than others and (2) whether all of the scores were clumped in the middle or more evenly spaced across the whole range. These two pieces of information make up the
data’s distribution; the examination of the distribution is a useful first step when analyzing data. Figure 2.7 depicts these data in the form of a histogram, a type of bar graph. As with most bar graphs, the vertical axis of this graph shows the frequency , the number of observations that fall within a certain category or range of scores. These graphs are generally very easy to interpret: The higher the bar, the more scores that fall into the specific range. For example, if you look
on the horizontal axis in Figure 2.7 , you will see a column of test scores corresponding to people who scored around 500 on the test. Looking over to the vertical axis, you will see there were four individuals in that range. It is usually easy to describe the distribution of scores from a histogram. By examining changes in frequency across the horizontal axis—basically by describing the heights of the bars—we can learn something about the variable.
Figure 2.7 Graphing Psychological Data The frequency of standardized test scores forming a normal curve.
Histograms are a nice and simple way to present data and are excellent for providing researchers and students with an initial idea of what the data look like. But, they are not the only way to depict results of an experiment. Sometimes it is easier to answer questions about the distribution of the data if we present the
same information using a smooth line called a curve. Sometimes a distribution is a symmetrical curve, as it is with our GRE scores. In this case, the left half is the mirror image of the right half. This is known as a normal distribution
(sometimes called the bell curve), a symmetrical distribution with values clustered around a central, mean value.
Many variables wind up in a normal distribution, such as the scores on most standardized tests. Other variables have what is known as a skewed distribution,
like the ones shown in Figure 2.8 . You’ve likely encountered skewed distributions in your own life. Imagine a situation in which the grades on a school assignment were incredibly high, with only a few people performing poorly. In
this case, the curve would show a negatively skewed distribution , a distribution in which the curve has an extended tail to the left of the cluster. However, what if the test were extremely difficult, like a calculus exam written by
a professor with a mean streak? In this case, most people in the course would have low scores, with only a few stellar students getting As. These results would
produce a positively skewed distribution , a distribution in which the long tail is on the right of the cluster. Although researchers generally prefer to have normally distributed data, skewed results are quite common. Most of the time, skews occur because there is an upper or lower limit to the data. For example, a person cannot take less than 0 minutes to complete a quiz, so a curve depicting times to complete a quiz cannot continue indefinitely to the left, beyond the zero point. In contrast, just one person could take a very long time to complete a quiz, causing the right side of the curve to extend far to the right.
Figure 2.8 Skewed Distributions Negatively skewed distributions have an extended tail to the left (as in the left graph below). Positively skewed distributions have an extended tail to the right (as in the right graph below).
Central Tendency
When examining data, it is often useful to look at where the scores seem to
cluster together. When we do this, we are estimating central tendency , a measure of the central point of a distribution. Although we naturally assume that the central tendency is “the average,” there are actually three different measures
of central tendency used in psychology. The first measure is known as the mean , the arithmetic average of a set of numbers. This is the measure of central tendency that we are most familiar with as it is used for class averages and in most sports (e.g., batting average in baseball or goals-against average in
hockey). A second measure of central tendency is the median , the 50th percentile—the point on the horizontal axis at which 50% of all observations are lower, and 50% of all observations are higher. The third and final measure of central tendency is the mode , which is the category with the highest frequency (that is, the category with the most observations).
At first glance, it might seem silly to have three different methods of measuring the central tendency of your data. Indeed, when the data are normally distributed
as they are in Figure 2.9 , the mean, median, and mode are identical. The mean is $30 000, which is exactly in the centre of the histogram. The same can be said for the median; again, it is $30 000, with half of the incomes less than $30 000 and half more than $30 000. Likewise, the mode is the same as the mean and median—$30 000 has the highest frequency, which, as seen in Figure 2.9 , is 3. So, if the three measures of central tendency are equal, which do we use? If the data are normally distributed, researchers generally use the mean. But, if the data are skewed in some way, then researchers need to
think about which measure is best. The measure used least is the mode. Because it provides less information than the mean or the median, the mode is typically only used when dealing with categories of data. For example, when you vote for a candidate, the mode represents the candidate with the most votes, and (in most cases) that person wins.
Figure 2.9 Central Tendency in Symmetrical Distributions This symmetrical histogram shows the annual income of nine randomly sampled households. Notice that the mean, median, and mode are all in the same spot— this is a characteristic of normal distributions.
When the data are not a perfectly symmetrical curve, the mean, median, and mode produce different values. If the histogram spreads out in one direction—in Figure 2.10 , it is positively skewed—we are usually better off calculating central tendency by using the median. This is because extreme values (positive or negative) will have a large effect on the mean, but will not affect the median. In other words, when you start to add extremely wealthy households to the data set, the tail extends to the right and the mean is pulled in that direction. The longer the tail, the more the mean is pulled away from the centre of the curve. By comparison, the median stays relatively stable, so it is a better choice for describing central tendency when dealing with skewed data. For instance, if you added Bill Gates’s annual income (approximately $11.5 billion dollars—for a net
worth over $72 billion) to the list of nine incomes in Figure 2.10 , the mean annual income becomes just over $1.5 billion. If you take the median of those ten incomes, the central tendency is $30 000. Looking at those data, which measure seems most consistent with the “big picture” of the results?
Figure 2.10 Central Tendency in a Skewed Distribution The mean is not always the ideal measure of central tendency. In this example, the mode and the median are actually more indicative of how much money most people make.
Variability
Measures of central tendency help us summarize a group of individual cases with a single number by identifying a cluster of scores. However, this information
only tells us part of the story. As you can see in Figure 2.11 , scores can differ in terms of their variability , the degree to which scores are dispersed in a distribution. In other words, some scores are quite spread out while others are more clustered. High variability means that there are a larger number of cases
that are closer to the extreme ends of the continuum for that set of data (e.g., a
lot of excellent students and a lot of poor students in a class). Low variability means that most of the scores are similar (e.g., a class filled with “B” students). Variability can be caused by measurement errors, imperfect measurement tools, differences between participants in the study, or characteristics of participants on that given day (e.g., mood, fatigue levels). All data sets have some variability. But, if information about variability is not provided by the researcher, it is impossible to understand how well the measure of central tendency—the single score representing the data—reflects the entire data set. Therefore, whenever psychologists report data from their research, their measures of central tendency are almost always accompanied by measures of variability.
Figure 2.11 Visualizing Variability Imagine that these curves show how two classes fared on a 20-point quiz. Both classes averaged scores of 15 points. However, the students in one class (depicted in red) scored much more similarly to one another compared to students in another class (depicted in black), whose scores showed greater variability. The class represented by the black line would have a higher standard deviation.
One calculation that allows researchers to link central tendency and variability is
known as the standard deviation , a measure of variability around the mean. Think of it as an estimate of the average distance from the mean. A large standard deviation would indicate that there is a lot of variability in the data and that the values are quite spread out from the mean. A small standard deviation would indicate the opposite.
Standard deviations allow investigators to see how different scores relate to the mean and to each other. Perhaps the best way to understand the standard deviation is by working through an example. In a standard intelligence test, there is a normal distribution (a bell curve) with a mean of 100 and a standard
deviation of 15 (see Module 9.1 ). Based on what you’ve read in this module, you would infer that 100 is the mid-point of the curve when these data are graphed. But, how much of the data is included in each standard deviation? As
you can see in Figure 2.12 , researchers have found that approximately 68% of the data are found within one standard deviation of the mean—34% above the mean (between 100 and 115) and 34% below the mean (between 85 and 100). This makes intuitive sense—we would expect a fairly large proportion of the scores to be grouped near the average score. As we move further away from the average score, each standard deviation would make up less and less of the data, because really high or really low scores are relatively rare. So, the next standard deviation in our example makes up roughly 27% of the data—13.5% of the scores would fall between 70 and 85 and 13.5% would fall between 115 and 130. When you add the two standard deviations together, you can see that they include over 95% of the IQ scores in the population. Therefore, when you hear about people like the physicist Stephen Hawking, whose IQ is estimated to be around 160, you can see that these are rare individuals indeed (comprising less than one-tenth of a percent of the population).
Figure 2.12 Standard Deviations in a Normal Distribution In a normal curve, most of the data are clustered within one standard deviation of the mean. Over 95% of the data in a normal distribution are found within two standard deviations of the mean.
This section of the module demonstrates that by making a graph and reporting two numbers—the measure of central tendency and the standard deviation—you can provide a “big picture” summary of your data that almost anyone can understand. That’s Step 1 of statistics. Step 2 uses these measures to test whether or not your hypothesis is supported by your data—in other words, whether your project worked.
Module 2.4a Quiz:
Descriptive Statistics
Know . . . 1. The always marks the 50th percentile of the distribution.
A. mean B. median C. mode D. standard deviation
2. The is a measure of variability around the mean of a distribution.
A. mean deviation B. median C. mode D. standard deviation
Apply . . . 3. Dr. Lee taught two sections of Introductory Psychology. The mean score
for both classes was 70%. However, the standard deviation was 15% for the first class and 5% for the second class. What can we infer about Dr. Lee’s two classes?
A. There was more variability in the test scores of the first class. B. The mode would equal the mean in the first class but not in the
second class.
C. There was more variability in the second class than in the first class.
D. The mean, median, and mode would all be equal in the second class.
Analyze . . . 4. In a survey of recent graduates, your university reports that the mean
salaries of the former students are positively skewed. What are the consequences of choosing the mean rather than the median or the mode in this case?
A. The mean is likely to provide a number that is lower than the largest cluster of scores.
B. The mean is likely to provide a reliable estimate of where the scores cluster.
C. The mean is likely to provide a number that is higher than the largest cluster of scores.
D. The mean provides the 50th percentile of the distribution, making it the best choice to depict this cluster of scores.
Hypothesis Testing: Evaluating the Outcome of a Study
After researchers have described their data, the next step is to test whether the data support their hypothesis. In order to do this, researchers analyze data using
a hypothesis test —a statistical method of evaluating whether differences among groups are meaningful, or could have been arrived at by chance alone. What scientists are essentially trying to do is determine if their experimental manipulation is the cause of any difference between groups or between conditions. However, the ability to tease out these differences is affected by the concepts discussed earlier in this module—specifically, the measure of central tendency for the groups being measured as well as the variability of data in each of the groups. The difference in the central tendency for the two groups represents a “signal” that we are trying to detect, similar to a voice in a loud room. The variability represents the “noise,” the outside forces that are making it difficult to detect the signal.
To make this discussion more concrete, let’s use an example of a behaviour that almost everyone performs: texting. Let’s say that we wanted to test whether text messaging reduces feelings of loneliness in first-year university students. For three days, randomly selected students who regularly send text messages are assigned to one of two groups: those who can text and those who cannot. After three days, the students fill out a survey measuring how lonely they have felt.
The diagram in Figure 2.13 shows us the key elements of such an experiment. Individuals are sampled from the population and randomly assigned to either the experimental or control group. The independent variable consists of the two groups, which includes texting or no texting. The dependent variable is the outcome—in this case, loneliness (as measured by a valid questionnaire), with larger scores indicating greater loneliness. As you can see, the mean loneliness score of the group who could text message is three points below the mean of the group who did not text message (78 vs. 81, respectively). So, based on this information, are you willing to say that texting causes people to feel less lonely? Or have we left something out?
Figure 2.13 Testing a Simple Hypothesis To conduct an experiment on whether texting reduces loneliness, students would be randomly assigned to either text-messaging or no-text-messaging groups. Their average scores on a loneliness scale would then be compared.
What we do not know from the diagram is the variability of test scores. On the one hand, it is quite possible that the scores of the two groups look like the
graphs on the left in Figure 2.14 . In that situation, the means are three points apart and the standard deviation is very small, so the curves have very little overlap. In this case, it is fairly easy to detect differences between the groups; the “signal” is easy to pick out from the “noise.” On the other hand, the scores of each group could have a broad range and therefore look like the graphs on the right. In that case, the group means are three points apart, but the groups overlap so much—the standard deviations are very high—that they seem virtually identical. In this case, the “noise”—the variability within each of the two groups—is so large that it is difficult to detect the “signal,” the differences between the two groups.
Figure 2.14 How Variability Affects Hypothesis Testing (a) The means (represented by M) differ between the two groups, and there is little overlap in the distribution of scores. When this occurs, the groups are much more likely to be significantly different. (b) Even though the means differ, there is much overlap between the distributions of scores. It is unlikely that these two means would be significantly different.
How, then, would researchers know if the difference in scores is meaningful? “Meaningful” seems like a vague term; as we have already discussed, science requires precise definitions. In order to address this problem, psychologists
perform analyses that rely on the concept of statistical significance.
Working the Scientific Literacy Model Statistical Significance
Statistical significance is a concept that implies that the means of the groups are farther apart than you would expect them to be by random chance alone. It was first proposed in 1925 by Ronald Fisher, an English statistician working at an agricultural research station east of London (U.K.). Statistical significance quickly became a key component of research in many disciplines. However, it has also been a source of some
surprisingly intense arguments (Cohen, 1994).
What do we know about statistical significance? Statistical significance testing is based on the researcher making
two hypotheses. The null hypothesis assumes that any differences between groups (or conditions) are due to chance. The experimental hypothesis assumes that any differences are due to a variable controlled by the experimenter. The goal of researchers is to find differences between groups that are so large that it is virtually impossible for the null hypothesis to be true; in other words, they are not due to chance. The probability
of the results being due to chance is known as a p-value. Lower p-values (e.g., p = 0.01 as opposed to p = 0.45) indicate a decreased likelihood that your results were a fluke, and therefore an increased likelihood that you had a great idea and designed a good experiment.
So, how do we find the p-value? The specific formulas used for these calculations will vary according to how the experiment is set up. But, they all involve a measure of central tendency (usually the mean) and a measure of variability (usually the standard deviation). These numbers are then used in statistical
tests that will produce a p-value.
What can science tell us about statistical significance? When Fisher first presented the idea of significance testing, he noted that scientists needed to establish a fairly conservative threshold for rejecting the null hypothesis (i.e., for deciding that the results were significant). He correctly thought that if it were quite easy for researchers to find a significant result, it would increase the likelihood that results labelled as being significant were actually due to chance. If enough of these false positives occurred, then the entire idea of significance would soon become meaningless. Fisher therefore recommended that researchers
use p < 0.05 as the cut-off point (this value was consistent with
earlier statistical techniques, so his decision was likely an attempt
to compromise with other statisticians; Stigler, 2008). If a p-value were less than 0.05, then there was less than a 5% chance that
the results were due to chance. This p-value quickly became the standard in a number of fields, including psychology.
Of course, just because a particular value is widely accepted does not mean that scientists can stop using their critical thinking skills. Sometimes the consequences of having a false positive are quite severe, as in the case of testing new medicines for a disease. It would be tragic to make claims about a wonder drug only to find out that the results were due to a chance result that could not be reproduced. In such cases, researchers sometimes
use an even more conservative p-value, such as requiring results to be less than 0.01 (i.e., p < 0.01).
It is also worth noting that when testing small sample sizes, it is difficult for the results to reach significance. But, some types of research, such as studies of rare brain-damaged patients, have a limited number of potential participants. It therefore becomes more difficult to detect statistically significant differences in these studies despite the fact that the groups do appear to differ when
you look at graphs of the data (Bezeau & Graves, 2001). In these cases, significance testing might not be the best statistical tool for analyzing the data. Luckily, significance testing is not the only technique available.
Can we critically evaluate the use of statistical significance testing in research? Although significance testing has been a potent tool for researchers in the social sciences for almost a century, it does
have some detractors. American psychologist Paul Meehl (1967) subtly described significance testing as “a potent but sterile intellectual rake who leaves in his merry path a long train of
ravished maidens but no viable scientific offspring” (p. 265).
Although this description may be a touch dramatic, there are at least two concerns related to significance testing. The first is the problem of multiple comparisons. If a “fluke” result can occur approximately 5% of the time, the more tests you perform for your experiment, the greater the likelihood that one of them is due to chance. In order to cope with this problem, researchers generally
use a stricter acceptable p-value; as the number of comparisons increases, researchers decrease the p-value (i.e., make it more conservative). This makes it more difficult to produce significant results, but does help ensure that the results are not due to chance. A second problem is the fact that as you increase the number of participants in your study, it becomes easier to find significant effects. At first blush, this doesn’t seem like a valid concern. Having more participants means that you are sampling a larger portion of the population of interest. Isn’t that a good thing? The answer is yes, of course it is. But, if you sample thousands of people—as often happens in medical studies tracking potential lifestyle causes of diseases—extremely small differences will still be statistically significant. The media provides almost daily reports of different foods increasing or decreasing the risk of particular diseases. Before totally altering your lifestyle, it is best to look up the original report to see if the difference was large, or was simply due to the fact that the sample size was in the thousands.
As an alternative to significance testing, Jacob Cohen (1988) developed a technique known as power analysis, whose goal is to calculate effect sizes. Rather than saying that a difference is significant, which is essentially a yes–no decision, effect sizes tell the researcher whether the difference is statistically small or large. So, instead of an experiment supporting or disproving a theory, effect sizes allow the researcher to adjust how much they
believe that their hypothesis is true (Cohen, 1994).
Why is this relevant? Statistical significance gives psychology researchers a useful standard for deciding if the differences between groups (or experimental conditions) are meaningful. Having established criteria for deciding if an effect is significant is important, because it means that all researchers are using standardized tools. If different research groups were using different criteria for deciding that effects were “real,” then it would be nearly impossible for that research area to move forward—people would be speaking different languages. Significance testing makes sure that everyone is on the same page, statistically speaking. However, as noted above, there are alternative methods for examining data. Effect sizes are becoming commonplace in many areas of psychology; an increasing number of academic journals now
require researchers to calculate both statistical significance and effect sizes, thus giving readers an even more detailed picture of the data.
A final point is that, although statistical significance tells us that results are meaningful, there is still a possibility that the results were due to chance. It is only through replication—having other laboratories repeat the experiments and produce similar results—that we can become confident that a difference is meaningful. Many scientists now make their stimuli and data available to other researchers in order to encourage this process. This move toward openness and replication is itself quite significant.
Module 2.4b Quiz: Hypothesis Testing: Evaluating the Outcome of a Study
Understand . . .
1. A hypothesis test is conducted after an experiment to
A. determine whether the two groups in the study are exactly the same.
B. determine how well the two groups are correlated. C. see if the groups are significantly different, as opposed to being
different due to chance.
D. summarize the distribution using a single score.
Analyze . . .
2. Imagine an experiment where the mean of the experimental group is 50 and the mean of the control group is 40. Given that the two means are obviously different, is it still possible for a researcher to say that the two groups are not significantly different?
A. Yes, the two groups could overlap so much that the difference was not significant.
B. Yes, if the difference was not predicted by the hypothesis. C. No, because the two groups are so far apart that the difference
must be significant.
D. No, in statistics a difference of 10 points is just enough to be significant.
Module 2.4 Summary
central tendency
descriptive statistics
experimental hypothesis
frequency
hypothesis test
mean
median
Know . . . the key terminology of statistics.2.4a
mode
negatively skewed distribution
normal distribution
null hypothesis
positively skewed distribution
standard deviation
statistical significance
variability
Significance tests are statistics that tell us whether differences between groups or distributions are meaningful. For example, the averages of two groups being compared may be very different. However, how much variability there is among individuals within each of the groups will determine whether the averages are significantly different. In some cases, the averages of the two groups may be different, yet not statistically different because the groups overlap so much. This possibility explains why psychologists use significance tests—to test whether groups really are different from one another.
Take a look at Figure 2.15 , a histogram showing the grades from a quiz in a statistics course, and then answer the following questions.
1. What is the shape of this distribution? Normal, negatively skewed, or positively skewed?
2. What grade range is the mode for this class? 3. How many people earned a grade in the “B” range (between 80 and 89)?
Understand . . . how and why psychologists use significance tests.2.4b
Apply . . . your knowledge to interpret the most frequently used types of graphs.
2.4c
Figure 2.15 Application Activity
Although the mean is the most commonly used measure of central tendency, it is not always the best method for describing a set of data. For example, incomes are positively skewed. Suppose one politician claims the mean income level is $40 000, while the other claims that the median income level is $25 000. Which politician is giving the more representative measure? It would seem that the median would be a more representative statistic because it is not overly influenced by extremely high scores.
Analyze . . . the choice of central tendency statistics based on the shape of the distribution.
2.4d
Chapter 3 Biological Psychology
3.1 Genetic and Evolutionary Perspectives on Behaviour Heredity and Behaviour 73
Module 3.1a Quiz 79
Evolutionary Insights into Human Behaviour 79
Working the Scientific Literacy Model: Hunters and Gatherers: Men, Women, and Spatial Memory 81
Module 3.1b Quiz 86
Module 3.1 Summary 86
3.2 How the Nervous System Works: Cells and Neurotransmitters Neural Communication 89
Module 3.2a Quiz 93
The Chemical Messengers: Neurotransmitters and Hormones 93
Working the Scientific Literacy Model: Testosterone and Aggression 97
Module 3.2b Quiz 99
Module 3.2 Summary 100
3.3 Structure and Organization of the Nervous System Divisions of the Nervous System 102
Module 3.3a Quiz 104
The Brain and Its Structures 104
Working the Scientific Literacy Model: Neuroplasticity and Recovery from Brain Injury 113
Module 3.3b Quiz 114
Module 3.3 Summary 115
3.4 Windows to the Brain: Measuring and Observing Brain Activity Insights from Brain Damage 117
Module 3.4a Quiz 118
Structural and Functional Neuroimaging 119
Working the Scientific Literacy Model: Functional MRI and Behaviour 122
Module 3.4b Quiz 123
Module 3.4 Summary 124
Module 3.1 Genetic and Evolutionary Perspectives on Behaviour
Roberto A Sanchez/E+/Getty Images
Learning Objectives
Know . . . the key terminology related to genes, heredity, and evolutionary psychology. Understand . . . how twin and adoption studies reveal relationships between genes and behaviour.
3.1a
3.1b
Psychologist Martie Haselton has given new meaning to the phrase dress for success. She is not talking about professional advancement, however; rather, she is referring to success in attracting a mate. Dr. Haselton is an evolutionary psychologist—she studies how human behaviour has evolved to solve problems that relate to survival and reproductive success. As part of her work, she has discovered that the clothes people choose are related to sexual motivation in some subtle ways.
In one project, Dr. Haselton and her colleagues invited female volunteers to the laboratory to participate in a study about personality, sexuality, and health. The young women were not given any specific directions about what to wear and during their visit to the laboratory they agreed to be photographed. Later, male and female volunteers viewed the photographs to judge whether they thought the women in the photos had dressed to look attractive. It turns out that women were rated as having dressed more attractively when they were in their peak level of fertility of
the menstrual cycle (Durante et al., 2008; Haselton et al., 2007). The researchers suggested that wearing such clothing during the fertile phase of the menstrual cycle was an attempt to be noticed by a potential mate (although the women in the study might disagree).
Of course, evolutionary psychologists are quick to point out that females are not alone in “signalling” their receptiveness for sexual activity. Males provide numerous—if not more obvious—examples. Indeed, body building, flaunting material assets, and other public displays of strength and status are common male strategies for attracting mates. Researchers must ask themselves this question: Is this behaviour just a coincidence? Or is this how the evolutionary forces that allowed our species to survive for hundreds of thousands of years are influencing our behaviour in the
Apply . . . your knowledge of genes and behaviour to hypothesize why a trait might be adaptive. Analyze . . . claims that scientists have located a specific gene that controls a single trait or behaviour. Analyze . . . explanations for cognitive gender differences that are rooted in genetics.
3.1c
3.1d
3.1e
modern world? Evolutionary psychologists like Dr. Haselton are building evidence to argue that how we dress and how we send many other signals can be explained by evolutionary principles, a topic we explore in this module.
Focus Questions
1. How is human behaviour influenced by genetic factors? 2. How has evolution played a role in modern-day human
behaviour?
A question that underlies a great deal of psychological inquiry is “Why do we behave the way we do?” In some situations, you might be tempted to say that your behaviour was a reaction to someone else or to the situation that you were
in. In others, you might say that you interpreted a situation in a particular way, and that led to a particular response. You might also say that you just reacted “naturally,” which implies that your behaviour is sometimes hard-wired. According to the biopsychosocial model of psychology, all three explanations can be valid in some situations. Therefore, to fully understand why you behave the way you do, it is necessary to understand the forces that influence each of these factors that affect our behaviour. In the current module, we will focus on genetic and evolutionary explanations; however, it is important to remember that almost everything you do—or anyone else does—is due to biological, cognitive (psychological), and social factors.
Heredity and Behaviour
Examples of genetic influences on physical traits easily come to mind because we tend to share our eye colour, facial characteristics, stature, and skin colouration with our parents. But research has made it clear that behaviours are influenced by genes just as physical characteristics are; indeed, the two are
often related. Genetics has an influence on the brain, just as it has an influence on eye colour, and changes in brain functions lead to changes in behaviour. Therefore, although a discussion of genetics may seem unrelated to how you think or feel, the work of genes—both during development and during everyday life—has a dramatic effect on your behaviour.
The Genetic Code
Given that genetics can influence so many aspects of our lives, it is important to review some of this field’s basic concepts. Our genetic code isn’t hidden in the darkest corners of our brains. Instead, it is found in the nucleus of most of the billions of cells in the human body. This genetic material is organized into genes , the basic units of heredity; genes are responsible for guiding the process of creating the proteins that make up our physical structures and regulate development and physiological processes throughout the lifespan.
Genes are composed of segments of DNA (deoxyribonucleic acid) , a molecule formed in a double-helix shape that contains four nucleotides: adenine, cytosine, guanine, and thymine (see Figure 3.1 ). These nucleotides are typically abbreviated using the first letter of their names—A, C, G, and T. Each gene is a unique combination of these four nucleotides. For example, a gene may consist of sequences of nucleotides such as AGCCTAATCGATGCGCCA . . . and so on. These sequences of nucleotides (i.e., these genes) represent the instructions or code used to create the thousands of different proteins found in the human body. These proteins specify which types of molecules to produce and when to produce them. Genes also contain information about which environmental factors might influence whether the genes become active (“expressed”) or not. Together, this information makes up an individual’s genotype , the genetic makeup of an organism—the unique set of genes that comprise that individual’s genetic code.
Figure 3.1 DNA Molecules The nucleus of a cell contains copies of each chromosome. Chromosomes are composed of the genes arranged in the familiar double helix—a long strand of DNA molecules. Source: Lilienfeld, Scott O.; Lynn, Steven J; Namy, Laura L.; Woolf, Nancy J., Psychology: From Inquiry To Understanding,
2nd Ed., ©2011. Reprinted And Electronically Reproduced By Permission Of Pearson Education, Inc., New York, NY.
The result is an organism’s phenotype , the physical traits and behavioural characteristics that show genetic variation, such as eye colour, the shape and size of facial features, intelligence, and even personality. This phenotype develops because of differences in the nucleotide sequencing of A, C, G, and T, as well as through interactions with the environment.
Genes are organized in pairs along chromosomes , structures in the cellular nucleus that are lined with all of the genes an individual inherits. Humans have approximately 20 000–25 000 genes distributed across 23 pairs of
chromosomes, half contributed by the mother and half by the father (see Figure 3.2 ). (In some cases, an extra chromosome—a trisomy—is present, thus altering the genetic make-up as well as the phenotype of the individual. The most common chromosomal abnormality is Down Syndrome, a trisomy on the 21st chromosome, although many others exist.)
Figure 3.2 Human Chromosomes Human DNA is aligned along 23 paired chromosomes. Numbers 1–22 are common to both males and females. Chromosome 23 is sex linked, with males having the XY pattern and females the XX pattern. somersault1824/Shutterstock
If two corresponding genes at a given location on a pair of chromosomes are the
same, they are referred to as homozygous. If the two genes differ, they are heterozygous. Whether a trait is expressed depends on which combination of pairs is inherited. In order to make these abstract concepts more concrete, let’s look at an example that affects everyone: our sense of taste. Researchers have
shown that the ability to taste a very bitter substance called phenylthiocarbamide (PTC) is based on which combination of genes we inherit from either parent (the
genotype; see Figure 3.3 ). The test for whether you can taste PTC (the phenotype) is typically performed by placing a small tab of paper soaked in the substance on the tongue. Some people are “tasters”; they cringe at the bitter taste of PTC. Others—the “non-tasters”—cannot taste anything other than the
tab of paper. Those who are tasters inherited at least one copy of the dominant gene for tasting (abbreviated capital “T”) from either parent. People can also
inherit a recessive copy of this gene (t). Those who report tasting PTC are either homozygous dominant (TT) or heterozygous (Tt). Non-tasters are homozygous recessive (tt)—they inherited a recessive copy of the gene from both parents. Those who are tasters may find foods such as Brussels sprouts, cauliflower, and cabbage to be unpleasant, or at least too bitter to eat, as these foods contain PTC.
Figure 3.3 Genetic Inheritance Whether someone tastes the bitter compound PTC depends on which copies of
the gene he or she inherits. Shown here is the statistically probable outcome of two heterozygous (Tt) parents with four children. Source: Data from Influence of life stress on depression: Moderation by a polymorphism in the 5-HTT gene by Caspi, A., et
al., Science, 301, 386–389. 2003.
In this example, the genotype represents what was inherited (i.e., tt, Tt, or TT). The phenotype represents the physical and behavioural manifestation of that genotype that occurs through interactions with the environment (i.e., being a
taster or a non-taster for this specific sensation—note that non-tasters in this context might have normal responses to other tastes). As you will see, this attempt to link genes to behaviour is a rapidly growing area of research in psychology and medicine.
As geneticists continue to unravel different parts of the entire human genome, it is becoming increasingly clear that simple examples like the taster/non-taster trait provide only a glimpse of what knowledge might soon be available to us. Indeed, in recent years, an entirely new field has developed that attempts to identify the genes involved with specific behaviours: behavioural genomics.
Behavioural Genomics: The Molecular Approach
Although researchers have suggested that genetics play a role in many abilities
and behaviours, until recently it has not been possible to determine how traits are inherited. To make this determination, researchers now go straight to the
source of genetic influence—to the genes themselves. Behavioural genomics
is the study of DNA and the ways in which specific genes are related to behaviour. The technology supporting behavioural genomics is relatively new, but once it became available, researchers initiated a massive effort to identify the
components of the entire human genome—the Human Genome Project. This project, which was completed in 2003, resulted in the identification of approximately 20 000–25 000 genes. Imagine the undertaking: determining the sequences of the billions of A, C, G, and T nucleotides making up the genes, including where each gene begins and ends, and how they are all arranged on the chromosomes. The Human Genome Project itself did not directly provide a
cure for a disease or an understanding of any particular behaviour. Instead, it has led to an abundance of new techniques and information about where genes
are located, and it opened the door for an entirely new era of research (Plomin & Crabbe, 2000). Indeed, researchers can now compare the genotypes of different groups of people (e.g., depressed and non-depressed individuals) to look for differences that might shed light on the cause of different conditions. For example, in 1997, researchers identified a gene that was found in families prone to Parkinson’s disease, a neurological disorder involving tremors and difficulties
making movements (Polymeropoulos et al., 1997). Since then, a number of mutations that are linked to Parkinson’s have been identified including SNCA, Parkin, PINK1, DJ1, and LRRK2 (Klein & Schlossmacher, 2006).
However, we must be cautious in our interpretation of such discoveries. Like any approach to answering scientific questions, behavioural genomic research does have its limitations. For example, although a single gene has been identified as a risk factor for Alzheimer’s disease, not everyone who inherits it develops the disease. The same is true for many other conditions. This is a common misconception about genes and behaviour.
Behavioural Genetics: Twin and Adoption Studies
Although behavioural genomics studies can identify genes related to behaviours, they don’t tell us how sensitive these genes are to environmental factors like stress, family life, or socioeconomic status. These questions are examined using
a complementary field known as behavioural genetics , the study of how genes and the environment influence behaviour. Behavioural genetic methods applied to humans typically involve comparing people of different levels of relatedness, such as parents and their offspring, siblings, and unrelated individuals, and measuring resemblances for a specific trait of interest. The group that has provided the most insight into the genetic effects on behaviour is twins.
Myths in Mind Single Genes and Behaviour
Enter the phrase “scientists find the gene for” into your favourite Internet search engine and you will wind up with more hits than you would ever have time to sift through. Although it is true that behaviour, both normal
and abnormal, can be traced to individual genes, typically combinations of genes influence behaviour. When it comes to complex characteristics such as personality or disorders like Alzheimer’s disease and schizophrenia, there is very little chance that any single gene could be
responsible for them (Duan et al., 2010). A person’s intelligence and his predisposition to alcoholism, anxiety, shyness, and depression are all examples of traits and conditions with genetic links, but they all involve multiple genes.
Another misconception is that a single gene can affect only one trait. In reality, the discovery that a particular gene predisposes someone to
alcoholism does not mean that this gene is only relevant to alcohol addiction; it most likely affects other traits as well. For example, genes that are present in people who abuse alcohol are also more likely to be found in individuals who have a history of other problems such as additional forms of drug dependence and antisocial behaviour. In other words, these different behaviours may share some characteristics, and
the gene may be related to that “shared genetic liability” (Dick, 2007).
So, when you encounter a headline beginning “Scientists find gene for . . .,” don’t read it as “Scientists found THE gene for. . . .” It is likely that the news describes the work of scientists who found another one of the many genes involved in a disorder or, in the case of Alzheimer’s disease, a
gene that is a risk factor and not the sole cause.
Twins present an amazing opportunity to conduct natural experiments on how genes influence behaviour. One method commonly used in twin studies involves
comparing identical and fraternal twins. Monozygotic twins come from a single ovum (egg), which makes them genetically identical (almost 100% genetic similarity). An ideal comparison group, dizygotic twins (fraternal twins) come from two separate eggs fertilized by two different sperm cells that share the same womb; these twins have approximately 50% of their genetics in common. Researchers around the world have studied the genetic and environmental
bases of behaviour by comparing monozygotic twins, dizygotic twins, non-twin siblings, and unrelated individuals. The assumption underlying these studies is that if a trait is genetically determined, then individuals with a greater genetic similarity will also have a greater similarity for that trait. Researchers have also
examined these different groups in longitudinal studies , studies that follow the same individuals for many years, often decades. For example, one twin study determined the degree to which anxiety and depression are influenced by genetics in children and adolescents. It was far more likely for both monozygotic twins to show anxiety or depressive symptoms than for both dizygotic twins to do so; thus, these results demonstrate the influential role that genes play in
depression (Boomsma et al., 2005).
Behavioural geneticists use twin studies to calculate heritability —a statistic, expressed as a number between zero and one, that represents the degree to which genetic differences between individuals contribute to individual differences in a behaviour or trait found in a population. A heritability of 0 means that genes do not contribute to individual differences in a trait, whereas a heritability of 1.0 indicates that genes account for all individual differences in a trait. It is important
to point out that heritability scores do not simply reflect how much genetics contributes to the trait itself. Rather, heritability scores tell us the degree to which
genetics explain differences between people with that trait. So, the heritability of having a tongue is 0 because we all have a tongue (i.e., there are no differences to explain). But, the taste sensitivity of that tongue differs based on genetics and on the foods you were exposed to while growing up. Taste will therefore have a heritability score somewhere between 0 and 1.
Identical twins are genetically the same, whereas fraternal twins are no more closely related than full siblings from different pregnancies. However, fraternal twins do share much of the same prenatal and postnatal environment if they are reared together. Researchers assume, then, that if the identical twins are more similar on a given trait than fraternal twins, this difference is due to genetics. But,
it is possible that identical twins are treated more similarly than are fraternal twins (so they have more nature and more nurture in common). How would this affect your interpretation of twin studies? Top: Creatas Images/Thinkstock/Getty Images bottom: Martin Harvey/Alamy Stock Photo
Heritability estimates are rarely, if ever, an extreme value of 0 or 1.0. Instead, genetics and environmental influences (e.g., family life) both account for some of the differences in our behaviour. For instance, the estimated heritability found in the study on depression and anxiety described earlier was approximately .76 for
3-year-old identical twin pairs (Boomsma et al., 2005). This tells us that 76% of individual differences in depression and anxiety at age 3 can be attributed to genetic factors in the population that was studied. However, depression and anxiety can also obviously be influenced by our different life experiences. It
should not be a surprise to learn that heritability estimates for these behaviours
change as we age. In the Boomsma and colleagues (2005) study, the heritability of anxiety and depression went from .76 at age 3 to .48 at age 12 for the identical twin pairs. This change is likely due to the fact that an individual’s peer group and social life can have a larger effect on one’s emotional well-being during the “tween” and teen-aged years than they would during the toddler years (when family is the main non-genetic factor). This finding should serve as a reminder that the environment never stops interacting with genes.
Behavioural geneticists also study adopted children to estimate genetic
contributions to behaviour. The adopted family represents the nurture side of the continuum, whereas the biological family represents the nature side. On the one hand, if adopted children are more like their biological parents than their adoptive parents on measures of traits such as personality and intelligence, we might conclude that these traits have a strong genetic component. On the other hand, if
the children are more like their adoptive, genetically unrelated parents, a strong case can be made that environmental factors outweigh the biological predispositions. Interestingly, young adopted children are more similar to their adoptive parents in intelligence levels than they are to their biological parents. By the time they reach 16 years, however, adopted adolescents score more similarly to their biological parents than their adoptive parents in tests of intelligence, suggesting that some genes related to intelligence do not exert their
influence(s) on behaviour until later on in development (Plomin et al., 1997). Compare this finding to that from the study described in the preceding paragraphs: For intelligence, heritability seems to increase with age, whereas the opposite is true for depression and anxiety.
Although heritability estimates provide important information about the different effects of “nature” and “nurture” on different behaviours, we have to be cautious about how we generalize this information. Heritability estimates are limited to the population being studied. We cannot make definitive statements about the heritability of depression in Brazil based on the results of a study conducted in Canada (although we can use the Canadian study to generate hypotheses about
what we think we would find if we performed the same study in Brazil). This is because any estimate of heritability is affected by (1) the amount of genetic
variability within the group being studied and (2) the variability in the environments that members of that group might be exposed to. For example, people from an isolated village in the Amazon rain forest would likely not have much variability in their genetics because they would not have a lot of contact with outside groups. In contrast, many Canadians have diverse genetic backgrounds. Therefore, the individual differences in the Amazon village would most likely be due to environmental factors; this would lead to a lower heritability estimate for this group. This is not to say that one way of life is better than another—but we need to be mindful of these differences in genetic and environmental variability so that we don’t incorrectly assume that North American genetic studies generalize to the entire world.
Heritability estimates can vary with age. The heritability of depression and anxiety decreases with age whereas the heritability of intelligence increases with age. Ale Ventura/PhotoAlto Agency RF Collections/Getty Images;
Steve Debenport/E+/Getty Images.
Gene Expression and Behaviour
The fact that heritability estimates change over time based on our different experiences shows us that nature and nurture interact to produce behaviour.
What these estimates don’t tell us is how that interaction occurs in our bodies and brains. Recent advances in our understanding of genetics and the human genome have begun to shed light on some of these relationships.
Almost every cell in our bodies contains the same genes, the basic unit of heredity. But, only some of these genes are active, leading to the production of proteins (or other gene products like ribosomal RNA); the other genes are inactive and do not influence protein production. Of the approximately 20 000–25 000 genes in the human genome, between 6000 and 7000 are active in the human brain. These genes influence the development of different brain structures, the production of chemicals that allow brain cells to communicate with each other, and the refinement of connections between cells that allow large-
scale brain networks to form (French & Pavlidis, 2011). The expression of these genes is influenced by genetics, environmental factors that influence the chemical make-up of the cells, or a combination of the two.
If some genes fail to be activated (or expressed) properly, people may be at a greater risk for developing brain-related disorders. For example, Dan Geschwind
and colleagues (2011) found that children with autism had less gene expression in several regions of the brain. This decrease in gene expression was linked to problems with language, decision making, and understanding other people’s emotions. Researchers are now investigating ways to alter gene expression in order to treat different brain disorders such as Parkinson’s disease and Alzheimer’s disease.
Importantly, gene expression is a lifelong process (Champagne, 2010). Factors such as diet, stress level, and sleep can influence whether genes are turned on
or off. This study of changes in gene expression that occur as a result of experience and that do not alter the genetic code is known as epigenetics . Studies with mice have shown that increased maternal licking and grooming (the
rodent equivalent of cuddling) led to an increase in the expression of the GR gene in the hippocampus (Francis et al., 1999). This gene influences stress responses and can affect how well (or poorly) individuals respond to novel
situations. Low levels of licking and grooming led to decreased GR expression and a larger stress response (Weaver et al., 2004). Similar effects have been observed in humans. Decreased GR expression was noted in a recent study of childhood abuse victims who later committed suicide, demonstrating the power of these gene–environment interactions. Indeed, there is increasing evidence
that epigenetics plays a role in a number of psychological disorders (Labrie et
al., 2012).
Epigenetics research suggests that grooming not only influences social bonds, but can also affect the expression of genes. Eric Isselee/123RF
The fact that gene expression can be influenced by the environment is an
example of the social part of the biopsychosocial model of behaviour discussed throughout this textbook—nurture can influence nature. Some researchers have speculated that gene expression could also be influenced by the culture in which one lives. Culture, family, and other social bonds all influence how we respond—
both psychologically and biologically—to different situations and stimuli. Therefore, these sociocultural factors have the potential to influence whether or
not certain genes are expressed (Richardson & Boyd, 2005).
Although many of the changes in gene expression do not alter the genetic code,
some do get passed on from generation to generation. Chemically induced changes in the expression of genes in the amygdala and hippocampus— structures related to emotion and memory—have been shown to influence
anxiety-related behaviours for three generations of rats (Skinner et al., 2008)! Licking and grooming have similarly been shown to affect both gene expression
and maternal behaviours across three generations (Champagne et al., 2003). Therefore, how you behave now could have lasting effects on the genetic codes of your grandchildren.
Module 3.1a Quiz:
Heredity and Behaviour
Know . . . 1. The chemical units that provide instructions on how specific proteins are
to be produced are called . A. chromosomes B. genes C. genomic D. autosomes
Understand . . . 2. A person who is homozygous for a trait
A. always has two dominant copies of a gene. B. always has two recessive copies of a gene. C. has identical copies of the gene. D. has different copies of the gene.
Apply . . . 3. If a researcher wanted to identify how someone’s life experiences could
affect the expression of specific genes and thus put that person at risk for developing depression, she would most likely use which of the following methods?
A. Behavioural genetics B. A comparison of monozygotic and dizygotic twins in different
parts of the world
C. An adoption study D. Epigenetics
Analyze . . . 4. Imagine you hear a report about a heritability study that claims trait X is
“50% genetic.” Which of the following is a more accurate way of stating this?
A. Fifty percent of individual differences of trait X within a population are due to genetic factors.
B. Only half of a population has the trait. C. Half of that trait is dependent upon genetics. D. More than 50% of similarities of trait X within a population are due
to genetic factors.
Knowing about genes gives us some idea as to why individuals differ. But, they don’t tell the whole story. We also need to examine how some traits or physical characteristics enhanced our ancestors’ ability to survive and to pass on these genes to future generations, including us.
Evolutionary Insights into Human Behaviour
On December 27, 1831, a young Charles Darwin began his voyage on the HMS
Beagle, a ship tasked to survey the coastline of South America. Darwin’s (self- funded) position was to act as a naturalist, examining the wildlife, flora, and geology of the areas the ship visited. This five-year voyage, which included additional stops in Australia and South Africa, exposed Darwin to a vast number of species and eventually led to him developing one of the most important (and controversial) theories in human history.
While travelling among the different Galápagos Islands (900 km west of modern- day Ecuador), Darwin made a number of important observations. First, he
identified fossils from several extinct species. This discovery highlighted the fact that not all species were able to survive in this environment. But, some species
did have characteristics that allowed them to flourish. Second, he noticed small differences between the same species of birds and turtles living on different islands. These differences meshed quite well with the particular environments the animals lived in. From these observations, Darwin deduced that the species that were a good “fit” for their environment survived while other species did not.
The challenge for Darwin was to find a way to explain this observation. Looking at the individual animals, he saw a number of small differences similar to the differences you’d see between people in your classroom. Some individuals had traits that would enhance their ability to survive such as speed and strength. These individuals would likely get enough food to eat and would be able to find mates. Individuals without these traits would be less likely to mate. If this pattern continued, there would be more offspring with the favourable traits (strength and speed) than without those characteristics. Darwin developed these observations
into his theory of natural selection , the process by which favourable traits become increasingly common in a population of interbreeding individuals, while traits that are unfavourable become less common (see Figure 3.4 ).
Figure 3.4 How Traits Evolve
Evolution through natural selection requires both that a trait be heritable (i.e., be passed down through reproductive means) and that certain individuals within a breeding population have a reproductive advantage for having the trait. © Pearson Education, Inc.
Although genes had not yet been discovered, they lay at the heart of Darwin’s theories. When animals mate, each parent provides half of the offspring’s genetic material. The genes of some animals would combine in such a way to produce traits favourable to that setting (i.e., they were adaptive) and the genes of other animals would combine in less useful ways. Because the adaptive or fit animals were more likely to survive and reproduce, these traits—and therefore these genes—would be more likely to be passed on to future generations. This process
is known as evolution , the change in the frequency of genes occurring in an interbreeding population over generations.
Evolution is not a continuous process, however. If an animal is perfectly adapted for its environment, then there is no evolutionary pressure for change to occur. Let’s call that version 1.0 of the animal. But what if some pressure such as a change in the climate or the availability of food occurs? In this case, a given trait might be advantageous in that specific environment and specific point in time. Individuals with that trait would survive; those without it might not. Through natural selection, this trait would eventually become common within that species and may in the future serve other functions and interact with the environment in novel ways. Let’s call this version 2.0 of the animal. When the next environmental pressure occurred, a subset of version 2.0 of the animal would possess traits to make them more evolutionarily fit than the other version 2.0 animals. This subset would survive and reproduce, eventually leading to version 3.0 of the animal. While this description is over-simplified, it does illustrate a key point: Any modern species is based upon version after version after version of species that were fit for their particular environment and time.
Evolutionary Psychology
Darwin suggested that humans followed a similar evolutionary path, changing
and adapting over the course of thousands of generations. He was correct— there is now fossil evidence showing that many branches of our ancestral family tree died out, likely because their physical and mental characteristics were not fit
for their environment. What separated our species, Homo sapiens, from other animals was that our ancestors had (1) larger frontal lobes than other species
(see Figure 3.5 ) and (2) had brains with more folds, thus allowing for more brain cells to be squeezed inside their skulls. These adaptations allowed our ancestors to form plans, solve problems, make quick decisions, and control our
attention and actions (Stuss, 2011). As a result, they were able to think their way out of different challenges such as changes to the environment or food supply. They also were able to communicate this knowledge using symbolic representations of objects and ideas, as shown in carvings and cave paintings
(Chase & Dibble, 1987); this allowed them to pass on knowledge from generation to generation, just as they passed on their genes.
Figure 3.5 The Prefrontal Cortex in Different Species Human brains have much more space dedicated to the frontal lobes, particularly the prefrontal cortex, than any other species. This brain area is related to many of our higher cognitive functions like problem solving and decision making. Source: Based on Fuster, J.M., The Prefrontal Cortex: Anatomy, Physiology, and Neuropsychology of the Frontal Lobe, 2nd
edition. New York: Raven Press, 1989.
Although all of this makes intuitive sense to us now, in the second half of the 19th century, Darwin’s theories met with considerable opposition. By stating that animals evolved over time based on environmental pressures, Darwin was challenging the view that animals had been created “as is” by an all-knowing deity. By stating that all humans had common ancestors that evolved into modern people, Darwin was demonstrating that all people—regardless of ethnicity or economic status—were essentially equal. This view was not popular in Victorian England, where the aristocracy looked at the working class with disdain and where the English felt that they had the right to colonize non- Caucasian countries such as India and parts of Africa. However, over time, Darwin’s ideas became accepted in almost all scientific circles. Today, a modern
branch of psychology known as evolutionary psychology attempts to explain human behaviours based on the beneficial function(s) they may have served in our species’ development.
Working the Scientific Literacy Model Hunters and Gatherers: Men, Women, and Spatial Memory
Evolutionary psychologists are now attempting to link evolutionarily useful behaviours that were performed by our ancestors with our own modern cognitive abilities. One notable area of investigation is the study of differences in male and female cognitive abilities.
What do we know about the sex differences in spatial memory? Evolutionary psychologists hypothesize that male and female brains will differ in some ways because males and females have had to solve a different set of problems in order to survive and reproduce. Specifically, due to their size and strength, males
were traditionally responsible for tracking and killing animals. These responsibilities would require males to travel over long distances without becoming lost. Females, due to the fact that they cared for children, remained closer to home and instead spent time foraging for berries and edible plants. Males’ responsibilities would favour individuals with good spatial skills; females’ responsibilities would favour memory for the location of objects (e.g., plants). The question, then, is whether the abilities that were adaptive for males and females over the course of our
species’ evolution are still present today (Silverman & Eals, 1992). Put another way, will modern males and females show performance differences on different tests of spatial abilities that are consistent with their historic roles as hunter (males) and
gatherer (females)? This is the logic behind the hunter-gatherer theory , which explicitly links performance on specific tasks to the different roles performed by males and females over the course of our evolutionary history.
How can science test sex differences and spatial memory? One sex difference that has been reported involves solving the mental rotation task. In this task, participants see a three- dimensional image. They are then shown several additional figures, one of which is a rotated version of the original image. The task is to identify the rotated figure as quickly and as accurately as possible. To make this task more concrete, try the
examples shown in Figure 3.6 .
Figure 3.6 Mental Rotation Task
Instructions: Take a close look at standard object #1. One of the three objects to the right of it is the same. Which one matches the standard? Repeat this with standard object #2 and the three comparison shapes to the right of it. Source: Lilienfeld, Scott O.; Lynn, Steven J; Namy, Laura L.; Woolf, Nancy J., Psychology: From
Inquiry to Understanding, 2nd Ed., ©2011, pp.344. Reprinted and Electronically reproduced by
permission of Pearson Education, Inc., New York, NY.
Research shows that males are generally able to perform this task more quickly than females, and with greater accuracy. A possible reason for this difference is that it is influenced by testosterone levels, which are typically higher in males. In fact, researchers have found that males with high testosterone levels were better at solving the task than males with low levels of
testosterone (Hooven et al., 2004). These studies suggests that there is a biological (and possibly evolutionary) explanation for the male advantage in performing this specific task.
Answers: 1. A; 2. B
Researchers have also found that females outperform males on different types of spatial tasks, specifically, tests involving
memory for the spatial location of objects (see Figure 3.7 ). In addition to laboratory-based tests, females outperformed men in experiments conducted in natural settings. In one study, women were able to locate specific plants more quickly than were men
and also made fewer mistakes in identifying them (New et al., 2007). This advantage may be due to females’ evolutionary role as a gatherer rather than as a hunter.
Figure 3.7 Spatial Location Memory Task
In this task, participants are asked to remember the location of specific items. Source: Republished with permission of Springer Science, from The Hunter-Gatherer Theory of Sex
Difference in Spatial Abilities: Data from 40 Countries, Irwin Silverman; Jean Choi; Michael Peters,
36, and 2007; permission conveyed through Copyright Clearance Center, Inc.
Can we critically evaluate this evidence? Although sex differences on different forms of spatial abilities
have been observed in a number of conditions (Voyer et al., 2004), there are some points worth considering. The first is that an overall sex difference does not mean that all males will be better at mental-rotation tasks than all females. There is a great deal of variability within each group on almost all cognitive and perceptual abilities. It is better to think of the sex differences in mental rotation and spatial location tasks in terms of overlapping curves whose average scores differ slightly rather than as one sex being superior to the other on that cognitive ability. A second issue is whether these differences occur across cultures. Although the roles of hunter and gatherer were likely present in most ancient cultures due to females’ need to be with young children, there are much greater differences in modern cultures. Some cultures have very strict sex roles that could influence the education and abilities of males and females. Would culture influence the size of the sex differences on tests like the mental- rotation task? As it turns out, the answer is no. The male advantage in the mental-rotation task has been observed across 40 different countries, suggesting that the finding is not restricted
to Canadian universities (Silverman et al., 2007). However, although these results support the hypothesis that the differences on tasks like the mental-rotation task are biological in origin, they
do not necessarily show that these differences are due to the evolutionary roles of hunter and gatherer. Additionally, while evolutionary psychology presents possible explanations, it is
more likely that they are only one of many factors influencing your behaviour. Remember the biopsychosocial model!
Why is this relevant? The hunter-gatherer hypothesis shows us that the behaviours of our ancestors might have had an effect on the abilities of modern humans. The physical and cognitive characteristics that made males evolutionarily fit likely differed slightly from the characteristics that benefited females. Males with good spatial skills and females with good location memory would have been
more successful than individuals who did not have those abilities. But, while males and females differ on some skills, the differences are generally quite small, with many females outperforming males on spatial tasks. Therefore, it is important to be careful about over-interpreting the results of these studies.
Natural selection suggests that some traits make an individual more likely to survive and therefore to reproduce. The question is how do these individuals let others know that they possess these traits? In other words, how do they
convince someone to mate with them? According to Darwin (1871), certain traits or adaptations will have evolved to help some individuals increase their chances of mating while others do not. How this works varies from species to species.
Sexual Selection and Evolution
In some species, members of one sex (usually males) compete for access to the other sex (usually females). For instance, some deer and caribou literally lock
horns in violent fights known as rutting. The winner of the fight is much more likely to mate with females than is the loser. Similar examples occur in many
primate species. Here, a dominant male—often referred to as the alpha male— intimidates other males and is more likely to mate with multiple females than are
the subordinate males. These are examples of intrasexual selection , a situation in which members of the same sex compete in order to win the opportunity to mate with members of the opposite sex. Intrasexual selection is evolutionarily advantageous because the animals most likely to become dominant are the strongest and/or smartest, and therefore the most fit for that time and place. If this trend continues across many generations, the species as a whole will become stronger and smarter (i.e., more evolutionarily “fit”).
A second form of sexual selection is known as intersexual selection , a situation in which members of one sex select a mating partner based on their desirable traits. In the animal kingdom, we see numerous examples of males attempting to attract the attention of females. For instance, many male birds
display bright feathers and perform intricate dances or songs to attract females. This might seem cute, but this has a darker function as well. Brightly coloured birds must be fast and aware of their surroundings (i.e., evolutionarily fit). Otherwise, that glorious plumage, which also attracts predators, would turn them into someone’s lunch rather than into someone’s mate. Therefore, the brightly
coloured birds that do survive must have physical and mental characteristics that should be passed on to future generations.
Facial Symmetry and Attraction Which face do you prefer of these five? You likely chose the middle face because it has the highest level of symmetry. People can detect this quality without even having to study the faces very closely. The University of Western Australia
Humans also have characteristics that enhance mating success. On average, heterosexual women prefer men who are taller (6’0 or 1.83 m), with good
posture, and who are not very hairy (Buss, 2003; Dixson et al., 2010). Heterosexual men prefer women who are slightly shorter than them, have full lips, high cheekbones, and a small chin. A number of experiments have shown that people rate symmetrical faces as being more attractive than asymmetrical
faces (Gangestad et al., 1994; Rhodes, 2006). Overall, people tend to prefer partners who appear healthy. An evolutionary psychologist would suggest that such individuals would also be more likely to be fertile and to possess good genes.
Importantly, not all elements of intersexual selection are the gift (or curse) of our genes. Men often present cues that highlight their masculinity, such as wearing clothes that display their muscles. They also attempt to appear large and athletic, particularly when around potential mates. For example, if an attractive woman
walks by a group of men, they tend to stand up straight to appear taller and healthier, and thus more attractive (this makes for wonderful people-watching at bars). Evolutionary psychologists suggest that this behaviour is an attempt to appear more genetically fit than their competitors; doing so would suggest to potential mates that their offspring would be similarly fit. Women also attempt to highlight attractive elements of their physique. At the beginning of this module, you learned that women dress more attractively when they are ovulating. As
noted in the Biopsychosocial Perspectives box on page 84, some of these clothing selections might actually be tapping into other primal impulses.
Biopsychosocial Perspectives Sexual
Selection and the Colour Red Most of us have had the experience of seeing a woman in a red dress walk into a room and turn everyone’s head. A number of studies have found that the colour red has a powerful effect on people’s behaviour and judgments of beauty. For instance, when black-and-white photographs of women are presented on a red background, these women are rated as being more attractive than when the same images are presented on a
white background (Elliot & Niesta, 2008). Researchers in France have found that males tip waitresses more generously when the women are
wearing a red shirt (Guéguen & Jacob, 2012a), have a red ornament in their hair (Jacob et al., 2012), or are wearing red (rather than pink or brown) lipstick (Guéguen & Jacob, 2012b). So why does the colour red have these effects? This question has a one-word answer: SEX. Women who are wearing red clothes are perceived to be more interested in having sex than women wearing other colours. This perception occurs even when the same woman is shown in identical t-shirts whose colour
has been digitally altered (Guéguen, 2012); it is not affected by the attractiveness of the female model.
Of course, some of these results may be due to social factors. The colour red is related to sex in many cultures (e.g., “red light districts”). To test this hypothesis, researchers tested individuals in a remote village in
Burkina Faso (in Western Africa). Importantly, in this village, the colour red had negative associations—death, bad luck, and sickness—and no sexual connotations. The participants viewed black-and-white photographs of women surrounded by either a red or a blue border. Consistent with North American and European studies—and contrary to their cultural norms—the women with the red borders were rated as
being more attractive (Elliot et al., 2013).
Evolutionary psychologists are quick to point out that red is associated with sexual receptivity in many animals, including humans. Female baboons and chimpanzees—species that are evolutionarily close to humans—have redder chests and genitals when they are near ovulation
than at other times of their cycles (Deschner et al., 2004; Dixson, 1983). This blushing appears to be linked to estrogen levels, which open up the
blood vessels of these regions (Setchell & Wickings, 2004). In these species, males respond to the red swellings with copulation attempts
(Waitt et al., 2006). These researchers also found that male rhesus monkeys (Macaca mulatta) spent more time looking at red-enhanced photographs of female anogenital regions than at other images. In humans, sexual interest is associated with flushing in the face, neck, and
upper chest (Changizi, 2009). Anthropological research has shown that women have used lipstick and rouge to mimic these vascular changes (and thus appear more attractive to potential mates) for over 10 000
years (Low, 1979).
Of course, it is important to point out that women wearing red are not necessarily indicating their willingness to have sex! These data are trends across the population and do not predict individual people’s behaviour. But, it does show how evolutionary psychology can provide a new perspective on everyday behaviours.
Of course, there are other qualities we look for in a potential partner, particularly when it comes to long-term mates. But what are these qualities, and do
members of other cultures value similar characteristics? Buss (1989) conducted a survey of more than 10 000 people from 37 different cultures to discover what they most valued in a long-term partner. Across this broad sample, both men and
women agreed that love, kindness, commitment, character, and emotional maturity were important. However, there were some interesting differences. Women valued men with strong financial prospects, status, and good health whereas men placed a greater emphasis on physical beauty, youth, and other characteristics that relate to reproduction. Other investigators have found similar
sex differences (see Figure 3.8 ). Researchers in the United States showed yearbook photographs to heterosexual male and female research participants. Along with the photographs, participants were provided with information about each individual’s socioeconomic status (SES), a measure of their financial status. SES had a much greater effect on females’ willingness to enter
relationships with these individuals than it did for males (Townsend & Levy, 1990b). In a subsequent study, these researchers clothed the same models in outfits that implied high, medium, or low SES. Participants were asked to rate their willingness to engage in different types of relationships with this person ranging from “Coffee and conversation” to “Sex only” to “Marriage.” Clothing, the indicator of SES, had a much larger effect on females than males, particularly when the model was not physically attractive. Men were much more willing to engage in “Sex only” relationships regardless of SES or attractiveness
(Townsend & Levy, 1990a).
Figure 3.8 Sex Differences in the Minimum Acceptable Earning Level for Different Types of Relationships Females place a much higher value on economic stability than do males, particularly for long-term relationships. This result may be due to the fact that females can produce a limited number of offspring and therefore need to ensure that a mate has enough resources to ensure their survival. Evolutionary psychology is not necessarily romantic. Source: From Evolution, traits and the stages of human courtship: Qualifying the parental investment model, Journal of
Personality, 58, 97–116 by Douglas T. Kenrick, Edward K. Sadalla, Gary Groth, Melanie R. Trost. Copyright © 1990 John
Wiley & Sons, Inc. Reproduced with permission of John Wiley & Sons, Inc.
How can we explain this difference? According to evolutionary psychologists, this difference might be due to the resources required to raise offspring. Females have a limited number of eggs, and thus a finite number of opportunities to pass on their genes to another generation. If a female became pregnant and had a
baby, she would require resources to help raise the child, particularly when the child is quite young and it is difficult for the woman to bring in her own resources. Therefore, it would make sense that females would be attracted to males who can provide these resources; this sometimes means mating with someone who
is older and more established in life (Trivers, 1972). In contrast, men have a seemingly infinite amount of sperm and have fewer limits on the number of people they could theoretically impregnate. Given that their evolutionary impulse is to pass on their genes to as many offspring as possible, it makes sense for them to be attracted to young, healthy women who are likely able to reproduce
(Buss, 1989). Oddly, these motivations don’t appear in many love songs.
Module 3.1b Quiz:
Evolutionary Insights into Human Behaviour
Know . . . 1. For a trait to evolve, it must have a(n) basis.
A. learned B. social C. heritable D. developmental
Apply . . . 2. Evolution is best defined as
A. a gradual increase in complexity. B. a change in gene frequency over generations. C. solving the challenge of survival by adapting. D. a progression toward a complex human brain.
Analyze . . . 3. Evolutionary psychologists have made some claims that sex differences
in cognitive abilities are genetically determined. Which of the following is
not an alternative explanation for such claims? A. Hormone levels affect performance. B. Sociocultural history affects performance.
C. Different educational experiences affect performance. D. Technological limitations prevent the accurate study of sex
differences.
Module 3.1 Summary
behavioural genetics
behavioural genomics
chromosomes
dizygotic twins
DNA (deoxyribonucleic acid)
epigenetics
evolution
evolutionary psychology
genes
genotype
heritability
hunter-gatherer theory
intersexual selection
intrasexual selection
longitudinal studies
monozygotic twins
natural selection
phenotype
Know . . . the key terminology related to genes, heredity, and evolutionary psychology.
3.1a
Both methods measure genetic, environmental, and interactive contributions to behaviour. Twin studies typically compare monozygotic twins (genetically identical) and dizygotic twins (full siblings sharing the prenatal environment). Adoption studies compare adopted children to their adoptive and biological parents. These designs allow researchers to determine heritability, a number between 0 and 1 that estimates the degree to which individual differences in a trait (in a given population) are due to genetic factors. A heritability of 1.0 would mean that genes contribute to 100% of individual differences. A heritability of 0 would mean that genes have no effect on individual differences. Many human characteristics, including intelligence and personality, have heritability estimates typically ranging between .40 and .70.
Apply Activity Try putting yourself in an evolutionary psychologist’s position and answer the following two questions.
1. Many evolutionary psychologists claim that men are more interested in a mate’s physical attractiveness and youth, whereas women are more interested in qualities that contribute to childrearing success, such as intelligence and wealth. If this is the case, then who do you think would express more jealousy over sexual infidelity—men or women?
2. Researchers (Cramer et al., 2008) asked volunteers to rate how upset they would be by sexual infidelity in a mate and then they plotted the
results in the graph shown in Figure 3.9 . Do their results confirm your hypothesis?
Understand . . . how twin and adoption studies reveal relationships between genes and behaviour.
3.1b
Apply . . . your knowledge of genes and behaviour to hypothesize why a trait might be adaptive.
3.1c
Figure 3.9 Men’s and Women’s Reactions to Infidelity Men find sexual infidelity more distressing than do women, regardless of how a question is framed. Source: Copyright 2008 From Sex differences in subjective distress to unfaithfulness: Testing competing evolutionary and
violation of infidelity expectations hypotheses, The Journal of Social Psychology 148 (4): 389–405. by Robert Ervin Cramera,
Ryan E. Lipinskia, John D. Meteerb, Jeremy Ashton Houskac. Reproduced by permission of Taylor & Francis LLC,
(http://www.tandfonline.com).
Most psychological traits, as well as disorders such as Alzheimer’s disease, involve multiple genes, some of which may not yet have even been discovered.
(See the Myths in Mind feature .)
Analyze . . . claims that scientists have located a specific gene that controls a single trait or behaviour.
3.1d
Analyze . . . explanations for cognitive gender differences that are3.1e
The Working the Scientific Literacy Model feature summarized research showing that males have an advantage when it comes to a specific mental rotation task. Given that this is a relatively consistent sex difference, high testosterone levels are associated with better performance on the task, and the male advantage has been found cross-culturally, it seems plausible that this difference has a genetic basis. In future chapters we will return to issues related to sex-based differences
in cognitive abilities (see Module 9.2 ).
rooted in genetics.
Module 3.2 How the Nervous System Works: Cells and Neurotransmitters
Rod Williams/Nature Picture Library
Learning Objectives
Know . . . the key terminology associated with nerve cells, hormones, and their functioning. Understand . . . how nerve cells communicate. Understand . . . the ways that drugs and other substances affect the brain.
3.2a
3.2b 3.2c
A bite from an Australian species of snake called the taipan can kill an adult human within 30 minutes. In fact, it is recognized as the most lethally venomous species of snake in the world (50 times more potent than the also fatal venom of the king cobra). The venom of the taipan is neurotoxic, meaning that it specifically attacks cells of the nervous system. These cells are involved with more than just “thinking”—in fact, networks of nervous system cells working together are critical for basic life functions like breathing and having a heartbeat. A direct attack on these cells, therefore, spells trouble. In the case of the taipan, its bite first leads to drowsiness followed by difficulties controlling one’s head and neck muscles. Victims then experience progressive difficulty with swallowing, followed by tightness of the chest and paralysis of breathing. If enough venom was injected and treatment is not available, coma and death occur. All of this happens because of damage to the cells that will be discussed in this module—cells that work together to produce the complex human behaviours we engage in every day.
Incidentally, not all snake venom attacks the nervous system. The venom found in most rattlesnakes in North America is not neurotoxic (although you still shouldn’t hug one). Instead, it damages tissue in the vicinity of the bite as well as those tissues it reaches within the bloodstream, particularly the heart. Although this is not exactly comforting news, it should at least allow you to enjoy nature without being afraid that a snake will attack your nervous system’s cells. That’s what spiders are for . . .
Focus Questions
1. Which normal processes of nerve cells are disrupted by a
Understand . . . the roles that hormones play in our behaviour. Apply . . . your knowledge of neurotransmitters to form hypotheses about drug actions. Analyze . . . the claim that we are born with all the nerve cells we will ever have.
3.2d 3.2e
3.2f
substance like snake venom?
2. What roles do chemicals play in normal nerve cell functioning?
When we think of cells, we often imagine looking at plants or earthworms through a microscope in high-school biology class. Although thrilling, this activity likely seems to be the furthest thing from the study of behaviour. However, cells —particularly cells in the nervous system—play an incredibly important role in absolutely everything you do, from moving and sensing to thinking and feeling. Understanding how cells function and communicate with each other as part of networks will help you better understand topics discussed in later modules, such
as how we learn (Modules 6.1 , 6.2 , and 7.1 ), how different drugs (both clinical and recreational) work (Modules 5.3 and 16.3 ), and how stress affects our bodies and brains (Module 14.2 ). This module therefore serves as a building block that will deepen your understanding of almost all of the behaviours that make you “you.”
Neural Communication
The human body is composed of many different types of cells. Psychologists are
most interested in neurons , one of the major types of cells found in the nervous system, that are responsible for sending and receiving messages throughout the body. Billions of these cells receive and transmit messages every day, including while you are asleep. Millions of them are firing as a result of you reading these words. In order to understand how this particular type of cell can produce complex behaviours, it is necessary to take a closer look at the structure and function of the neuron.
The Neuron
The primary purpose of neurons is to “fire,” to receive input from one group of neurons and to then transmit that information to other neurons. Doing so allows single neurons to work together as part of networks involving thousands (and
sometimes millions) of other cells; this will eventually lead to some form of behaviour. To that end, neurons are designed in such a way that there are parts
of the cell specialized for receiving incoming information from other neurons and parts of the cell specialized for transmitting information to other neurons.
All neurons have a cell body (also known as the soma), the part of a neuron that contains the nucleus that houses the cell’s genetic material (see Figure 3.10 ). Genes in the cell body synthesize proteins that form the chemicals and structures that allow the neuron to function. The activity of these genes can be influenced by the input coming from other cells. This input is received by dendrites , small branches radiating from the cell body that receive messages from other cells and transmit those messages toward the rest of the cell. At any given point in time, a neuron will receive input from several other neurons (sometimes over 1000 other neurons!). These impulses from other cells will
travel across the neuron to the base of the cell body known as the axon hillock. If the axon hillock receives enough stimulation from other neurons, it will initiate a chemical reaction that will flow down the rest of the neuron.
Figure 3.10 A Neuron and Its Key Components Each part of a nerve cell is specialized for a specific task.
This chemical reaction is the initial step in a neuron communicating with other cells (i.e., influencing whether other cells will fire or not). The activity will travel from the axon hillock along a tail-like structure that protrudes from the cell body.
This structure, the axon , transports information in the form of electrochemical reactions from the cell body to the end of the neuron. When the activity reaches the end of the axon, it will arrive at axon terminals, bulb-like extensions filled with vesicles (little bags of molecules). These vesicles contain neurotransmitters , the chemicals that function as messengers allowing neurons to communicate with each other. The impulse travelling down the axon will stimulate the release of these neurotransmitters, thus allowing neural communication to take place.
Many different types of neurotransmitters exist, and each can have a number of different functions—something we will explore in more detail later in this module.
Although all neurons are designed to transmit information, not all neurons
perform the same function. Sensory neurons receive information from the bodily senses and bring it toward the brain, often via the spinal cord. In contrast, motor neurons carry messages away from the brain and spinal cord and toward muscles in order to control their flexion and extension (see Figure 3.11 ).
Figure 3.11 Sensory and Motor Neurons Sensory neurons carry information toward the spinal cord and the brain, whereas motor neurons send messages to muscles of the body. The interneuron links the sensory and motor neurons. This is the pathway of a simple withdrawal response
to a painful stimulus. Source: Lilienfeld, Scott O.; Lynn, Steven J; Namy, Laura L.; Woolf, Nancy J., Psychology: From Inquiry To Understanding,
2nd Ed., ©2011. Reprinted And Electronically Reproduced By Permission Of Pearson Education, Inc., New York, NY.
Within the brain itself, the structure and function of neurons varies considerably. Some cells have few if any dendrites extending from the cell body; these cells do not perform tasks requiring a lot of interactions with other neurons. In contrast, some neurons have huge branches of dendrites. Obviously, these latter neurons will perform functions involving more communication between neurons. The key point is that these differences between neurons are not simply due to chance— they have a purpose. The physical structure of a neuron is related to the function it performs.
Myths in Mind We Are Born with All the Brain
Cells We Will Ever Have For decades, neuroscience taught us that nerves do not regenerate; in other words, scientists believed that we are born with all of the brain cells we will ever have. This conclusion made perfect sense because no one had ever seen new neurons form in adults, and severe neurological damage is often permanent.
In the past 15 years or so, however, advances in brain science have
challenged this belief (Wojtowicz, 2012). Researchers have observed neurogenesis —the formation of new neurons—in a limited number of brain regions, particularly in a region critical for learning and memory
(Eriksson et al., 1998; Tashiro et al., 2007). The growth of a new cell, including neurons, starts with stem cells —a unique type of cell that does not have a predestined function. When a stem cell divides, the resulting cells can become part of just about anything—bone, kidney, or brain tissue. The deciding factor seems to be the stem cell’s chemical
environment (Abematsu et al., 2006).
Our increased understanding of neurogenesis has raised some exciting
possibilities—perhaps scientists can discover how to trigger the neural growth in other parts of the nervous system. Doing so might allow scientists to repair damaged brain structures or to add cells to brain areas affected by degenerative diseases like Parkinson’s disease and Alzheimer’s disease. When this technology is developed, there may finally be hope for recovery from injury and disease in all nerve cells.
Glial Cells
Although neurons are essential for our ability to sense, move, and think, they cannot function without support from other cells. This support comes from
different types of cells collectively known as glia (Greek for “glue”). Glial cells
are specialized cells of the nervous system that are involved in mounting immune responses in the brain, removing waste, and synchronizing the activity of the billions of neurons that constitute the nervous system. Given that glial cells perform so many different support functions, it should come as no surprise to learn that they outnumber neurons in the brain by a ratio of approximately 10 to 1.
A critical function served by certain glial cells is to insulate the axon of a neuron.
These glial cells form a white substance called myelin , a fatty sheath that insulates axons from one another, resulting in increased speed and efficiency of neural communication. In an unmyelinated axon, the neural impulse decays quickly and needs to be regenerated along the axon; the myelin protects the impulse from this decay, thus reducing how often the impulse needs to be regenerated. The speed difference between axons with and without myelin is substantial. Axons without myelin transmit information at speeds ranging from 0.5 to 10 m/s (metres per second); myelinated axons transmit information at
speeds of up to 150 m/s (Hartline & Coleman, 2007; Hursh, 1939). For obvious reasons, most neurons in the brain have myelin.
When the myelin sheath is damaged, the efficiency of the axon decreases
substantially. For instance, multiple sclerosis is a disease in which the immune system does not recognize myelin and attacks it—a process that can devastate
the structural and functional integrity of the nervous system. When myelin breaks down in multiple sclerosis, it impairs the ability of the affected neurons to transmit information along their axons. As a result, groups of brain structures that normally fire together to produce a behaviour can no longer work as a functional
network (Rocca et al., 2010; Shu et al., 2011). It would be similar to trying to drive a car that is missing a wheel. The specific symptoms associated with multiple sclerosis differ depending upon where in the brain the myelin damage occurred. Numbness or tingling sensations could be caused by the disruption of sensory nerve cell signals that should otherwise reach the brain. Problems with voluntary, coordinated movement could be due to the breakdown of myelin that supports motor nerves. The important point is that damage to a small group of axons can lead to impairments in the functioning of large networks of brain areas
(Rocca et al., 2012).
As you can see, each part of an individual neuron and glial cell performs an important function. Ultimately, however, it is the activity of networks of nerve cells that allows messages to be transmitted within the brain and the rest of the body. This activity involves the most important function a neuron can perform: to fire.
The Neuron’s Electrical System: Resting and
Action Potentials
Neural activity is based on changes in the concentrations of charged atoms
called ions. When a neuron is not transmitting information, the outside of the neuron has a relatively high concentration of positively charged ions, particularly sodium and potassium, while the interior of the axon has fewer positively charged ions as well as a relatively high concentration of negatively charged chloride ions. This difference in charge between the inside and outside of the cell leaves the inside of the axon with a negative charge of approximately −70
millivolts (−70 mV; see the first panel of Figure 3.12 ). This relatively stable state during which the cell is not transmitting messages is known as its resting potential .
Figure 3.12 Electrical Charges of the Inner and Outer Regions of Nerve Cells The inner and outer environments of a nerve cell at rest differ in terms of their electrical charge. During the resting potential, there is a net negative charge. When a nerve cell is stimulated, generating an action potential, positively charged ions rush inside the cell membrane. After the cell has fired, the positively charged ions are channelled back outside the nerve cell as it returns to a resting state. Source: Lilienfeld, Scott O.; Lynn, Steven J; Namy, Laura L.; Woolf, Nancy J., Psychology: From Inquiry To Understanding,
2nd Ed., ©2011. Reprinted And Electronically Reproduced By Permission Of Pearson Education, Inc., New York, NY.
Importantly, this seemingly stable resting state involves a great deal of tension.
This is because of two forces, the electrostatic gradient and the concentration gradient. Don’t let these technical terms scare you: the electrostatic gradient just means that the inside and outside of the cell have different charges (negative and positive, respectively), and the concentration gradient just means that different types of ions are more densely packed on one side of the membrane than on the other (e.g., there are more sodium ions outside the cell than inside the cell). However, most substances have a tendency to move from areas of high concentration to areas of low concentration whenever possible; in other words, substances spread out whenever they can so that they are evenly distributed.
So, if small pores (known as ion channels) opened up in the neuron’s cell membrane, there would be a natural tendency for positively charged sodium ions to rush into the cell.
This is what happens when a neuron is stimulated. The surge of positive ions
into the cell changes the potential of the neuron (e.g., changing from –70 mV to – 68 mV). These charges flow down the dendrites and cross the cell body to the axon hillock, where the cell body meets the axon. If enough positively charged ions reach the axon hillock to push its charge past that cell’s firing threshold
(e.g., –55 mV), the neuron will then initiate an action potential , a wave of electrical activity that originates at the beginning of the axon near the cell body and rapidly travels down its length (see the middle panel of Figure 3.12 ). When an action potential occurs, the charge of that part of the axon changes from approximately –70 mV to approximately +35 mV; in other words, the cell
changes from being negatively to positively charged (see Figure 3.13 ). This change does not occur along the entire axon at once. Rather, as one part of the axon becomes depolarized, it forces open the ion channels ahead of it, thus causing the action potential to move down the length of the axon as positively
charged ions rush through the membrane pores (Hodgkin, 1937). This pattern continues until the action potential reaches the axon terminal.
Figure 3.13 Time Course and Phases of a Nerve Cell Going from a Resting Potential to an Action Potential
Nerve cells fire once the threshold of excitation is reached. During the action potential, positively charged ions rush inside the cell membrane, creating a net positive charge within the cell. Positively charged ions are then forced out of the cell as it returns to its resting potential. Source: Based on “The Time Course and Phases of a Nerve Cell Going from Resting to Action Potential,” adapted from
Sternberg, 2004.
Of course, if this were the entire story, then all of our neurons would fire once and never fire again because the ion channels would remain open. Luckily for us, there are mechanisms in place to help our neurons return to their resting state (– 70 mV) so that they can fire again. At each point of the axon, the ion channels slam shut as soon as the action potential occurs. The sodium ions that had rushed into the axon are then rapidly pumped back out of the cell, returning it to a resting state. This process of removing the sodium ions from the cell often
causes the neuron to become hyperpolarized; this means that the cell is more negative than its normal resting potential (e.g., –72 mV instead of –70 mV). This
additional negativity makes the cell less likely to fire. It normally takes 2–3 milliseconds for the membrane to adjust back to its normal resting potential. This
brief period in which a neuron cannot fire is known as a refractory period .
When the action potential reaches the axon terminal, it triggers the release of
that cell’s neurotransmitters into the synapses , the microscopically small spaces that separate individual nerve cells. The cell that releases these chemicals is known as the presynaptic cell (“before the synapse”) whereas the cell that receives this input is known as the postsynaptic cell (or “after the synapse”). The dendrites of the postsynaptic cell contain specialized receptors that are designed to hold specific molecules, including neurotransmitters. Then, this process of neural communication will begin again.
Although this description of an action potential explains how a neuron fires, it does not explain how the nervous system differentiates between a weak and a strong neural response. It would make intuitive sense for a stronger stimulus (e.g., a loud noise) to produce a larger action potential than a weak stimulus (e.g., someone whispering); however, this is not the case. When stimulated, a
given neuron always fires at the same intensity and speed. This activity adheres
to the all-or-none principle : Individual nerve cells fire at the same strength every time an action potential occurs. Neurons do not “sort of” fire, or “overfire”— they just fire. Instead, the strength of a sensation is determined by the rate at which nerve cells fire as well as by the number of nerve cells that are stimulated. A stimulus is experienced intensely because a greater number of cells are stimulated, and the firing of each cell occurs repeatedly.
Module 3.2a Quiz:
Neural Communication
Know . . . 1. A positive electrical charge that is carried away from the cell body and
down the length of the axon is a(n) . A. refractory period B. resting potential C. action potential D. dendrite
2. Which of the following is a function of glial cells? A. Glial cells slow down the activity of nerve cells. B. Glial cells help form myelin. C. Glial cells suppress the immune system response. D. Glial cells contain the nucleus that houses the cell’s genetic
material.
Understand . . . 3. A neuron will fire when the ions inside the cell body are
A. in the resting potential. B. shifted to a threshold more positive than the resting potential. C. shifted to a threshold more negative than the resting potential. D. in the refractory period.
4. Sensory and motor nerves differ in that
A. only sensory neurons have dendrites. B. only motor neurons have axons. C. sensory neurons carry messages toward the brain, and motor
neurons carry information away from the brain.
D. sensory neurons carry messages away from the brain, and motor neurons carry information toward the brain.
The Chemical Messengers: Neurotransmitters and Hormones
As you read in the first part of this module, the presynaptic neuron releases neurotransmitters into the synapse; a fraction of these neurotransmitters will bind
to receptors on the postsynaptic neuron. This binding can have one of two effects on the postsynaptic cell. If the actions of a neurotransmitter cause the neuron’s membrane potential to become less negative (e.g., changing from –70
mV to –68 mV), it is referred to as excitatory because it has increased the probability that an action potential will occur in a given period of time. In contrast, if the actions of a neurotransmitter cause the membrane potential to become more negative (e.g., changing from –70 mV to –72 mV), it is referred to as
inhibitory because it has decreased the likelihood that an action potential will occur. An important factor in determining whether a postsynaptic neuron is excited or inhibited is the type of neurotransmitter(s) binding with its receptors.
Many different types of neurotransmitters have been identified, although most neurons send and receive a limited number of these substances. Each neurotransmitter typically has its own unique molecular shape. A lock-and-key analogy is sometimes used to explain how neurotransmitters and their receptors work: When neurotransmitters are released at the axon terminal, they cross the synapse and fit in a particular receptor of the dendrite like a key in a lock (see Figure 3.14 ).
Figure 3.14 The Lock-and-Key Analogy for Matching of Neurotransmitters and Receptors The molecular structures of different neurotransmitters must have specific shapes in order to bind with the receptors on a neuron. Source: Lilienfeld, Scott O.; Lynn, Steven; Namy, Laura L.; Woolf, Nancy J., Psychology: From Inquiry To Understanding,
Books A La Carte Edition, 2nd Ed., ©2011. Reprinted and Electronically reproduced by permission of Pearson Education,
Inc., New York, NY.
After neurotransmitter molecules have bound to postsynaptic receptors of a
neighbouring cell, they are released back into the synaptic cleft , the minute space between the axon terminal (terminal button) and the dendrite. This process is almost as important as the action potential itself. Prolonged stimulation of the receptors makes it more difficult for the cell to return to its resting potential; this is obviously necessary for the neuron to be able to fire again. Therefore, if a neurotransmitter remained latched onto a receptor for long periods of time, it would decrease the number of times that the neurons could fire (i.e., it would make your brain less powerful).
Once neurotransmitters have detached from the receptors and float back into the
synapse, they are either broken down by enzymes or go through reuptake , a process whereby neurotransmitter molecules that have been released into the synapse are reabsorbed into the axon terminals of the presynaptic neuron (see Figure 3.15 ). Reuptake serves as a sort of natural recycling system for neurotransmitters. It is also a process that is modified by many commonly used drugs. For example, the class of antidepressant drugs known as selective serotonin reuptake inhibitors (SSRIs), not surprisingly, inhibits reuptake of the neurotransmitter serotonin; in this way, SSRIs such as fluoxetine (Prozac) eventually increase the amount of serotonin available at the synapse. The result is a decrease in depression and anxiety. The process of reuptake occurs for a number of different neurotransmitters released throughout the nervous system.
Figure 3.15 Major Events at the Synapse As the action potential reaches the axon terminals, neurotransmitters (packed into spherically shaped vesicles) are released across the synaptic cleft. The neurotransmitters bind to the postsynaptic (receiving) neuron. In the process of reuptake, some neurotransmitters are returned to the presynaptic neuron via reuptake proteins. These neurotransmitters are then repackaged into synaptic vesicles.
Types of Neurotransmitters
There are literally dozens of neurotransmitters influencing the functioning of your
brain as you read this module. The various neurotransmitters listed in Table 3.1 are only a small sample of the chemicals that produce your behaviour. Each of these neurotransmitters has a molecular structure and is designed to match particular types of receptors, similar to how different keys will fit into different locks. These substances also differ in terms of the specific brain areas they target. As a result, different neurotransmitters will have different effects on our behaviour.
Table 3.1 Major Neurotransmitters and Their Functions
Neurotransmitter Some Major Functions
Glutamate Excites nervous system; memory and autonomic nervous
system reactions
GABA (gamma-amino
butyric acid)
Inhibits brain activity; lowers arousal, anxiety, and
excitation; facilitates sleep
Acetylcholine Movement; attention
Dopamine Control of movement; reward-seeking behaviour;
cognition and attention
Norepinephrine Memory; attention to new or important stimuli; regulation
of sleep and mood
Serotonin Regulation of sleep, appetite, mood
The most common neurotransmitters in the brain are glutamate and GABA. Glutamate is the most common excitatory neurotransmitter in the brains of vertebrates (Dingledine et al., 1999; Meldrum, 2000). It is involved in a number of processes, including our ability to form new memories (Bliss & Collingridge, 1993; Peng et al., 2011). Abnormal functioning of glutamate-releasing neurons has also been implicated in a number of brain disorders including the triggering
of seizures in epilepsy (During & Spencer, 1993) and damage caused by strokes (Hazell, 2007; McCulloch et al., 1991). In contrast, GABA (gamma- amino butyric acid , for those of you enraged by acronyms) is the primary inhibitory neurotransmitter of the nervous system, meaning that it prevents neurons from generating action potentials. It accomplishes this feat by reducing the negative charge of neighbouring neurons even further than their resting state of −70 mV. When GABA binds to receptors, it causes an influx of negatively charged chloride ions to enter the cell, which is the opposite net effect of what happens when a neuron is stimulated. As an inhibitor, GABA facilitates sleep
(Tobler et al., 2001) and reduces arousal of the nervous system. Low levels of GABA have been linked to epilepsy, likely because there is an imbalance
between inhibitory GABA and excitatory glutamate (Upton, 1994).
Another common neurotransmitter is acetylcholine. Acetylcholine is one of the most widespread neurotransmitters within the body, found at the junctions between nerve cells and skeletal muscles; it is very important for voluntary movement. Acetylcholine released from neurons connected to the spinal cord binds to receptors on muscles. The change in the electrical properties of the muscle fibres leads to a contraction of that muscle. This link between the
nervous system and muscles is known as a neuromuscular junction. A number of animals release venom that influences the release of acetylcholine, including the
black widow spider (Diaz, 2004) and a number of snakes. Recall the neurotoxic snake venom discussed at the beginning of this module: This toxin disrupts the activity of acetylcholine transmission at the neuromuscular junctions. Different snakes carry slightly different types of neurotoxic venom. Some types of venom block acetylcholine release at the presynaptic terminals, preventing its release into the synapse. Another type of venom blocks the receptors on the
postsynaptic cell, preventing acetylcholine from binding to them (Lewis & Gutmann, 2004). Either way, the effects are devastating.
In addition to these effects in neuromuscular junctions, acetylcholine activity in
the brain is associated with attention and memory (Drachman & Leavitt, 1974; Himmelheber et al., 2000). Altered levels of this neurotransmitter have also been linked to cognitive deficits associated with aging and Alzheimer’s disease
(Bartus et al., 1982; Craig et al., 2011). Indeed, several drugs used to reduce the progression of Alzheimer’s disease are designed to slow the removal of acetylcholine from the synapse, thus allowing it to have a larger effect on
postsynaptic cells (Darvesh et al., 2003). The fact that acetylcholine can influence functions ranging from movement to memory shows us that where in the nervous system a neurotransmitter is released can have a dramatic influence
on what roles that neurotransmitter will serve.
This point is particularly noticeable when one discusses a class of
neurotransmitters known as the monoamines. This group of brain chemicals includes the well-known neurotransmitters dopamine, norepinephrine, and
serotonin. Dopamine is a monoamine neurotransmitter involved in such varied functions as mood, control of voluntary movement, and processing of rewarding experiences. When reading this definition, you can’t help but be stunned by the variety of processes influenced by dopamine. This breadth is due to the fact that dopamine is released by neurons in (at least) three pathways extending to different parts of the brain including areas in the centre of the brain
related to movement and to reward responses (Koob & Volkow, 2010; Martinez & Narendren, 2010; see Module 5.3 ) and areas in the front third of the brain involved with controlling our attention (Robbins, 2000).
Attention is also influenced by our overall alertness or arousal, a characteristic
that is affected by the neurotransmitter norepinephrine. Norepinephrine (also known as noradrenaline) is a monoamine synthesized from dopamine molecules that is involved in regulating stress responses, including increasing arousal, attention, and heart rate. Norepinephrine is formed in specialized nuclei in the bottom of the brain (known as the brainstem) and projects throughout the cortex, influencing the activity of a number of different systems ranging from
wakefulness to attention (Berridge & Waterhouse, 2003). It also projects down the spinal cord and serves as part of the “fight-or-flight” response to threatening
stimuli. Norepinephrine often works alongside epinephrine (also known as adrenaline), a hormone and neurotransmitter created in the adrenal gland on the kidneys. Both norepinephrine and epinephrine energize individuals to help them become more engaged with a given activity. (Interesting trivia: Epinephrine has
its name because the name adrenaline was trademarked by a drug company.)
Finally, serotonin is a monoamine involved in regulating mood, sleep, aggression, and appetite (Cappadocia et al., 2009; Young & Leyton, 2002). It is formed in the brainstem and projects throughout the brain and spinal cord. Serotonin is the neurotransmitter that you are most likely to have heard of due to its critical role in depression. As discussed earlier in this module, many antidepressant medications block the reuptake of serotonin, thus ensuring that this substance remains in the synapse for longer durations. The result is an elevation of mood and a decrease in symptoms of depression and anxiety.
Throughout this section, we have noted that medications (or other substances) can influence the levels of these neurotransmitters as well as how efficiently they bind to their targets. But, as you will see, not all drugs affect neurotransmission in the same way.
Drug Effects on Neurotransmission
Drugs of all varieties, from prescription to recreational, affect the chemical
signalling that takes place between nerve cells. Agonists are drugs that enhance or mimic the effects of a neurotransmitter’s action. The well-known drug nicotine is an acetylcholine agonist, meaning that it stimulates the receptor sites for this neurotransmitter. The antianxiety drug alprazolam (Xanax) is a GABA agonist—it causes relaxation by increasing the activity of this inhibitory neurotransmitter. Drugs can behave as agonists either directly or indirectly. A
drug that behaves as a direct agonist physically binds to that neurotransmitter’s receptors at the postsynaptic cells (e.g., nicotine molecules attach themselves to receptors that acetylcholine molecules would normally stimulate). A drug that
acts as an indirect agonist facilitates the effects of a neurotransmitter, but does not physically bind to the same part of the receptor as the neurotransmitter. For example, a drug that blocks the process of reuptake would be an indirect agonist. A drug that attaches to another binding site on a receptor but does not interfere with the neurotransmitter’s binding would also be an indirect agonist.
Drugs classified as antagonists inhibit neurotransmitter activity by blocking receptors or preventing synthesis of a neurotransmitter (see Figure 3.16 ).
You may have heard of the cosmetic medical procedure known as a Botox injection. Botox, which is derived from the nerve-paralyzing bacterium that causes botulism, blocks the action of acetylcholine by binding to its postsynaptic
receptor sites (Dastoor et al., 2007). Blocking acetylcholine could lead to paralysis of the heart and lungs; however, when very small amounts are injected into tissue around the eyes, the antagonist simply paralyzes the muscles that lead to wrinkles. When muscles are not used, they cannot stretch the skin— hence the reduction in wrinkling when acetylcholine activity is blocked. Because Botox directly binds with acetylcholine receptors and thus prevents acetylcholine
from doing so, it is considered a direct antagonist. If a chemical reduces the influence of a neurotransmitter without physically blocking the receptor, it would be classified as an indirect antagonist.
Figure 3.16 Drug Effects at the Synapses Drugs can act as agonists by facilitating the effects of a neurotransmitter, or as antagonists by blocking these effects.
Botox injections paralyze muscles, which can increase youthful appearance in areas such as the face. It is a direct antagonist for acetylcholine. Thinkstock/Stockbyte/Getty Images
Hormones and the Endocrine System
Neurotransmitters are not the body’s only chemical messenger system. Hormones are chemicals secreted by the glands of the endocrine system. Generally, neurotransmitters work almost immediately within the microscopic space of the synapse, whereas hormones are secreted into the bloodstream and travel throughout the body. Thus, the effects of hormones are much slower than those of neurotransmitters. With help from the nervous system, the endocrine
system contributes to homeostasis—the balance of energy, metabolism, body temperature, and other basic functions that keeps the body working properly
(see Figure 3.17 ; see Module 11.1 ). In other words, the brain triggers activity in the endocrine system which then influences the brain’s activity via hormones. This cycle continues as our brain and body attempt to maintain the appropriate energy levels for dealing with the environment.
Figure 3.17 The Endocrine System Glands throughout the body release and exchange hormones. The hypothalamus interacts with the endocrine system to regulate hormonal processes. Source: Lilienfeld, Scott O.; Lynn, Steven J; Namy, Laura L.; Woolf, Nancy J., Psychology: From Inquiry To Understanding,
2nd Ed., ©2011. Reprinted And Electronically Reproduced By Permission Of Pearson Education, Inc., New York, NY.
The brain area that is critical for this brain-endocrine relationship is the hypothalamus , a brain structure that regulates basic biological needs and motivational systems. The hypothalamus releases specialized chemicals called releasing factors that stimulate the pituitary gland —the master gland of the endocrine system that produces hormones and sends commands about hormone production to the other glands of the endocrine system. These hormones can be released by glands throughout the body before finding their way to the brain via the bloodstream.
How we respond to stress illustrates nicely how the nervous and endocrine systems influence each other. In psychological terms, stress is loosely defined as an imbalance between perceived demands and the perceived resources available to meet those demands. Such an imbalance might occur if you
suddenly realize your midterm exam is tomorrow at 8:00 A.M. Your resources— time and energy—may not be enough to meet the demand of succeeding on the exam. The hypothalamus, however, sets chemical events in motion that physically prepare the body for stress. It signals the pituitary gland to release a
hormone into the bloodstream that in turn stimulates the adrenal glands , a pair of endocrine glands located adjacent to the kidneys that release stress hormones, such as cortisol and epinephrine. Cortisol and epinephrine help mobilize the body during stress, thus providing enough energy for you to deal with the sudden increase in activity necessary to respond to the stress-inducing
situation (see Module 14.2 ).
Another important chemical is endorphin , a hormone produced by the pituitary gland and the hypothalamus that functions to reduce pain and induce feelings of pleasure. Endorphins are released into the bloodstream during events such as strenuous exercise, sexual activity, or injury. They act on portions of the brain that are attuned to reward, reinforcement, and pleasure, inhibiting the perception of pain and increasing feelings of euphoria (extreme pleasantness and relaxation). Morphine—a drug derived from the poppy plant—binds to
endorphin receptors (the term endorphin translates to endogenous [internal] morphine). Morphine molecules fit into the same receptor sites as endorphins and, therefore, produce the same painkilling and euphoric effects.
Extracts from the seeds of some poppy flowers contain opium. Morphine and one of its derivatives, heroin, can be synthesized from these seeds. Martin Nemec/Shutterstock
The final hormone that will be discussed is perhaps the best known:
testosterone. This hormone serves multiple functions, including driving physical and sexual development over the long term. Testosterone levels also surge during sexual activity. However, as you will read in the next section, these are not testosterone’s only functions.
Working the Scientific Literacy Model Testosterone and Aggression
Testosterone is one of the main sex hormones produced by the body. In men, it is produced by specialized cells in the testes; in women, it is produced in the ovaries. It can also be secreted by
the adrenal cortex on the kidneys (Mazur & Booth, 1998). Because it is related to male sexual development and functioning, this hormone was traditionally targeted as an explanation for why men tend to be more physically aggressive than women. In other
words, there was an assumption that testosterone causes aggression. Scientific studies paint a slightly more complex picture.
What do we know about testosterone and aggression? There is a large body of research linking testosterone and aggression. In one experiment, researchers castrated a group of mice, an experience that obviously reduced their testosterone levels. The castrated mice as well as a control group of healthy mice then encountered an aggressive mouse. Although this type of interaction would usually lead to physical fights, the castrated
mice showed almost no aggressive response (Beeman, 1947). However, when castrated mice received an injection of testosterone prior to the interaction, they did respond aggressively. This study suggested a causal link between testosterone and aggression. Human research also indicates a similar relationship. High testosterone levels were associated with a history of violent crime (e.g., murder, armed robbery) in both
male and female prisoners (Dabbs et al., 1995; Dabbs & Hargrove, 1997). Prisoners who were jailed for less violent crimes had lower testosterone levels. Thus, both animal and
human research has historically shown some link between testosterone and aggression.
How can science explain the relationship between testosterone and aggression? Scientific studies show that the relationship between testosterone
and aggression is more specific than was once thought. Testosterone appears to be involved with social aggression and dominance rather than with non-social forms of aggression such
as hunting or responding to attacks (Eisenegger et al., 2011). Dominance involves an individual striving for or attempting to maintain a high social status. In animals, such a status is often linked with increased access to food and potential mates. In many primate species such as rhesus monkeys, dominance is achieved non-violently through stares, threatening body language, and shouts rather than through physical contact
(Higley et al., 1996). It is also associated with higher testosterone levels. In studies with human participants, socially dominant adolescents and adults tended to have higher levels of
testosterone (Carré et al., 2009; Rowe et al., 2004).
Testosterone also increased when participants perceived a potential threat to their status. Chimpanzees who anticipate competing for access to food show an elevated testosterone
response (Wobber et al., 2010). In humans, several studies have found that competition was linked with increased testosterone,
with activities ranging from wrestling and tennis to chess (Booth et al., 1989; Mazur et al., 1992)! Importantly, higher testosterone levels were found for winners than for losers, again suggesting a
link between this hormone and social dominance (Oliveira et al., 2009).
Can we critically evaluate this research? One concern with many of these studies is that they are
correlational. As you read in Module 2.2 , correlational designs show a relationship between two variables but cannot be used to state that one causes the other. For instance, it is impossible to say if winning led to an increase in testosterone or if players with higher testosterone levels were more likely to win. In order to deal with this concern, some researchers have manipulated the competitions so that one player or the other wins. The results of
these studies showed that winning leads to an increase in testosterone (e.g., Schultheiss et al., 2005).
Another question that arises is how does testosterone actually affect behaviour? What does testosterone do to allow people and animals to become (or feel) more socially dominant? Several studies suggest that injections of testosterone lead to less
socially minded behaviour (Eisenegger et al., 2011). For instance, in most situations, people tend to subtly mimic the facial expressions of others; this makes the other person feel like they are being understood and increases social bonds. Researchers have found that injections of testosterone decrease facial mimicry
(Hermans et al., 2006). Participants who have received testosterone are also more aware of potential threats. When you perceive a happy face, it does not likely cause any alarm. The same is true for people who have received an injection of
testosterone (see Figure 3.18 ). However, when these same individuals view an angry face—which is a potential threat—their heart rate increases much more than the heart rates of control
participants (van Honk et al., 2001). Together, these studies suggest that testosterone alters behaviours that would promote social bonding, thus making the individual more likely to respond with social aggression.
Figure 3.18 Testosterone and Social Threat
Individuals who received an injection of testosterone showed
much larger heart rate responses to threatening faces than did control participants. The groups did not differ when viewing non- threatening happy faces. Source: Republished with permission of Elsevier Science, Inc., from The role of testosterone in social
interaction. Trends in Cognitive Sciences, Vol. 15, No. 6, 2011., by Christoph Eisenegger; Johannes
Haushofer; Ernst Fehr. Permission conveyed through Copyright Clearance Center, Inc.
Why is this relevant? These studies demonstrate that testosterone is not simply related
to aggression. Instead, it is related to social aggression. Although this still means that this hormone could be linked with violent crime (which is, in some ways, a form of dominance), social dominance also has an evolutionary purpose. Dominant individuals are more likely to survive (and therefore reproduce) in many species. They would receive better food and access to mates. They would also experience less stress caused by attacks from dominant members of the group. Therefore, although we don’t think of social aggression as being as a good thing, testosterone likely helped our ancestors to survive while others did not.
Neurons in Context
When reading about neuronal structures, neurotransmitters, and hormones, it is easy to lose sight of how these cells and molecules fit together with discussions
of genetics (Module 3.1 ) and larger brain structures (Module 3.3 ). In the last few years, a number of genes related to different neurotransmitters have been identified. These genes can influence how the neurotransmitters are formed as well as processes such as reuptake. These seemingly minor differences in genes can affect neurotransmitter levels and thus how neurons communicate with each other. This alters the networks of neurons firing together
in the brain; these networks of structures produce your thoughts, movements, and sensations. So, while a discussion of brain cells seems far removed from the science of behaviour, these brain cells are, in fact, what makes you “you.”
Module 3.2b Quiz:
The Chemical Messengers: Neurotransmitters and Hormones
Know . . . 1. A(n) is a drug that blocks the actions of a neurotransmitter.
A. agonist B. antagonist C. stop agent D. endorphin
Understand . . . 2. To reverse the effects of neurotoxic venom from a snakebite, which of the
following actions would likely be most effective?
A. Give the patient a high dose of dopamine. B. Give the patient a substance that would allow the body to resume
transmission of acetylcholine.
C. Give the patient a drug that would increase GABA transmission. D. Give the patient an acetylcholine antagonist.
Apply . . . 3. People who experience a loss of pain sensation in the middle of exercise
are likely having a rush of . A. adrenaline B. norepinephrine C. pituitary D. endorphin
Analyze . . . 4. People often attribute male aggression to high levels of testosterone.
Which of the following statements is an important consideration regarding
this claim?
A. High testosterone levels may be correlated with predatory aggression (e.g., hunting behaviours), but may not necessarily be the cause of it.
B. Testosterone is found exclusively in males and, therefore, is a likely cause of male aggression.
C. There are multiple types of aggression; testosterone is only linked with social aggression.
D. Testosterone does not affect aggressive behaviours.
Module 3.2 Summary
acetylcholine
action potential
adrenal glands
agonists
all-or-none principle
antagonists
axon
cell body
dendrites
dopamine
endorphin
GABA (gamma-amino butyric acid)
glial cells
glutamate
Know . . . the key terminology associated with nerve cells, hormones, and their functioning.
3.2a
hormones
hypothalamus
myelin
neurogenesis
neuron
neurotransmitters
norepinephrine
pituitary gland
refractory period
resting potential
reuptake
serotonin
stem cells
synapses
synaptic cleft
Nerve cells fire because of processes involving both electrical and chemical factors. A stimulated nerve cell goes from resting potential to action potential following an influx of positively charged ions inside the membrane of the cell. As the message reaches the end of the nerve cell, neurotransmitters are released into synapses and bind to neighbouring postsynaptic cells. Depending on the type of neurotransmitter, the effect can be either inhibitory or excitatory.
Understand . . . how nerve cells communicate.3.2b
Understand . . . the ways that drugs and other substances affect the brain.
3.2c
Drugs can be agonists or antagonists. A drug is an agonist if it enhances the effects of a neurotransmitter. This outcome occurs if the drug increases the release of a neurotransmitter, blocks reuptake, or mimics the neurotransmitter by binding to the postsynaptic cell. A drug is an antagonist if it blocks the effects of a neurotransmitter. Antagonists block neurotransmitter release, break down neurotransmitters in the synapse, or block neurotransmitters by binding to postsynaptic receptors.
Hormones have multiple influences on behaviour. The nervous system—in particular, the hypothalamus—interacts with the endocrine system in controlling the release of hormones. A few of humans’ many hormonally controlled responses include reactions to stress and pain as well as sexual responses. Some hormones are associated with, though not necessarily a primary cause of, aggressive behaviour.
In this module you read about how selective serotonin reuptake inhibitors (SSRIs) slow down the reuptake process to increase the amount of serotonin at the synapse.
Apply Activity Consider another drug—a monoamine oxidase inhibitor (MAOI).
1. Based on its name, monoamine oxidase inhibitor, which neurotransmitters would be affected by such a drug? (See page 95.)
2. If monoamine oxidase is an enzyme that breaks down monoamine transmitters, what would happen if a drug inhibits the enzyme? What effect would this action have on levels of the neurotransmitters (i.e., an overall increase or decrease)?
3. Would the effects of an MAOI resemble those of an SSRI?
Understand . . . the roles that hormones play in our behaviour.3.2d
Apply . . . your knowledge of neurotransmitters to form hypotheses about drug actions.
3.2e
Earlier in this module, a Myths in Mind feature addressed the question of whether we are born with all of the nerve cells we will ever have. Although scientists once believed this to be true, we now know that neurogenesis—the growth of new neurons—takes place in several parts of the brain. One of these regions is the hippocampus, which is involved in learning and memory (see Module 7.1 ).
Analyze . . . the claim that we are born with all the nerve cells we will ever have.
3.2f
Module 3.3 Structure and Organization of the Nervous System
Montreal Neurological Hospital and Institute
Learning Objectives
Know . . . the key terminology associated with the structure and organization of the nervous system.
3.3a
Some of you may have seen this Canadian Heritage Moment on television: A woman smells toast burning and then collapses to the ground while having a seizure. The scene then changes to a surgical suite. Dr. Wilder Penfield, a doctor at the Montreal Neurological Institute, is electrically stimulating different parts of the woman’s brain prior to her surgery to remove the brain tissue causing her seizures. In one scene, she reports that she sees “the most wonderful lights.” After another electrical burst, she asks, “Did you pour cold water on my hand, Dr. Penfield?” Then, in the scene’s climax, the patient says, “Dr. Penfield! I can smell burnt toast!” By locating the sensation that immediately preceded the woman’s seizure, Dr. Penfield was able to deduce the probable source of the woman’s seizures.
In addition to showing us that early brain researchers were part scientist and part detective, this Canadian Heritage Moment also makes an important point about the organization of the brain: Different parts of the brain will be related to different functions, including sensations, memories, and emotions. In this module, we will discuss many of the important brain regions related to the biology of behaviour. (Note: If you haven’t seen the video mentioned in this section, you can find it online at
https://www.youtube.com/watch?v=mSN86kphL68.)
Focus Questions
1. How do the different divisions of the nervous system work together when you are startled?
2. How does the brain control movement?
Understand . . . how studies of split-brain patients reveal the workings of the brain. Apply . . . your knowledge of brain regions to predict which abilities might be affected when a specific area is injured or diseased. Analyze . . . whether neuroplasticity will help people with brain damage.
3.3b
3.3c
3.3d
In this module, we translate our knowledge of nerve cells into an understanding of how they work as an integrated system. This section is rich with terminology and can be challenging. As you read through it, try to think about how the different parts of the nervous system apply to your own behaviour and experiences. Doing so will help you remember the terms, and will also show you that many different parts of your nervous system interact when you perform even the simplest of behaviours.
Divisions of the Nervous System
Think about it: billions of cells work together to let you have a personality, feel emotions, dance, enjoy music, and remember all of the ups and downs you experience in life. In addition to these voluntary activities, the nervous system is also involved in a number of involuntary processes like controlling your heart rate, blinking, and breathing. Given these diverse functions, it shouldn’t be surprising to hear that the nervous system has a number of divisions that allow these processes to seamlessly take place. We begin our exploration of the nervous system by examining the most basic of these distinctions—the difference between the central and peripheral nervous systems.
The Central Nervous System
Look up from this page and examine the objects around you. What are they? Can you use words to describe them? How would you use them? Your ability to think up answers to these questions involves different parts of your central
nervous system. The central nervous system (CNS) consists of the brain and the spinal cord (see Figure 3.19 ). The human brain is perhaps the most complex entity known. Its capacity to store information is almost limitless. Your personality, preferences, memories, and conscious awareness are all packed into this three-pound structure made up of approximately 100 billion individual neurons. The other part of the CNS, the spinal cord, runs from your neck down to the base of your spine. The spinal cord receives information from the brain and
stimulates nerves that extend out into the body; this stimulation produces movements. It also receives information from sensory nerves in the body and transmits it back to the brain (or, in the case of reflexes, organizes rapid
movements without the help of the brain). These two structures are critical for our survival. But, our ability to move and to sense the outside world would be impossible without another major division of the nervous system.
Figure 3.19 The Organization of the Nervous System The nervous system can be divided into several different components, each with a specific set of structures and functions.
The Peripheral Nervous System
Wiggle your fingers. Now feel the edges of this book (or the edge of your computer if you’re reading an eText). In both cases, you are sending information from your central nervous system to the nerves in the rest of your body that control movement. You are also receiving sensory input from your body as you interact with your environment. These processes are performed by the peripheral nervous system (PNS) , a division of the nervous system that transmits signals between the brain and the rest of the body and is divided into two subcomponents, the somatic system and the autonomic system (see Figure
3.20 ). The somatic nervous system consists of nerves that control skeletal muscles, which are responsible for voluntary and reflexive movement; it also consists of nerves that receive sensory input from the body. This would be the division of the PNS that is active when you wiggle your fingers or feel the edge of a book. Any voluntary behaviour, such as coordinating the movements needed to reach, walk, or move a computer mouse, makes use of the somatic nervous system.
Figure 3.20 The Autonomic Nervous System The sympathetic and parasympathetic divisions of the autonomic nervous system control and regulate responses of the glands and organs of the body. Source: Lilienfeld, Scott O.; Lynn, Steven; Namy, Laura L.; Woolf, Nancy J., Psychology: From Inquiry To Understanding,
Books A La Carte Edition, 2nd Ed., ©2011. Reprinted and Electronically reproduced by permission of Pearson Education,
Inc., New York, NY.
But, not all behaviours are voluntary. For example, it is unlikely that you can make your heart race or your palms sweat. Responses such as these are often
automatic, occurring outside of our conscious control. These behaviours are
performed by the autonomic nervous system , the portion of the peripheral nervous system responsible for regulating the activity of organs and glands. This system includes two subcomponents, one that increases our ability to make rapid responses, and one that helps us return to normal levels of emotional
arousal. The sympathetic nervous system is responsible for the fight-or- flight response of an increased heart rate, dilated pupils, and decreased salivary flow—responses that prepare the body for action. If you hear footsteps behind you as you are walking alone or if you barely avoid an accident while driving,
then you will experience sympathetic arousal. In this process, blood is directed toward your skeletal muscles, heart rate and perspiration increase, and digestive processes are slowed; each of these responses helps to direct energy where it is most needed in case you need to respond. However, if you remained in this heightened state of emotional arousal, you would quickly run out of energy resources. It is therefore important for you to have a system in place that allows
your body to quickly return to normal levels of energy use. The parasympathetic nervous system helps maintain homeostatic balance in the presence of change; following sympathetic arousal, it works to return the body to a baseline, nonemergency state. Generally speaking, the parasympathetic nervous system does the opposite of what the sympathetic nervous system does (see Figure 3.20 ).
So, if you thought you saw a snake beside your foot, you would have a sympathetic nervous system (PNS) response that would increase your heart rate and would send blood toward your leg muscles. Your brain (CNS) would initiate a movement and send that order down the spinal cord (CNS) where it would project out from spinal nerves (PNS) that influence the activity of muscles. Sensory feedback (PNS) from the skin and muscles would travel back to the spinal cord (CNS) and up to the brain (CNS). After some time had passed and you realized that it was actually a stick, not a snake, your parasympathetic nervous system (PNS) would help you calm down so that you were no longer frightened and no longer using up all of your energy responding to this stimulus.
Although these different parts of the PNS and CNS clearly influence a number of our responses, most of these activities are biologically simple. An exception is
the activity that occurs in the brain, a stunningly complex structure made up of hundreds of smaller parts. As most of our behaviour is directed by brain activity, the rest of this module will focus on explaining how the different parts of this biological marvel function, alone and in larger networks.
Module 3.3a Quiz:
Divisions of the Nervous System
Know . . . 1. Which division of the peripheral nervous system is responsible for
countering much of the activity associated with the sympathetic nervous system?
A. Somatic nervous system B. Pseudosympathetic nervous system C. Central nervous system D. Parasympathetic nervous system
2. The central nervous system consists of which of the following? A. The brain and the spinal cord B. The sympathetic and parasympathetic nervous system C. The brain and the nerves controlling digestion and other
automatic functions
D. The somatic and autonomic systems
Understand . . . 3. A major difference between the somatic and autonomic branches of the
nervous system is that
A. the somatic nervous system controls involuntary responses, and the autonomic nervous system controls voluntary movement.
B. the somatic nervous system is located in the brain, and the autonomic nervous system is located peripherally.
C. the somatic nervous system controls voluntary movement, and the autonomic nervous system controls involuntary responses.
D. the somatic nervous system controls sensation, and the
autonomic nervous system controls movement.
The Brain and Its Structures
When you look at the brain, you will immediately notice that it appears to be
divided into two symmetrical halves known as cerebral hemispheres. Each hemisphere contains the same structures, although there are some small
differences in the size of these brain areas (Springer & Deutsch, 1998). Within each hemisphere, the structures of the brain are organized in a hierarchical fashion. The human brain, as well as that of other animals, can be subdivided
into three main regions: the hindbrain, the midbrain, and the forebrain (Table 3.2 ). This system of dividing the brain may tempt you to view it as a mass of separate compartments. Keep in mind that the entire brain is composed of highly integrated circuitry and feedback loops. In other words, although the forebrain may perform complex thinking processes like decision making, its activity is influenced by (and influences) structures in the midbrain and the hindbrain.
Table 3.2 Major Brain Regions, Structures, and Their Functions
Regions and Structures Functions
Hindbrain
Brainstem (medulla and
pons)
Breathing, heart rate, sleep, and wakefulness
Cerebellum Balance, coordination and timing of movements; attention
and emotion
Midbrain
Superior colliculus Orienting visual attention
Inferior colliculus Orienting auditory attention
Forebrain
Basal ganglia Movement, reward processing
Amygdala Emotion
Hippocampus Memory
Hypothalamus Temperature regulation, motivation (hunger, thirst, sex)
Thalamus Sensory relay station
Cerebral Cortex
Occipital lobe Visual processing
Parietal lobe Sensory processing, bodily awareness
Temporal lobe Hearing, object recognition, language, emotion
Frontal lobe Thought, planning, language, movement
The Hindbrain: Sustaining the Body
The hindbrain consists of structures that are critical to controlling basic, life- sustaining processes. At the top of the spinal cord is a region called the brainstem , which is the “stem” or bottom of the brain and consists of two structures: the medulla and the pons (Figure 3.21 ). Nerve cells in the medulla connect with the body to perform basic functions such as regulating breathing, heart rate, sneezing, salivating, and even vomiting—all those actions your body does with little conscious control on your part. The fact that the medulla can control all of these activities without us consciously controlling our responses is important—without this ability, our lives would consist of nothing more than sending signals to various organs to ensure that we stayed alive. The pons
contributes to general levels of wakefulness, and also appears to have a role in
dreaming (see Module 5.1 ). Due to its connections to other structures in the brain and spinal cord, the pons is also part of a number of networks including
those that control balance, eye movements, and swallowing (Nolte, 1999).
Figure 3.21 The Hindbrain and Midbrain Structures in the hindbrain are responsible for basic functions that sustain the body. The midbrain includes structures that control basic sensory responses and voluntary movement. Source: Lilienfeld, Scott O.; Lynn, Steven J; Namy, Laura L.; Woolf, Nancy J., Psychology: From Inquiry To Understanding,
2nd Ed., ©2011. Reprinted And Electronically Reproduced By Permission Of Pearson Education, Inc., New York, NY.
An additional hindbrain structure, the reticular formation, extends from the medulla upwards to the midbrain, a higher brain region that will be described shortly. The reticular formation influences attention and alertness. When you wake up in the morning, you can thank (in part) your reticular formation. This structure also communicates with cells in the spinal cord involved with movements related to walking and posture.
The structures in the hindbrain are able to influence a number of different behaviours through their connections to other parts of the brain and spinal cord.
They also have dense connections with another hindbrain structure, the
cerebellum. The cerebellum (Latin for “little brain”) is the lobe-like structure at the base of the brain that is involved in the monitoring of movement, maintaining balance, attention, and emotional responses. The cerebellum’s role in movement has been known for almost two centuries (Flourens, 1824; Schmahmann, 2004). Damage to this structure leads to uncoordinated and jerky movements that interfere with walking, posture, and most limb movements. These symptoms suggest that the cerebellum is involved with coordinating and timing ongoing
movements rather than with generating responses on its own (Yamazaki & Tanaka, 2009). However, recent research indicates that these timing functions extend beyond movement. Patients with damage to the cerebellum have
difficulty controlling their attention (Schweizer, Alexander, et al., 2007; Schweizer, Oriet, et al., 2007). They also have problems with emotional control, including personality changes and impulsivity, a set of symptoms now known as
the cognitive affective behavioural syndrome (Schmahmann & Sherman, 1998). The cerebellum is likely able to influence this wide variety of functions because it has dense connections to a number of areas in the forebrain as well as to evolutionarily older structures in the base of the brain like the hypothalamus, a
structure related to the autonomic nervous system (Stoodley & Schmahmann, 2010; Zhu et al., 2006). Through these connections, the so-called “little brain” is able to have a big effect on behaviour.
The Midbrain: Sensation and Action
The cerebellum is not the only neural region involved with both movement and
attention. The midbrain , which resides just above the hindbrain, primarily functions as a relay station between sensory and motor areas (Figure 3.21 ). For example, have you ever detected a sudden movement out of the corner of your eye? This ability to capture your visual attention is influenced by the
superior colliculus (plural colliculi). Of course, your ability to orient your attention is not limited to visual stimuli. How do you respond when someone’s phone rings in class? You, quite naturally, pay attention to that new sound and turn your head toward its source (while mentally judging the person’s ringtone). This ability to move your auditory attention is influenced by another midbrain structure, the
inferior colliculus (plural colliculi).
Like the hindbrain, structures in the midbrain do not act as independent units; rather, they are part of much larger networks. This concept is powerfully
illustrated by the substantia nigra. This midbrain area has connections to structures in the forebrain (discussed below); this network of dopamine-releasing cells is involved with the control of movements. Parkinson’s disease—a condition marked by major impairments in voluntary movement—is caused by a loss of the dopamine-producing cells in this network.
The Forebrain: Emotion, Memory, and Thought
The forebrain , the most visibly obvious region of the brain, consists of all of the neural structures that are located above the midbrain, including all of the folds and grooves on the outer surface of the brain; the multiple interconnected structures in the forebrain are critical to such complex processes as emotion, memory, thinking, and reasoning. The forebrain also contains spaces called ventricles (Figure 3.22 ). Although the ventricles appear hollow, they are filled with cerebrospinal fluid, a solution that helps to eliminate wastes and provides nutrition and hormones to the brain and spinal cord. Cerebrospinal fluid also cushions the brain from impact against the skull.
Figure 3.22 The Cerebral Ventricles Four ventricles in the brain contain cerebrospinal fluid. This provides nutrition and cushioning for many parts of the brain. Source: Carlson, Neil R., Physiology of Behaviour, 11th ed., ©2013, pp. 29, 72. Reprinted and Electronically reproduced by
permission of Pearson Education, Inc., Upper Saddle River, New Jersey.
Sitting next to the ventricles are the basal ganglia , a group of three structures that are involved in facilitating planned movements, skill learning, and integrating sensory and movement information with the brain’s reward system (Figure 3.23 ). The basal ganglia form networks that promote and inhibit movements. These two networks interact to allow us to have our different muscles work together in the correct sequence rather than having them “flex” at random times. People who are very practised at a specific motor skill, such as playing an instrument or riding a bicycle, have actually modified their basal ganglia through practice to better coordinate engaging in the activity. Improper functioning of the basal ganglia can lead to movement disorders like Parkinson’s disease and Huntington’s disease, a condition involving uncontrollable movements of the body, head, and face. The basal ganglia are also affected in people who have
Tourette’s syndrome—a condition marked by erratic and repetitive facial and
muscle movements (called tics), heavy eye blinking, and frequent noise making such as grunting, snorting, or sniffing. The excess dopamine that appears to be transmitted within the basal ganglia contributes to many of the classic Tourette’s
symptoms (Baym et al., 2008). Incidentally, contrary to popular belief, the shouting of obscenities (coprolalia) is actually relatively uncommon in people with Tourette’s syndrome.
Figure 3.23 The Basal Ganglia The basal ganglia function in both voluntary movement and responses to rewarding stimuli.
Some parts of the basal ganglia are also involved in emotion, particularly
experiences of pleasure and reward (Berridge et al., 2009). These structures respond to several different types of rewards including tasty foods like chocolate
(Small et al., 2003) and monetary rewards (Elliott et al., 2003; Zald et al., 2004). They also form a network with a nearby structure—the nucleus accumbens— whose activity accompanies many kinds of pleasurable experiences, including
sexual excitement and satisfying a food craving (Avena et al., 2008). As you will read in Module 5.3 , this basal ganglia–nucleus accumbens network is also related to the pleasurable effects caused by some drugs (Uchimura & North, 1990).
Another major set of forebrain structures comprises the limbic system , an integrated network involved in emotion and memory (Maclean, 1952; see Figure 3.24 ). One key structure in the limbic system is the amygdala , which facilitates memory formation for emotional events, mediates fear responses, and appears to play a role in recognizing and interpreting emotional stimuli, including facial expressions. In addition, the amygdala connects with structures in the nervous system that are responsible for adaptive fear responses such as freezing in position when a possible threat is detected; it is also connected to areas responsible for attention, which is why you usually notice when a spider is on your wall. Just below the amygdala is another limbic structure called the hippocampus (Greek for “seahorse”—something it physically resembles if you’ve
had a few drinks). The hippocampus is critical for learning and memory, particularly the formation of new memories (Squire et al., 2007; see Module 7.1 ).
Figure 3.24 The Limbic System Structures in the limbic system include the hypothalamus, hippocampus, and amygdala, which play roles in regulating motivation, memory, and emotion. Source: Lilienfeld, Scott O.; Lynn, Steven J; Namy, Laural L.; Woolf, Nancy J., Psychology: From Inquiry to Understanding,
Books A La Carte Edtion, 2nd Ed., ©2011. Reprinted and Electronically reproduced by permission of Pearson Education,
Inc., New York, NY.
You already encountered the hypothalamus in Module 3.2 when you read about its relationship to the endocrine system, and you will encounter it again in Module 11.1 when you read about its influence on the regulation of hunger and thirst. The hypothalamus serves as a sort of thermostat, maintaining the appropriate body temperature, and it regulates drives such as aggression and sex by interacting with the endocrine system. In fact, regions of the
hypothalamus trigger orgasm for both females and males (Meston et al., 2004; Peeters & Giuliano, 2007). Direct electrical stimulation of parts of the hypothalamus can produce intense physical pleasure. In a classic set of studies in the 1950s, Olds (1958) found that rats who could press a lever to stimulate the lateral (outside part) of the hypothalamus did so for hours on end, often forgoing food and sleep in order to repeatedly press the lever. In fact, the rats were willing to cross a painful electrical grid in order to reach the lever so that they could
return to stimulating themselves.
Another important, albeit less arousing, forebrain structure is the thalamus , a set of nuclei involved in relaying sensory information to different regions of the brain. Most of the incoming sensory information, including what we see and hear, is routed through specific nuclei in the thalamus. Different types of information are processed by different nuclei before being sent to more specialized regions
of the brain for further processing (Sherman, 2007; Sherman & Guillery, 1996). Many of these regions are found in the outer layer known as the cerebral cortex.
The Cerebral Cortex
The cerebral cortex is the convoluted, wrinkled outer layer of the brain that is involved in multiple higher functions, such as thought, language, and personality. This highly advanced, complex structure has increased dramatically in size as
the primate brain has evolved (Kouprina et al., 2002; see Module 3.1 ). The wrinkled surface of the brain seems to have solved a biological problem endured by our species, as well as by many other mammals: how to pack more cells (i.e., more computing power) into the same amount of space. Because the skull can only be so large, the brain has countered this constraint by forming a wrinkled surface, thereby increasing the surface area of the cortex. More surface area means more neurons and, likely, greater cognitive complexity.
The cerebral cortex consists primarily of the cell bodies and dendrites of neurons; these parts of the neuron give the outer part of the brain a grey-brown colour. The axons of these neurons extend throughout the brain and allow communication between different neural regions to occur. Most of these axons
are wrapped in a white, fatty substance called myelin (see Module 3.2 ), which helps speed up the transmission of neural impulses. Figure 3.25 shows a slice of the brain revealing contrasting light and dark regions, known as white matter and grey matter. When you see an image like Figure 3.25 , it is easy to underestimate the complexity of the brain and its connections. Just to put this image into perspective:
The grey matter of the brain consists of approximately 100 billion neurons
(Drachman, 2005). The white matter of a 20-year-old male brain would extend approximately 176 000 km; for a 20-year-old female brain, it would extend approximately
149 000 km (Marner et al., 2003). Healthy adults have between 100 and 500 trillion synapses, or connections between cells (Drachman, 2005). Each of these synapses can fire several times a second.
That is a considerable amount of computing power.
Figure 3.25 Grey and White Matter of the Brain The cerebral cortex includes both grey matter and white matter, which consist of myelinated axons. Also seen here are the ventricles of the brain. These cavities within the brain are filled with cerebrospinal fluid that provides nourishment and exchange of chemicals with the brain as well as its protective structure. Source: Lilienfeld, Scott O.; Lynn, Steven J; Namy, Laura L.; Woolf, Nancy J., Psychology: From Inquiry To Understanding,
2nd Ed., ©2011. Reprinted And Electronically Reproduced By Permission Of Pearson Education, Inc., New York, NY.
The Four Lobes
In each cerebral hemisphere, the cortex forms the outer surface of four major
areas known as lobes: the occipital, parietal, temporal, and frontal lobes (Figure 3.26 ). Each of the cerebral lobes has a particular set of functions. Nerve cells from each of the four lobes are interconnected, however, and are also networked with regions of the midbrain and hindbrain already described.
Figure 3.26 The Four Lobes of the Cerebral Cortex The cerebral cortex is divided into the frontal, parietal, occipital, and temporal lobes. Source: Lilienfeld, Scott O.; Lynn, Steven J; Namy, Laura L.; Woolf, Nancy J., Psychology: From Inquiry To Understanding,
2nd Ed., ©2011. Reprinted And Electronically Reproduced By Permission Of Pearson Education, Inc., New York, NY.
The occipital lobes are located at the rear of the brain and are where visual information is processed. The occipital lobes receive visual information from the thalamus. After processing this information, they send it out along two different visual pathways, one that projects to the temporal lobes and is involved with object recognition and one that projects to the parietal lobes and is involved with
using vision to guide our movements (Milner & Goodale, 2006).
The parietal lobes are involved in our experiences of touch as well our bodily awareness. At the anterior (front) edge of the parietal lobe is the somatosensory cortex—a band of densely packed nerve cells that register touch sensations. The amount of neural tissue dedicated to a given body part in this region is roughly based on the number of sensory receptors present at each respective body region. For instance, the volume of nerve cells in the somatosensory cortex corresponding to the face and hands is proportionally greater than the volume of cells devoted to less sensitive regions like the torso and legs. This is because we acquire more sensory information from our face and hands than we do from most other body parts; very few people use their stomach when trying to identify objects by touch. This difference in the amount of space in the somatosensory
cortex allocated to different parts of the body is depicted in Figure 3.27 ; figures such as this are referred to as a homunculus or “little man.”
Figure 3.27 The Body as Mapped on the Motor Cortex and Somatosensory Cortex The regions of the motor cortex are involved in controlling specific body parts. The somatosensory cortex registers touch and other sensations that correspond to the body region depicted. Why do you think it is evolutionarily useful to have these two cortices next to each other in the brain? Source: Marieb, Elaine N.; Hoehn, Katja, Human Anatomy And Physiology, 7th Ed., ©2007, p.438. Reprinted And
Electronically reproduced by permission Of Pearson Education, Inc., New York, NY.
Regions within the parietal lobes also function in performing mathematical, visuospatial, and attention tasks. Damage to different regions of the parietal lobe can lead to specific impairments. For instance, right parietal lobe damage can
lead to neglect, a situation in which the patient does not attend to anything that appears in the left half of his or her visual field (Heilman & Valenstein, 1979; Hughlings Jackson, 1876/1932); examples of a neglect patient’s drawings are shown in Figure 3.28 . Neglect can even occur for the left half of the patient’s imagined visual images (Bisiach & Luzatti, 1978)!
Figure 3.28 Unilateral Neglect Patients with damage to the right parietal lobe sometimes show evidence of neglect, a failure to attend to the left half of their visual field.
Source: Republished with permission of British Medical Journal (BMJ Publishing Group), from Hemispatial neglect, J Neurol
Neurosurg Psychiatry, Vol 75, pg 13-21, 2004. Retrieved from http://jnnp.bmj.com/content/75/1/13.abstract?sid=28fd8ac7-
acc2-414c-b0b0-e97478852233 by A Parton, P Malhotra, M Husain. Permission conveyed through Copyright Clearance
Center, Inc.
The temporal lobes are located at the sides of the brain near the ears and are involved in hearing, language, and some higher-level aspects of vision such as object and face recognition. Different sections of the temporal cortex perform different roles. The superior (top) part of the temporal cortex is known as the
auditory cortex—it is essential for our ability to hear. Damage to this region leads to problems with hearing despite the fact that the patient’s ears work perfectly;
this condition is known as cortical deafness (Mott, 1907). Slightly behind this region, near the back of the temporal lobe, is Wernicke’s area, which is related to understanding language (Wernicke, 1874). The close proximity of the hearing and language-comprehension areas makes sense, as these two functions are
closely related (see Module 8.3 for a detailed discussion of language).
Some of the structures on the bottom surface of the temporal lobes have a key role in memory. These brain areas send information about the objects being viewed and their location or context to the hippocampus, a forebrain structure
discussed above (Diana et al., 2007; Eichenbaum et al., 2007). The hippocampus—which is found in the medial or middle portions of the temporal lobes—then sends output to different brain areas, particularly regions of the frontal lobes, showing again that many different areas of the brain work together to produce almost every behaviour we perform.
The frontal lobes are important in numerous higher cognitive functions, such as planning, regulating impulses and emotions, language production, and voluntary movement (Goldman-Rakic, 1996). The frontal lobes also allow you to deliberately guide and reflect on your own thought processes. Like the temporal lobes, the frontal lobes can be divided into a number of subsections with specific
functions (Miller & Cummings, 2007). A key distinction is between areas related to movement and areas related to the control of our mental lives.
Toward the rear of the frontal lobes is a thick band of neurons that form the
primary motor cortex, which is involved in the control of voluntary movement. Like the somatosensory cortex discussed above, the primary motor cortex is organized in a homunculus, with different body areas requiring different amounts
of space (see Figure 3.27 ). Body parts such as the fingers that perform fine- motor control will require more space in the motor cortex than areas like the upper thigh, which does not perform many intricate movements. Importantly, motor areas in the frontal lobes are active not just when moving the corresponding body part, but also when planning a movement. This ability to prepare movements before they are needed would clearly be useful when dealing with threats and likely contributed to our species’ survival.
The front two-thirds of the frontal lobes are known as the prefrontal cortex. This region, which itself can be divided into a number of subsections, performs many of our higher-order cognitive functions such as decision making and controlling our attention. The prefrontal cortex has connections to many of the other brain areas discussed in this module, and appears to help regulate their activity; these
control processes are known as executive functions. Such functions are not always necessary; however, when we encounter new situations or need to override our normal responses, the prefrontal cortex is almost always involved
(Milner, 1963; Stuss & Knight, 2002).
We would obviously like to find ways to strengthen our executive functions. The
Psych@ section on page 111 provides on interesting technique: exercise.
The four lobes of the brain are found in both of our cerebral hemispheres. It is therefore important to have some way for these brain regions to communicate with each other. This prevents us from having our left and right hemispheres
working against each other. In Figure 3.29 , you can see that crossing the midline of the brain is a densely concentrated bundle of nerve cells called the corpus callosum , a collection of neural fibres connecting the two brain hemispheres. This thick band of fibres allows the right and left hemispheres to communicate with each other. This communication has an added benefit: It allows the two hemispheres to work together to produce some of our behaviours. It also opens up the possibility that each hemisphere will become specialized for
performing certain functions.
Figure 3.29 The Corpus Callosum The left and right hemispheres of the brain are connected by a thick band of axons called the corpus callosum. Source: Lilienfeld, Scott O.; Lynn, Steven J; Namy, Laura L.; Woolf, Nancy J., Psychology: From Inquiry To Understanding,
2nd Ed., ©2011. Reprinted And Electronically Reproduced By Permission Of Pearson Education, Inc., New York, NY.
PSYCH@ The Gym Somehow, physical exertion, pain, and breaking down and rebuilding muscle end up making people feel better. But the benefits of exercise do not apply just to one’s mood: Exercise also affects cognitive activities such as learning and memory. But how?
In recent years, neuroscientists have begun unravelling the mystery of how exercise benefits brain health. Brain imaging studies have revealed that people who engage in regular exercise show improved functioning of the prefrontal cortex compared to non-exercisers. In addition, people who exercise perform better than non-exercisers on tasks involving planning,
scheduling, and multitasking (see Davis et al., 2011; Hillman et al., 2008). Animal studies have shown that exercise increases the number of cells in the hippocampus, which is critical for memory, and increases the quantity of brain chemicals that are responsible for promoting cell growth
and functioning (Cotman & Berchtold, 2002). But animals are not the only beneficiaries of an exercise program; similar findings have been reported for elderly people who regularly engage in aerobic exercise
(Erickson et al., 2011).
Despite the clear benefits associated with exercise, many school curricula have dropped physical education in favour of spending more time on preparation for standardized testing. It is not clear that time away from the gym and the playground is having much benefit. A review of 14
studies—12 conducted in the U.S., one in British Columbia (Ahamed et al., 2007), and one in South Africa—found a “significant positive relationship” between physical activity and academic performance
(Singh et al., 2012). This effect may be due to changes in blood flow to the brain, a reduction in stress due to time away from schoolwork, a positive emotional experience associated with play, or, more likely, a combination of several factors. Science is clearly demonstrating that
exercise affects the brain basis of learning and memory (Cotman & Berchtold, 2002; Hillman et al., 2008). These results suggest that provincial governments should increase, not decrease, funding for physical education in schools. Hopefully these studies will help get that
ball rolling.
Left Brain, Right Brain: Hemispheric Specialization
Although they appear to be mirror images of each other, the two sides of the
cortex often perform very different functions, a phenomenon called hemispheric specialization. Speaking in very general terms, the right hemisphere is specialized for cognitive tasks that involve visual and spatial skills, recognition of visual stimuli, and musical processing. In contrast, the left hemisphere is more
specialized for language and math (Corballis, 1993; Gazzaniga, 1967, 2000). However, although some hemispheric differences are quite pronounced, many
are a matter of degree (Springer & Deutsch, 1998).
Our understanding of hemispheric specialization expanded greatly through work
with split-brain patients. In the 1960s, physicians hoping to curtail severe epileptic seizures in their patients used a surgical procedure to treat individuals who were not responding to other therapies. The surgeon would sever the corpus callosum, leaving a patient with two separate cerebral hemispheres. This surgery is not as drastic as it might sound. Patients were remarkably normal after the operation, but several interesting observations were made. One was that split-brain patients responded quite differently to visual input that was presented
to either hemisphere alone (Sperry, 1982).
To see how this works, take a look at Figure 3.30 . Imagine the person pictured has a split brain. She should be able to match the two objects to her
right and verbalize the match, because the left side of her visual system perceives the objects and language is processed in the left hemisphere of the brain. In contrast, a visual stimulus presented on the left side of the body would
be processed on the right side of the brain. As you can see from Figure 3.30 , when the object is presented to the left side of the split-brain patient, the individual does not verbalize which of the objects match, because her right hemisphere is not specialized for language and cannot label the object. If asked to point at the matching object, however, she is able to do so (but only with her left hand, which is controlled by the right hemisphere). Thus, she is able to
process the information using her right hemisphere, but cannot articulate it with language.
Figure 3.30 A Split-Brain Experiment This woman has had a split-brain operation. She is able to verbalize which objects match when they are placed to her right side, because language is processed in the left hemisphere. She cannot verbalize the matching objects on the left, but can identify them by pointing with her left hand (which is controlled by her right hemisphere). Source: Lilienfeld, Scott O.; Lynn, Steven J; Namy, Laura L.; Woolf, Nancy J., Psychology: From Inquiry To Understanding,
2nd Ed., ©2011. Reprinted And Electronically Reproduced By Permission Of Pearson Education, Inc., New York, NY.
Today, split-brain studies are extremely rare, as modern epilepsy medications are often sufficient to treat the symptoms of these patients without the need to sever the corpus callosum. However, the insights gained from these patients still inform our understanding of the brain. It must be stressed, however, that many of these differences are a matter of degree rather than being an absolute one-
hemisphere-or-the-other distinction. Indeed, the reality is that most cognitive functions are spread throughout multiple brain regions, with one hemisphere
sometimes being superior to the other hemisphere (see Table 3.3 ).
Table 3.3 Examples of Hemispheric Asymmetries
Left Hemisphere Right Hemisphere
Language production Visuospatial skills
Language comprehension Prosody (emotional intonation)
Word recognition Face recognition
Arithmetic Attention (rapid orienting to new stimuli)
Moving the right side of the body Moving the left side of the body
Before finishing a discussion of the hemispheres, it is also important to point out that the media often misrepresents how hemispheric specialization works. Terms like “left-brained” and “right-brained” are used quite frequently, with the assumption that left-brained people are rigid-thinking accountants who spend hours counting their grey suits and right-brained people are creative Bohemian artists who flamboyantly wander from experimental art exhibits to melodramatic poetry readings. There are numerous websites that allow you to test yourself on this dimension. However, while these types of characters undoubtedly exist, the degree to which these personalities are linked to different hemispheres is very limited. In fact, neuroimaging studies of personality traits show that characteristics similar to left- and right-brained people (as measured by the
pseudoscientific tests) are distributed across both hemispheres (De Young et al., 2010).
The Changing Brain: Neuroplasticity
In Module 3.2 , you read about stem cells, immature cells whose final role— be it a neuron or a kidney cell—is based on the chemical environment in which it develops. In other words, the cell’s experience (its environment) influenced its physical structure. While fully formed neurons will never have this type of flexibility, brain cells do have a remarkable property called neuroplasticity —the capacity of the brain to change and rewire itself based on individual experience. For example, numerous studies have shown that the occipital lobes of people who are blind are used for non-visual purposes
(Pascual-Leone et al., 2005). This plasticity was beautifully demonstrated in a brain-imaging study using healthy individuals. All participants underwent brain imaging to determine the areas that became active when they performed tasks related to hearing and touch; during this initial phase, the occipital lobes—a region associated with vision—was not active. These participants were then blindfolded for five days before being scanned again. During the second scan session, brain areas normally dedicated to vision became active during touch
and hearing tasks (Pascual-Leone & Hamilton, 2001).
There are numerous other examples of neuroplasticity. For example, experienced musicians develop a greater density of grey matter in the areas of
the motor cortex of the frontal lobe as well as in the auditory cortex (Gaser & Schlaug, 2003). Studies of children have found that individuals who practised an instrument regularly for over two years had a thicker corpus callosum in areas
connecting the left and right frontal and temporal lobes (Schlaug et al., 2009). Even a seemingly silly skill like learning to juggle can influence the thickness of
white-matter pathways connecting different brain areas (Scholz et al., 2009). The key point in all of these studies is that although genetics controls some of your brain’s characteristics, your brain’s connections are not set in stone. What
you do with (and to) your brain can have a dramatic effect on your brain’s connections and thus how your brain functions.
Working the Scientific Literacy Model Neuroplasticity and Recovery from Brain Injury
The fact that neuroplasticity exists makes it seem like recovery from brain damage should be easy—the remaining brain areas should simply rewire themselves to take over the functions of the damaged brain areas. However, it’s not that simple—and we’re lucky it isn’t.
What do we know about neuroplasticity? Some animals with relatively simple brains and spinal cords, such as fish and some amphibians, have a lifelong ability to regenerate damaged areas of their central nervous system. If members of these species suffer a brain or spinal cord injury, they will automatically create new tissue to replace the damaged nerves
(Sperry, 1951, 1956, 1963, 1968). Humans can do this to a limited degree in the peripheral nervous system as well. This is
because chemicals called trophic factors (growth factors) can stimulate the growth of new dendrites and axons. However, the ability of the human brain to recover from damage is more limited. New neurons can form in adulthood, but only in a few regions
such as part of the hippocampus (Eriksson et al., 1998). That means we can’t simply grow a new brain part whenever we’re injured.
Our ability to repair our brains is also limited by the presence of
chemicals that actually inhibit the growth of new axons around an injured area (Yang & Schnarr, 2008). Why would this occur? Researchers suggest that these inhibitory chemicals prevent the brain from forming incorrect connections between brain areas, a result that might produce even larger behavioural problems than
the initial damage itself (Berlucchi, 2011; Kolb et al., 2010). So, if our central nervous system is protecting us against neuroplasticity, how can neuroplasticity be the key to recovering from brain damage?
How can science explain how neuroplasticity contributes to recovery from brain damage?
Although it seems like the brain is preventing its own recovery, there are actually a number of ways that neuroplasticity can work to help patients with brain damage. One possibility is that the same area in the opposite hemi sphere will take over some of the functions of the damaged region. Stunning evidence of this phenomenon has been found in studies of Melodic Intonation
Therapy (MIT; Norton et al., 2009). Researchers have found that some patients with damage to Broca’s area—a part of the left frontal lobe involved with the production of speech—can actually sing using fluent, articulated words, even though they cannot
speak those same words (see Figure 3.31 ). In a study of this technique, patients who had suffered strokes affecting Broca’s area underwent intensive MIT sessions. During these sessions the patients would sing long strings of words using just two pitches, while rhythmically tapping their left hand to the melody.
You can try this out with the help of Figure 3.32 . The patients underwent 80 or more sessions lasting 1.5 hours each day, 5 days per week. Remarkably, this therapy has worked for multiple patients—after these intensive therapy sessions, they typically
regain significant language function (Schlaug et al., 2009). The therapy does not “heal” damaged nerve cells in the left hemisphere at Broca’s area. Rather, language function is taken
over by the corresponding area of the right hemisphere.
Figure 3.31 Brain Specialization
Broca’s area and Wernicke’s area are associated with different aspects of language function. Damage to Broca’s area produces
difficulties in generating speech known as Broca’s aphasia. Source: Lilienfeld, Scott O.; Lynn, Steven J; Namy, Laura L.; Woolf, Nancy J., Psychology: From
Inquiry to Understanding, 2nd Ed., © 2011. Reprinted and electronically reproduced by permission of
Pearson Education, Inc., New York, NY.
Figure 3.32 Musical Intonation Therapy
During musical intonation therapy, patients are asked to sing phrases of increasing complexity. Source: Adapted From Melodic Intonation Therapy, by Nancy Helms-Estabrooks, Marjorie Nicholas,
Alisa R. Morgan 1989, Austin, TX: PRO-ED. Copyright 1989 by PRO-ED, Inc. Adapted with
permission.
Another method that the brain uses to repair itself is the reorganization of neighbouring neural regions. In healthy brains, the distinction between most brain areas is not as clear-cut as it appears on textbook diagrams. For instance, it is common for parts of the somatosensory cortex related to the hand to overlap a bit with regions related to the wrist. If one of those somatosensory areas were damaged, there might still be a small number of neurons associated with that body part preserved in other parts of the nearby cortex. When the brain is damaged, it is thought that these preserved neurons attempt to form new connections. Doing so would allow some sensation to return. This process is enhanced if the doctors force the patient to use the affected brain area as much as possible during rehabilitation
(Mark et al., 2006). Although it seems cruel, patients must remember to “use it or lose it.” In support of this view, research has shown that improvements in a patient’s recovery are linked to
the reorganization of the affected brain area (Pulvermüller & Berthier, 2008).
Can we critically evaluate this research? There are obviously limits to the effects of neuroplasticity. If a patient has damage to a large amount of her brain, it will not be possible for her to return to her normal level of functioning. Additionally, plasticity is more likely to be effective in younger
people, particularly children, than in older adults (Kennard, 1942). Therefore, it is important not to over-generalize the results just discussed. It is also possible that results that seem to be due to neuroplasticity are actually due to some other factor, such as changes in hormone levels, the brain’s metabolism, or growth
factor levels (Knaepen et al., 2010; Sperry, 1968). Although all of these alternative explanations have been tested to some degree in animal studies, it is sometimes difficult to generalize those findings to the human brain. Therefore, much more research is needed before researchers can make any definitive statements about how neuroplasticity helps brain-damaged patients recover.
Why is this relevant? Each year, 40 000–50 000 Canadians suffer strokes (Heart and Stroke Foundation of Canada, 2013) and over 160 000 suffer traumatic brain injuries (e.g., car accidents; Brain Injury Canada, 2016). Over 55 000 Canadians are living with brain tumours (Brain Tumour Foundation of Canada, 2013). Neuroplasticity will occur, to some degree, in the majority of these individuals. It is what will help people regain some of their abilities and some of their independence. Understanding neuroplasticity will improve the care given to patients. It will also inspire new research and
innovative techniques designed to help the brain heal itself (Kim et al., 2010). This research may affect your grandparents or your parents. And eventually, this research may affect you.
Module 3.3b Quiz:
The Brain and Its Structures
Know . . . 1. The ability to hear is based in which of the cerebral lobes?
A. Frontal B. Parietal C. Temporal D. Hypothalamus
Understand . . . 2. Why would a person who has undergone a split-brain operation be
unable to name an object presented to his left visual field, yet be able to correctly point to the same object from an array of choices?
A. Because his right hemisphere perceived the object, but does not house the language function needed for naming it
B. Because the image was processed on his left hemisphere, which is required for naming objects
C. Because pointing is something done with the right hand D. Because the right hemisphere of the brain is where objects are
seen
Apply . . . 3. Damage to the somatosensory cortex would most likely result in which of
the following impairments?
A. Inability to point at an object B. Impaired vision C. Impaired mathematical ability D. Lost or distorted sensations in the region of the body
corresponding to the damaged area
Analyze . . . 4. Which of the following statements best summarizes the results of
experiments on exercise and brain functioning?
A. Both human and animal studies show cognitive benefits of exercise.
B. Animal studies show benefits from exercise, but the results of human studies are unclear.
C. Exercise benefits mood but not thinking. D. Exercise only benefits older people.
Module 3.3 Summary
amygdala
autonomic nervous system
basal ganglia
brainstem
central nervous system (CNS)
cerebellum
cerebral cortex
corpus callosum
forebrain
frontal lobes
hippocampus
limbic system
midbrain
neuroplasticity
Know . . . the key terminology associated with the structure and organization of the nervous system.
3.3a
occipital lobes
parasympathetic nervous system
parietal lobes
peripheral nervous system (PNS)
somatic nervous system
sympathetic nervous system
temporal lobes
thalamus
Studies of split-brain patients were important in that they revealed that the two hemispheres of the brain are specialized for certain cognitive tasks. For example, studies of split-brain patients showed that the left hemisphere was specialized for language. These studies were carried out before other brain-
imaging techniques (see Module 3.4 ) became available.
Apply Activity Review Table 3.2 , which summarizes each of the major brain regions described in this module. Then try to answer the following questions.
1. While at work, a woman suffers a severe blow to the back of her head and then experiences visual problems. Which part of her brain has most likely been affected?
2. If an individual has a stroke and loses the ability to produce speech in clear sentences, what part of the brain is most likely to have been damaged?
Understand . . . how studies of split-brain patients reveal the workings of the brain.
3.3b
Apply . . . your knowledge of brain regions to predict which abilities might be affected when a specific area is injured or diseased.
3.3c
3. If an individual develops a tumour that affects the basal ganglia, what types of behaviours or abilities are likely to be affected?
4. A man suffers a gunshot wound that slightly damages his cerebellum. What problems might he experience (aside from repeatedly asking himself why someone shot him in the head)?
There are many examples of experience changing the structure of the brain. Research suggests that neuroplasticity can also help people recover from brain damage. If the damage is isolated to one cerebral hemisphere, cells in the same region of the opposite hemisphere may be able to take over some of the impaired functions. Additionally, it is possible that some of the cells involved with a function (e.g., sensation of the hand) were undamaged; these remaining cells may form new, stronger connections over the course of rehabilitation.
Analyze . . .whether neuroplasticity will help patients with brain damage.
3.3d
Module 3.4 Windows to the Brain: Measuring and Observing Brain Activity
Sun Media/Splash News/Newscom
Learning Objectives
On March 8, 2011, Boston Bruins’ (giant) defenceman Zdeno Chara dangerously bodychecked Montreal Canadiens’ forward Max Pacioretty into the boards; Pacioretty hit the stanchion, the location where the plexi- glass begins next to the players’ bench. Pacioretty lay motionless on the ice for several minutes with many people in the audience concerned for his life. He was taken off the ice on a stretcher while still unconscious and was rushed to the hospital for a neurological exam. He was diagnosed with a fracture of the 4th cervical vertebra (a bone in the neck) but, luckily, no spinal cord damage; he also had a severe concussion (also known as a mild traumatic brain injury). Injuries such as Pacioretty’s lead to a number of questions for people interested in the biology of behaviour: How can psychologists and medical personnel acquire clear images of a person’s brain for medical or research purposes? Is it possible to map out which brain areas are firing when people are performing a specific task like viewing photographs or memorizing a list of words? And, can scientists learn anything about the healthy brain by studying patients who have suffered brain damage? These topics will be addressed in the current module.
For those interested, Pacioretty made a full recovery, scoring 33 goals for the Canadiens over the course of the next season. Later that year, he won the Bill Masterton Trophy, handed out by the National Hockey League to the player who provides the best example of perseverance, team spirit, and dedication to hockey. He was very, very lucky.
Know . . . the key terminology associated with measuring and observing brain activity. Understand . . . how studies of animals with brain lesions can inform us about the workings of the brain. Apply . . . your knowledge of neuroimaging techniques to see which ones would be most useful in answering a specific research question. Analyze . . . whether neuroimaging can be used to diagnose brain injuries.
3.4a
3.4b
3.4c
3.4d
Focus Questions
1. How can lesions help us learn about the brain? 2. How can we make sense of brain activity as it is actually
occurring?
In Module 3.3 , you read about different brain areas and their functions. This leads to an obvious question: How did researchers find out what these brains areas do? In this module, we will examine the different methods and tools available to physicians and researchers in their quest to map out the functions of different brain areas.
Insights from Brain Damage
Early studies of the brain often involved case studies. A doctor would note a patient’s unique set of symptoms and would then ghoulishly wait for him or her to die so that an autopsy could be performed in order to identify the damaged area. As medical knowledge improved, surgeons began to routinely operate on the brains of patients with neurological problems. This allowed researchers to examine patients before and after brain surgery to see the effect that removing tissue would have on behaviour. However, in each of these cases, insights into the brain were based on individuals who had suffered some sort of trauma or illness. There was no way to test how healthy brains functioned. In the last four decades, advances in brain imaging have changed this, and have allowed researchers to safely measure the brain’s activity.
This is not to say that studying patients with brain damage is not scientifically useful. In fact, quite the opposite is true. The only way researchers can truly hope to understand how the brain works is by using a number of different methods to assess its function.
Lesioning and Brain Stimulation
Studies of patients who have suffered brain damage will appear in a number of modules in this book. The logic of this method is that if a person has part of his or her brain damaged and is unable to perform a particular task (e.g., form new memories), then it is assumed that the damaged structure plays a role in that behaviour. One drawback of studying human patients, however, is that the researcher has no control over where the damage occurs. A stroke generally produces widespread damage; rarely will it harm a single area while leaving the rest of the brain totally unaffected. This diffuse damage makes it difficult for brain researchers to perform controlled studies of patients—each patient will have a unique pattern of damage. It is also difficult to isolate the effects of damage to one brain area when several are affected.
In order to gain more experimental control (and a much larger number of subjects), scientists often create brain damage in animals. This process is known
as lesioning , a technique in which researchers intentionally damage an area in the brain (a lesion is abnormal or damaged brain tissue). Creating lesions allows the researcher to isolate single brain structures. He or she can then study animals with and without lesions to see how specific behaviours are changed by
the removal of that brain tissue. The control subjects are often part of a sham group, a set of animals that go through all of the surgical procedures aside from the lesion itself in order to control for the effects of stress, anesthesia, and the annoyance of stitches. An example of the lesion method is found in studies of spatial learning. Researchers hypothesized that the hippocampus was vital for this ability. In order to test this hypothesis, the researchers lesioned the hippocampus on both sides of the brains of one group of rats and performed sham surgery on the other rats. Each rat was then put into the Morris Water
Maze (Morris, 1981); this device consists of a container filled with an opaque (non-transparent) fluid (see Figure 3.33 ). The rat is placed in the water and must swim around until it finds a small platform hidden under the fluid. At first, the rat finds the platform by chance; over time, the rat learns the location of the platform and swims to it immediately. However, rats with lesions to the hippocampus show a marked impairment in learning the location of the platform,
presumably because the hippocampus is critical for many spatial abilities (Morris
et al., 1982). This example demonstrates the power of the lesion method to determine the roles played by specific brain areas.
Figure 3.33 The Morris Water Maze Tools like the Morris Water Maze allow researchers to test the effects of brain lesions on behaviours such as spatial memory.
Less drastic techniques impair brain activity only temporarily; in fact, some can be safely applied to humans. For instance, researchers can study brain functions
using transcranial magnetic stimulation (TMS) , a procedure in which an electromagnetic pulse is delivered to a targeted region of the brain (Bestmann, 2008; Terao & Ugawa, 2002). This pulse interacts with the flow of ions around the neurons of the affected area. The result is a temporary disruption of brain activity, similar to the permanent disruption caused by a brain lesion. This procedure has the advantage that healthy human volunteers can be studied (as opposed to animals or brain-damaged people, many of whom are elderly). TMS has been used to investigate a number of cognitive processes ranging from
visual perception (Perini et al., 2012) to arithmetic abilities (Andres et al., 2011) to memory for words and abstract shapes (Floel et al., 2004). In each case,
impairments in performance after receiving the TMS “temporary lesion” tell the researcher that the stimulated brain area is likely involved in that cognitive process.
Interestingly, if a weaker electromagnetic pulse is delivered, TMS can also be
used to stimulate, rather than temporarily impair, a brain region (Figure 3.34 ). For example, TMS has been used to increase the activity in the frontal lobes—an area related to planning and inhibiting behaviour—when people were performing a gambling task. This change led the participants to behave in a more cautious, risk-averse manner than when they performed the task without this stimulation
(Fecteau et al., 2007). TMS has also been used to stimulate under-active areas associated with depression, suggesting that this tool has clinical applications as
well (Kluger & Triggs, 2007). In fact, researchers have used this technique to help patients deal with symptoms of disorders ranging from Parkinson’s disease
(Degardin et al., 2012) to movement problems caused by strokes (Corti et al., 2012; Schlaug et al., 2008).
Figure 3.34 Brain Stimulation Transcranial magnetic stimulation involves targeting a magnetic field to a very specific region of the brain. Depending on the amount of stimulation, researchers can temporarily either stimulate or disable the region.
Although lesion work and TMS allow researchers to understand what happens to the brain when certain regions are removed or inactive, these methods don’t provide a picture of the brain’s structures or its patterns of activity. Luckily, there have been astonishing advances in structural and functional neuroimaging over the past forty years.
Module 3.4a Quiz:
Insights from Brain Damage
Know . . . 1. The control group in a typical lesion study is called the
A. metacranial group. B. pseudo-incision group. C. sham group. D. static group.
Understand . . . 2. Why do researchers often use the lesion method instead of studying
humans with brain damage?
A. It is possible to test more subjects using the lesion method. B. Brain damage usually differs between patients. C. The patients usually only have damage in one specific area. D. Both (A) and (B) are true.
Analyze . . . 3. Dr. Cerveau performed a TMS lesion study in her lab. She found that
applying a pulse to the parietal lobes prevented people from pressing a keypad in response to a suddenly appearing image. She concluded that the lesion affected attention. Why should we be cautious of her claim?
A. TMS is not a valid method of lesioning brain areas. B. The TMS lesion covered a large area and may have affected
other functions that might have slowed participants’ responses.
C. Response times are not a valid measure of how people pay attention.
D. All of the above are valid concerns.
Structural and Functional Neuroimaging
Neuroimaging (or brain imaging) is becoming increasingly important for many fields, particularly for psychology. Being able to examine the brains of living people and to measure neural activity while participants perform different tasks provides an astonishing window into the mind. Neuroimaging has also
revolutionized medicine, allowing doctors to see with great precision the size and location of brain injuries. The remainder of this module will focus on the two types of brain scanning: structural and functional neuroimaging.
Structural Neuroimaging
At the beginning of this module, you read about Montreal Canadiens’ forward Max Pacioretty’s scary injury and his surprising return to the National Hockey League. When Pacioretty first arrived at the hospital, the doctors would obviously have wanted to determine the extent of the damage to his brain. In order to get
this information, it was necessary to use structural neuroimaging , a type of brain scanning that produces images of the different structures of the brain. This type of neuroimaging is used to measure the size of different brain areas and to determine whether any brain injury has occurred.
There are three commonly used types of structural neuroimaging. Computerized tomography (or CT scan) is a structural neuroimaging technique in which x-rays are sent through the brain by a tube that rotates around the head. The x-rays will pass through dense tissue (e.g., grey matter) at a different speed than they will pass through less dense tissue, like the fluid in
the ventricles (Hounsfield, 1980). A computer then calculates these differences for each image that is taken as the tube moves around the head and combines
that information into a three-dimensional image (see Figure 3.35 ). As an interesting historical aside, the first commercial CT scanner was created in the early 1970s by EMI (and was called the EMI-Scanner), a company also involved in the music industry. This company had enough money to pay for four years of medical-imaging research because they were also the record label of a band
known as The Beatles (Filler, 2009).
Figure 3.35 Structural Neuroimaging Three different types of structural neuroimaging: (a) a CT scan, (b) an MRI scan, and (c) a diffusion tensor imaging scan. Guy Croft SciTech/Alamy Stock Photo; middle: Steve Smith;
Zephyr/Photo Researchers, Inc./Science Source
CT scans were considered state-of-the-art for over a decade. However, in the 1970s and early 1980s, a new form of structural neuroimaging emerged. Magnetic resonance imaging (or MRI) is a structural imaging technique in which clear images of the brain are created based on how different neural regions absorb and release energy while in a magnetic field. Although this sounds confusing, understanding MRIs involves three steps. First, a brain (or other body part) is placed inside a strong magnetic field; this causes the protons of the brain’s hydrogen atoms to spin in the same direction. Second, a pulse of radio waves is sent through the brain; the energy of this pulse is absorbed by the atoms in the brain and knocks them out of their previous position (aligned with the magnetic field). Finally, the pulse of radio waves is turned off. At this point, the atoms again become aligned with the magnetic field. But, as they do so, they release the energy they absorbed during the pulse. Different types of tissue— grey matter, white matter, and fluid—release different amounts of energy and return to their magnetic alignment at different speeds. Computers are used to calculate these differences and provide a very detailed three-dimensional image
of the brain (Huettel et al., 2009).
As you can see from Figure 3.35 , MRIs produce much clearer images than
CT scans and are more accurate at detecting many forms of damage including
concussions like that suffered by Max Pacioretty (Bazarian et al., 2007). So, why are CT scanners still used? Let’s go back to Pacioretty’s injury. He was hit into a structure that consisted of a thin pad covering metal and plexi-glass, so the chances of him having metal in his brain were quite slim. But what if a person entered the hospital after a car accident? He might have fragments of metal in his body; these would not react well to a powerful magnet. Therefore, CT scans, aside from being cheap, are a safe first-assessment tool for brain injuries. When the doctors have more information about the patient and his injury, then it is possible that the more accurate MRI will be used.
A final type of structural neuroimaging technique is also the newest. Diffusion tensor imaging (or DTI) is a form of structural neuroimaging allowing researchers or medical personnel to measure white-matter pathways in the brain. Although it is natural to assume that the grey matter—the cell bodies—is the most sensitive part of the brain, white-matter damage has been found in an
increasing number of brain disorders (Shenton et al., 2012). This is because most head injuries cause the brain to twist around in the skull. The result is that some of the white-matter pathways connecting different brain areas are torn. A large number of studies have shown that these pathways are damaged in
individuals who have suffered concussions (Niogi & Mukherjee, 2010), although it is unclear whether professional and collegiate/university sports leagues are using this technology when making return-to-play decisions for injured athletes
(J. K. Johnson et al., 2012).
Functional Neuroimaging
Although structural images provide useful information about the brain’s anatomy, they do not tell us much about the functions of those brain areas. This
information is gathered using functional neuroimaging , a type of brain scanning that provides information about which areas of the brain are active when a person performs a particular behaviour. There are a number of different functional neuroimaging methods available to researchers and physicians. A
common trade-off is between temporal resolution (how brief a period of time can be accurately measured) and spatial resolution (a clear picture of the brain).
Which tool is used depends upon the type of question being asked.
A neuroimaging method with fantastic temporal resolution is an electroencephalogram (or EEG) , which measures patterns of brain activity with the use of multiple electrodes attached to the scalp. The neural firing of the billions of cells in the brain can be detected with these electrodes, amplified, and depicted in an electroencephalogram. EEGs measure this activity every millisecond. They can tell us a lot about general brain activity during sleep, during wakefulness, and while patients or research participants are engaged in a particular cognitive activity. EEGs are also used to detect when patients with epilepsy are having a seizure; this would be shown by a sudden spike in activity
(neuronal firing) in one or more brain areas (see Figure 3.36 ). The convenience and relatively inexpensive nature of EEGs, compared to other modern methods, make them very appealing to researchers.
Figure 3.36 Measuring Brain Activity The electroencephalogram measures electrical activity of the brain by way of electrodes that amplify the signals emitted by active regions (left). In clinical conditions such as epilepsy (right), specific EEG measurements will spike. This provides the medical team with information about the origin of the seizure. Steve Smith
Chaikom/Shutterstock
From Figure 2 in Role of EEG in Epilepsy Syndromes in EEG of Common Epilepsy Syndromes by Raj D Sheth, MD.
Copyright © 2016 by Raj D Sheth. Used by permission of Medscape LLC.
But, how can EEG be used to further our understanding of human behaviour? In most studies, researchers would be interested in how brain responses differ for different types of stimuli, such as happy or fearful faces. EEGs have perfect temporal resolution for this task, but they have a problem: How do you link the EEG output (a bunch of squiggly lines) with your stimuli? To do this, researchers
have developed a technique known as event-related potentials (or ERPs). ERPs use the same sensors as EEGs; however, a computer takes note of exactly when a given stimulus (e.g., a smiling face) was presented to the participant. The experimenter can then examine the EEG readout for a brief period of time (usually 1–2 seconds) following the appearance of that stimulus. Importantly, the computer can collect the average brain responses for different types of experimental trials; so, if an experiment contained 50 separate stimulus presentations—25 happy faces and 25 fearful faces—the experimenter could
collect the average pattern of data after each type of stimulus (i.e., there would be one set of squiggly lines for happy faces and one for fearful faces).
Critically, the peaks and valleys of these waveforms are not random—each is associated with some sort of process occurring in the brain. For example, initial
detection of some sort of visual image could occur after 80–120 ms (Mangun et al., 1993); determining that the image was a face might occur at approximately 170 ms (Bötzel et al., 1995). And, identifying that face as someone you know might occur sometime after 300 ms. Researchers can then look at the size of the peaks and valleys to determine whether there was a difference in the amount of brain activity in response to the different stimulus types (e.g., a peak at 200 ms was higher for fearful than for happy faces). This technique can also have clinical uses. If a patient (e.g., someone with multiple sclerosis) was missing an expected waveform, the neurologist could conclude that a particular region of her
brain was not functioning normally (Ruseckaite et al., 2005).
Although ERPs are very useful for measuring when brain activity is occurring, they are much less effective at identifying exactly where that activity is taking place. Part of this problem is due to the fact that the skull disrupts the electrical signal from the neurons’ firing; this reduces the accuracy of ERP measurements. In order to get around this, some researchers measure the magnetic activity associated with cells firing. This is accomplished by using
magnetoencephalography (or MEG) , a neuroimaging technique that measures the tiny magnetic fields created by the electrical activity of nerve cells in the brain. Like EEG, MEG records the electrical activity of nerve cells just a few milliseconds after it occurs, which allows researchers to record brain activity
at nearly the instant a stimulus is presented (Hamalainen et al., 1993). In a study with happy and fearful faces, MEG could measure when an image was
detected and when it was recognized as being a face (Halgren et al., 2000). However, like ERPs, this speed comes with a trade-off; namely, MEGs do not provide a detailed picture of the activity of specific brain areas. So, although its ability to isolate the location of brain activity is slightly better than that of ERPs, it
is still difficult to isolate exactly where in the brain the activity occurred.
A functional imaging method that can show activity of the whole brain is positron emission tomography (or PET) , a type of scan in which a low level of a radioactive isotope is injected into the blood, and its movement to regions of the brain engaged in a particular task is measured. This method works under the assumption that active nerve cells use up energy at a faster rate than do cells that are less active. As a result, more blood will need to flow into those active areas in order to bring more oxygen and glucose to the cells. If the blood contains a radioactive isotope (as in a PET study), more radioactivity will be detected in areas of the brain that were active during that period of time. In most studies, participants will complete separate blocks of trials or even separate scanning sessions for different types of experimental trials. The activity from these sessions is then compared to see which brain areas are more (or less) active in response to different types of stimuli. For instance, researchers at McGill University provided the first evidence that the ventral (bottom) portions of
the right hemisphere of the brain were involved with recognizing faces (Sergent et al., 1992).
The greatest strength of PET scans is that they show metabolic activity of the brain. PET also allows researchers to measure the involvement of specific types of receptors (e.g., types of dopamine receptors) in different brain regions while
people perform an experimental task (e.g., Woodward et al., 2009). A drawback is that PET scans take a long time to acquire—at least two minutes—which is a problem when you want to see moment-by-moment activity of the brain. The
radioactivity of PET also generally limits the participants to men because it is possible that female participants could be in the early stages of pregnancy. In that case, the risks of participating would far outweigh the rewards. Instead, researchers are increasingly turning to a powerful neuroimaging technique with excellent spatial resolution.
PET scans use radioactive isotopes to help identify which areas of the brain were most active. Photo Researchers, Inc./Science Source
Working the Scientific Literacy Model Functional MRI and Behaviour
Functional magnetic resonance imaging (or fMRI ) measures brain activity by detecting the influx of oxygen-rich blood into neural areas that were just active (Kwong et al., 1992; Ogawa et al., 1992). Like PET scanning, fMRI can produce an accurate image of the functional brain. However, its ease of use (and lack of radioactivity) has quickly made it one of the most influential research tools in modern psychology.
What do we know about fMRI and Behaviour?
If you type in “fMRI” into the PubMed.gov research database, you will see that there have been over 30 000 papers published since this technology was developed 25 years ago. The growth in this field is staggering—there are literally hundreds of fMRI research papers published each year. Researchers are using fMRI to study almost every topic discussed in this book, ranging
from sensory processes (Chapter 4 ) to memory (Chapter 7 ) to social behaviours (Chapter 13 ) facet of psychology. Importantly, fMRI is also being used to examine clinical issues
including psychological disorders (Chapter 15 ) and disorders of consciousness (e.g., vegetative states, Module 5.3 ). It is also being used to examine brain activity in neurological patients like Max Pacioretty—psychologists and medical personnel can look at what areas of the brain are active when a person is performing different tasks such as remembering lists of words. If the patterns of activity deviate from those of healthy individuals, then the investigators can infer that specific brain regions are not working properly. With this surge in fMRI research and clinical
use, it is important to examine how fMRI links blood flow to descriptions of behaviour.
How can science explain how fMRI is used to examine behaviour? When a brain area is involved with a particular function, it will use up oxygen. The result is that blood in these areas will be
deoxygenated (without oxygen molecules). The body responds by sending in more oxygen-rich blood to replace the deoxygenated blood. Critically, these two types of blood have different magnetic properties. So, by measuring the changing magnetic properties of the blood in different brain areas, it is possible to see which areas were active when the person
performed a particular task (Huettel et al., 2009; Magri et al., 2012). When you see pictures of different brain areas “lit up,” those colourful areas indicate that more activity occurred in that location during one experimental condition than during another
(see Figure 3.37 ). To continue our example of perceiving faces, researchers could present happy or fearful faces to participants while they were in the fMRI scanner (which is the same machine used for structural MRI scans). After the study, the researchers could look at the average amount of brain activity that occurred when each participant viewed each type of face. In this case, seeing faces would activate a region in the bottom of
the right hemisphere known as the fusiform gyrus (Kanwisher et al., 1997; see Module 4.2 ). Faces expressing fear also would activate the amygdala, and faces expressing happiness activate
a wide network of structures in the frontal lobes (M. L. Phillips et al., 1998). Thus, fMRI provides very detailed images of where brain activity is occurring. Unfortunately, it can only measure activity at the level of seconds rather than milliseconds; therefore,
it lacks the temporal resolution of ERP and MEG (see Table 3.4 ).
Table 3.4 Common Methods of Functional Neuroimaging
Neuroimaging
Method
Advantages Disadvantages
EEG/ERP Excellent temporal Poor spatial resolution
resolution (measures
activity at the
millisecond level);
inexpensive
(does not give a picture
of individual brain
structures)
MEG Excellent temporal
resolution (measures
activity at the
millisecond level)
Poor spatial resolution
(does not give a picture
of individual brain
structures)
PET Provides a picture of
the whole brain
(although not as clear
as fMRI); allows
researchers to examine
activity related to
specific
neurotransmitters (e.g.,
dopamine)
Very poor temporal
resolution (takes at least
2 minutes to scan the
brain, often longer);
involves radioactive
isotopes that limit
possible participants;
very expensive
fMRI Excellent spatial
resolution (clear images
of brain structures)
Temporal resolution is
not as good as ERP or
MEG (it takes
approximately two
seconds to scan the
whole brain)
Figure 3.37 Functional Magnetic Resonance Imaging
Functional MRI technology allows researchers to determine how blood flow, and hence brain activity, changes as study participants or patients perform different tasks. In this image, the coloured areas depict increases in blood flow to the left and right temporal lobes, relative to the rest of the brain, during a cognitive task. Living Art Enterprises/Photo Researchers, Inc./Science Source
Can we critically evaluate this research? Although researchers have shown that the activity that we see in fMRI images is actually linked to the firing of neurons
(Logothetis et al., 2001), we still need to be cautious when
interpreting fMRI data. One reason is that it is correlational in nature. Activity increases or decreases at the same time as different stimuli are perceived; however, we can’t definitively
show that the activity was caused by the stimuli. Also, just because a brain area is active while we perform a task does not mean that it is necessary for that task. It is possible that a given area that “lights up” on fMRI is a small part of a larger network, or performs a supporting role. Therefore, it is useful to look at research using other methods (if available) to see if similar brain areas were implicated in a given behaviour.
There is an additional reason to be cautious of fMRI data. There is a growing trend for neuroimaging, particularly fMRI, to be used to explain or justify phenomena that are not easily measured
(Satel & Lilienfeld, 2013). Images of brains with areas lit up can be found on almost every major online news site. The problem is that many of the claims made in these stories are overstated (more likely, but not always, by the media than by the scientists). Given the massive connections between brain areas, headlines that suggest that scientists have discovered the “hate centre” or
the neural structure associated with how someone will vote are misleading. Most brain areas are activated by many different situations and stimuli. So, just as you would raise your skeptical eyebrows in response to reports of scientists finding the single
gene for a given behaviour (see Module 3.1 ), you should apply your critical-thinking skills toward claims about scientists identifying the single brain area for any complex process.
Why is this relevant? It is difficult to overstate how important fMRI has been to psychological science. It has allowed researchers to map out the networks associated with a huge range of topics, thus providing most of the “bio” components of the biopsychosocial model of behaviour. Recently, researchers at Queen’s University and the University of Manitoba have found ways to perform fMRI on
neurons in the spinal cord (Kornelsen et al., 2013; Stroman, 2005). Thus, it will soon be possible to measure how the entire central nervous system responds to different stimuli, an ability that will allow us to gain a more complete understanding of human behaviour.
Module 3.4b Quiz:
Structural and Functional Neuroimaging
Know . . . 1. The brain-imaging technique that involves measuring blood flow in active
regions of the brain is called
A. magnetic resonance imaging. B. MEG scan. C. PET scan. D. transcranial magnetic stimulation.
Understand . . . 2. Which of the following techniques does not provide an actual picture of
the brain?
A. PET scan B. MRI C. Electroencephalogram (EEG) D. fMRI
Apply . . . 3. A neuroscientist was interested in identifying the precise brain areas
involved when women see photographs of their loved ones. Which functional neuroimaging technique would be the most useful in identifying these regions?
A. fMRI
B. MRI C. Transcranial magnetic stimulation (TMS) D. CT scan
Analyze . . . 4. A drawback of PET scans compared to newer techniques, such as
magnetoencephalography, is that
A. PET is slower, which means it is more difficult to measure moment-to-moment changes in brain activity.
B. PET is faster, which makes it difficult to figure out how brain activity relates to what someone sees or hears.
C. PET is too expensive for research use. D. PET is slower, and it does not provide a picture of the brain.
Module 3.4 Summary
computerized tomography (CT) scan
diffusion tensor imaging (DTI)
electroencephalogram (EEG)
functional magnetic resonance imaging (fMRI)
functional neuroimaging
lesioning
magnetic resonance imaging (MRI)
magnetoencephalography (MEG)
positron emission tomography (PET)
structural neuroimaging
transcranial magnetic stimulation (TMS)
Know . . . the key terminology associated with measuring and observing brain activity.
3.4a
Researchers have learned a great deal from studies of neurological patients; however, because most accidental brain damage is spread out across many
structures, it is difficult to determine the effect of damage to a particular structure. Lesion studies with animals allow researchers to address this type of question by intentionally damaging a very specific region of the brain. These studies also allow researchers to test far more subjects than they could if they were testing humans with brain damage; therefore, animal lesion studies allow researchers to answer more questions than would otherwise be possible.
Apply Activity Review Table 3.4 , which summarizes each of the major types of functional neuroimaging. Then decide which one should be used to answer each of the following research questions.
1. Lynn was an epilepsy patient seeking treatment. Her seizures did not involve the muscle twitches typical of grand mal seizures. Instead, she would stop talking and stare blankly into the distance for 20–30 seconds (this is known as a petit mal seizure). Her neurologist wanted to use a neuroimaging method to detect when she was having a seizure. Which one should she use?
2. Neil was interested in how dopamine neurons in the brain responded when participants were given rewarding foods like jelly beans versus bland foods. Which functional neuroimaging method should he use to answer his question?
3. Jen wanted to measure the precise brain areas that were active when people experienced pain. Which neuroimaging method would give her this information?
Understand . . . how studies of animals with brain lesions can inform us about the workings of the brain.
3.4b
Apply . . . your knowledge of neuroimaging techniques to see which ones would be most useful in answering a specific research question.
3.4c
4. Jason was interested in how people pay attention to more than one stimulus at the same time. He wanted to measure brain responses within the first half second after images were flashed on a computer screen. Which method(s) would allow him to answer his research question?
Several methods for measuring brain activity were covered in this module. A CT scan can provide an initial picture of the brain; this is used most often when a patient first enters the hospital. If a more detailed image is necessary and the patient does not have metal fragments in his body, then MRI is used. If researchers are particularly interested in diagnosing white-matter damage, diffusion tensor imaging (DTI) may be used as well. Additionally, any of the functional imaging methods discussed in this module could show different patterns of activity for individuals with and without brain damage, depending upon the task being performed and the location of the injury.
Analyze . . . whether neuroimaging can be used to diagnose brain injuries.
3.4d
Chapter 4 Sensation and Perception
4.1 Sensation and Perception At a Glance Sensing the World Around Us 127
Module 4.1a Quiz 132
Perceiving the World Around Us 132
Working the Scientific Literacy Model: Backward Messages in Music 134
Module 4.1b Quiz 137
Module 4.1 Summary 137
4.2 The Visual System The Human Eye 140
Module 4.2a Quiz 146
Visual Perception and the Brain 146
Working the Scientific Literacy Model: Are Faces Special? 148
Module 4.2b Quiz 154
Module 4.2 Summary 155
4.3 The Auditory and Vestibular Systems Sound and the Structures of the Ear 157
Module 4.3a Quiz 159
The Perception of Sound 160
Working the Scientific Literacy Model: The Perception of Musical Beats 162
Module 4.3b Quiz 163
The Vestibular System 164
Module 4.3c Quiz 165
Module 4.3 Summary 165
4.4 Touch and the Chemical Senses The Sense of Touch 168
Working the Scientific Literacy Model: Empathy and Pain 171
Module 4.4a Quiz 173
The Chemical Senses: Taste and Smell 173
Module 4.4b Quiz 176
Multimodal Integration 176
Module 4.4c Quiz 178
Module 4.4 Summary 178
Module 4.1 Sensation and Perception at a Glance
Martin Philbey/Redferns/Getty Images
Learning Objectives
Know . . . the key terminology of sensation and perception. Understand . . . what stimulus thresholds are. Understand . . . the principles of Gestalt psychology. Apply . . . your knowledge of signal detection theory to identify hits, misses, and correct responses in examples.
4.1a 4.1b 4.1c 4.1d
In December 1985, 18-year-old Ray Belknap shot himself to death in Reno, Nevada. His friend, James Vance, attempted to do the same but survived, his face forever scarred by the shotgun blast. Vance later claimed that his actions were influenced by “subliminal messages” found in the heavy metal music of the band Judas Priest. His family sued the band for damages. The prosecution claimed that when played backwards, the song “Better by You, Better Than Me” contained the phrase “do it.” This phrase was allegedly perceived by the two youths, prompting them to attempt suicide. Although this claim seems outlandish, it led to lengthy legal proceedings and received heavy media coverage. It took the work of two Canadian psychologists to demonstrate that these allegations were unfounded. Their research, described later in this module, demonstrates the importance of scientific literacy and provides interesting insights about the abilities—and limitations—of our perceptual systems.
Focus Questions
1. What is the difference between sensation and perception? 2. What are the principles that guide perception?
Sensation and perception are different, yet integrated processes. To illustrate
this point, take a look at the Necker cube in Figure 4.1 . After staring at it for several seconds, the cube may appear to flip its orientation on the page (the side that looks like an interior wall at the back of the cube can also look like the exterior side of the front of the cube). Although the cube remains constant on the page and in the way it is reflected in the eye, it can be perceived in different ways. The switching of perspectives is a perceptual phenomenon that takes place in the brain.
Analyze . . . claims that subliminal advertising and backward messages can influence your behaviour.
4.1e
Figure 4.1 The Necker Cube Stare at this object for several seconds until it changes perspective. Source: Based on Galanter, E. (1962). Contemporary psychophysics. In R. Brown, E. Galanter, E. H. Hess, & G. Mandler
(Eds.), New Directions in Psychology (p. 231). New York: Holt, Rinehart, & Winston.
Sensing the World Around Us
The world outside of the human body is full of light, sound vibrations, and objects we can touch. A walk through campus can be filled with the moving shadows of towering elm trees, the sounds of birds chirping, and the cool crisp air of an autumn morning. In order to make sense of all this information, the body has developed an amazing array of specialized processes for sensing and perceiving the world around us. The process of detecting and then translating the complexity of the world into meaningful experiences occurs in two stages.
The first step is sensation , the process of detecting external events with sense organs and turning those stimuli into neural signals. At the sensory level, the sound of someone’s voice is simply air particles pushing against the
eardrum, and the sight of a person is merely light waves stimulating receptors in the eye. All of this raw sensory information is then relayed to the brain, where
perception occurs. Perception involves attending to, organizing, and interpreting stimuli that we sense. Perception includes organizing the different vibrations of the eardrum in a way that allows you to recognize them as a human voice and linking together the stimulation of groups of receptors in the eye into the visual experience of seeing someone walking toward you.
The raw sensations detected by the sensory organs are turned into information
that the brain can process through transduction , when specialized receptors transform the physical energy of the outside world into neural impulses. These neural impulses travel into the brain and influence the activity of different brain
structures, which ultimately gives rise to our internal representation of the world.
The sensory receptors involved in transduction are different for the different
senses (summarized in Table 4.1 ). The transduction of light occurs when it reaches receptors at the back of the eye; light-sensitive chemicals in the retina then convert this energy into nerve impulses that travel to numerous brain centres where colour and motion are perceived and objects are identified (see Figure 4.2 ). The transduction of sound takes place in a specialized structure in the ear called the cochlea, where sound energy is converted into neural impulses that travel to the hearing centres of the brain.
Table 4.1 Stimuli Affecting Our Major Senses and Corresponding Receptors
Sense Stimuli Type of Receptor
Vision
(Module
4.2 )
Light waves Light-sensitive structures at the back of
the eye
Hearing
(Module
4.3 )
Sound waves Hair cells that respond to pressure
changes in the ear
Touch
(Module
4.4 )
Pressure, stretching,
warming, cooling or piercing
of the skin surface
Different types of nerve endings that
respond to pressure, temperature
changes, and pain
Taste
(Module
4.4 )
Chemicals on the tongue and
in the mouth
Cells lining the taste buds of the tongue
Smell
(Module
4.4 )
Chemicals contacting mucus-
lined membranes of the nose
Nerve endings that respond selectively
to different compounds
Figure 4.2 From Stimulus to Perception Sensing and perceiving begin with the detection of a stimulus by one of our senses. Receptors convert the stimulus into a neural impulse, a process called transduction. Our perception of the stimulus takes place in higher, specialized regions of the brain.
The brain’s ability to organize our sensations into coherent perceptions is remarkable. All of our senses use the same mechanism for transmitting
information in the brain: the action potential (see Module 3.2 ). As a result, the brain is continually bombarded by waves of neural impulses representing the
world in all its complexity; yet, somehow, it must be able to separate different sensory signals from one another so that we can experience distinct sensations —sight, sound, touch, smell, and taste. It accomplishes this feat by sending signals from different sensory organs to different parts of the brain. Therefore, it is not the original sensory input that is most important for generating our perceptions; rather, it is the brain area that processes this information. We see because visual information gets sent to the occipital lobes, which generate our experience of vision. We hear because auditory information gets sent to our
temporal lobes, which generate our experience of hearing. This idea, that the different senses are separated in the brain, was first proposed in 1826 by the German physiologist Johannes Müller and is known as the doctrine of specific nerve energies .
Although this separation seems perfectly logical, it requires that distinct pathways connect sensory organs to the appropriate brain structures. Interestingly, these pathways are not fully distinct in the developing brain. Researchers at McMaster University have demonstrated that infants have a
number of overlapping sensations (Maurer & Maurer, 1988; Spector & Maurer, 2009). For instance, spoken language elicits activity in areas of the brain related to hearing, but also in brain areas related to vision. This effect does not
disappear until age 3 (Neville, 1995). As children age, the pathways in their brains become more distinct, with less-useful connections being pruned away. Thus, perception is a skill that our brains learn through experience.
Experience also influences how we adapt to sensory stimuli in our everyday lives. Generally speaking, our sensory receptors are most responsive upon initial exposure to a stimulus. For example, when you first walk out of a building onto a sidewalk beside a busy street, the sound from the traffic and the bright sunlight initially seem intense. This feeling occurs because both the sensory receptors and brain areas related to perception are extremely sensitive to change. The
orienting response describes how we quickly shift our attention to stimuli that signal a change in our sensory world.
The flip side of this ability is that we allocate progressively less attention to stimuli that remain the same over time; these unchanging stimuli elicit less
activity in the nervous system and are perceived as being less intense over time. So, the sound of traffic or the light outside will seem less intense after a few minutes than it did when you first exited the building. This process is known as sensory adaptation , the reduction of activity in sensory receptors with repeated exposure to a stimulus. Sensory adaptation provides the benefit of allowing us to adjust to our surroundings and shift our focus to other events that may be important. However, there are also drawbacks to sensory adaptation. We often get used to listening to loud music in our ear-bud headphones, which can eventually damage the auditory system. We also stop noticing how polluted and loud city life can be, even though both factors can influence our stress levels and
overall health (Evans, 2003).
There is a real-world example of sensory adaptation that most of us experience every day. Watch television for 5–10 minutes; but, rather than follow the plot of the show, pay attention to how many times the camera angle changes. Directors change the camera angle (and thus your sensation and perception) every few seconds in order to prevent you from experiencing sensory adaptation. The image on the screen will change from wide-angle shots to close-ups of different actors, and that change stimulates your orienting response, making it difficult for you to look away. Whether this over-exposure to rapidly changing stimuli is having a permanent effect on our brains—particularly the developing brains of
children—is a hotly debated issue in current psychological research (Bavelier et al., 2010; Healy, 2004).
Sensory adaptation is one process that accounts for why we respond less to a repeated stimulus—even to something that initially seems impossible to ignore. Flashon Studio/Shutterstock
Stimulus Thresholds
How loud does someone have to whisper for you to hear that person? If you touch a railroad track, how sensitive are your fingers to vibrations from a distant train? How does your hearing or sense of touch compare to other people that you know? Are they more or less sensitive? One early researcher, William Gustav Fechner (1801–1887), was fascinated by such questions. Fechner was a German physicist who was interested in vision. In 1839, he developed an eye disorder that forced him to resign from his academic position. He later recovered, but the experience of having impaired vision—and the effects this had on his thoughts and actions—changed the focus of his research. Fechner helped to
create psychophysics , the field of study that explores how physical energy such as light and sound and their intensity relate to psychological experience. A popular approach was to measure the minimum amount of a stimulus needed for detection, and the degree to which a stimulus must change in strength for the change to be perceptible to people.
See if you can estimate human sensory abilities in the following situations (based
on Galanter, 1962):
If you were standing atop a mountain on a dark, clear night, how far away do you think you could detect the flame from a single candle?
How much perfume would need to be spilled in a three-room apartment for you to detect the odour?
On a clear night, a candle flame can be detected 50 km away. One drop of perfume is all that is needed for detection in a three-room apartment (so no need to douse yourself in perfume or aftershave!). Each of these values represents an absolute threshold —that is, the minimum amount of energy or quantity of a stimulus required for it to be reliably detected at least 50% of the time it is presented (Figure 4.3 ). For example, imagine an experimenter asked you to put on headphones and listen for spoken words; however, she manipulated the volume at which the words were presented so that some could be heard and some could not. Your absolute threshold would be the volume at which you could detect the words 50% of the time. But, your absolute threshold might differ from the person beside you—the minimum amount of pressure, sound, light, or chemical required for detection varies among individuals and across the lifespan. There are also large differences across species. The family dog may startle, bark, and tear for the door before you can even detect a visitor’s approach, and a cat can detect changes in shadows and light that go unnoticed by humans. There is no magic or mystery in either example: These animals simply have lower absolute thresholds for detecting sound and light.
Figure 4.3 Absolute Thresholds The absolute threshold is the level at which a stimulus can be detected 50% of the time.
Another measure of perception refers to how well an individual can detect
whether a stimulus has changed. A difference threshold is the smallest difference between stimuli that can be reliably detected at least 50% of the time. When you add salt to your food, for example, you are attempting to cross a difference threshold that your taste receptors can register. Whether you actually
detect a difference, known as a just noticeable difference, depends primarily on the intensity of the original stimulus. The more intense the original stimulus, the larger the amount of it that must be added for the difference threshold to be reached. For example, if you add one pinch of salt to a plate of french fries that already had one pinch sprinkled on them, you can probably detect the difference. However, if you add one pinch of salt to fries that already had four pinches applied, you probably will not detect much of a difference. Apparently, to your senses, a pinch of salt does not always equal a pinch of salt.
This effect was formalized into an equation by Ernst Weber (1795–1878), a
German physician and one of the founders of psychophysics. Weber’s law
states that the just noticeable difference between two stimuli changes as a proportion of those stimuli. Imagine you’re holding 50 g of candy in your hand.
You may not notice if one gram of candy is added; instead, let’s say that the just noticeable difference is five grams (i.e., you can tell the difference between 50 g and 55 g of candy). Now let’s imagine that your friend hands you 100 g of candy. Again, she starts adding candy to your hand to see when you’ll notice a change. Weber’s law would suggest that the just noticeable difference would be 10 g. If the just noticeable difference of 50 g is 5 g, and if 100 g is 50 g doubled, then the just noticeable difference of 100 g should be 5 g doubled: 10 g.
The study of stimulus thresholds has its limitations. Whether someone perceives a stimulus is determined by self-report—that is, by an individual reporting that she either did or did not detect a stimulus. But, not all people are equally willing to say they sensed a weak stimulus. Some people may wait until they are 100% certain that a candle was viewed, whereas other people may claim to see a faint candlelight just because they expect to see it. This concept has real-world implications. Think of a radiologist trying to detect tumours in a set of images: If there are differences in the absolute threshold of different radiologists, then one might miss tumours that others would detect. But, this scenario is even more complex—different radiologists might be more or less likely to report seeing a tumour when they are unsure of what they have seen. How do we confirm whether these stimuli were truly perceived or whether the individuals were just guessing?
Signal Detection
If you are certain that a stimulus exists (e.g., you were hit in the face with a soccer ball), then there is no reason to worry about whether you did or did not perceive something. However, there are many instances in which we must make decisions about sensory input that is uncertain, as in the previous example of a radiologist. It is in these ambiguous situations that signal detection theory can be
a powerful tool for the study of our sensory systems. Signal detection theory
states that whether a stimulus is perceived depends on both the sensory experience and the judgment made by the subject. Thus, the theory requires us to examine two processes: a sensory process and a decision process. In a typical signal detection experiment conducted in the laboratory, the experimenter
presents either a faint stimulus or no stimulus at all; this is the sensory process.
The subject is then asked to report whether or not a stimulus was actually
presented; this is the decision process.
In developing signal detection theory, psychologists realized that there are four
possible outcomes (see Figure 4.4 ). For example, you may be correct that you heard a sound (a hit), or correct that you did not hear a sound (known as a correct rejection). Of course, you will not always be correct in your judgments. Sometimes you will think you heard something that is not there; psychologists
refer to this type of error as a false alarm. On other occasions you may fail to detect that a stimulus was presented (a miss). By analyzing how often a person’s responses fall into each of these four categories, psychologists can accurately measure the sensitivity of that person’s sensory systems.
Figure 4.4 Signal Detection Theory Signal detection theory recognizes that a stimulus is either present or absent (by relying on the sensory process) and that the individual either reports detecting the stimulus or does not (the decision process). The cells represent the four possible outcomes of this situation. Here we apply signal detection theory to a man alone in the woods.
Studies using signal detection theory have shown that whether a person can accurately detect a weak stimulus appears to depend on a number of factors
(Green & Swets, 1966). First among these is the sensitivity of a person’s sensory organs. For instance, some people can detect tiny differences in the tastes of spicy foods, whereas other people experience them all as “hot.” In addition to these objective differences, there are also a number of cognitive and emotional factors that influence how sensitive a person is to various sensory stimuli. These include expectations, level of psychological and autonomic- nervous-system arousal, and how motivated a person is to pay attention to nuances in the stimuli. If you were lost in the woods, your arousal level would be quite high. You would likely be better able to notice the sound of someone’s voice, the far-off growl of a bear, or the sound of a car on the road than you would be if you were hiking with friends on a familiar trail—even if the surrounding noise level was the same. Why does this difference in sensitivity occur? Is it due to enhanced functioning of your ears (the sensory process) or due to you being more motivated to detect sounds (the decision process)? Research shows that motivational changes are likely to affect the decision process so that you assume that every snapping twig is a bear on the prowl. This change in sensitivity has obvious survival value.
Myths in Mind Setting the Record Straight on
Subliminal Messaging Do you think that messages presented to you so rapidly that you couldn’t consciously see them would still influence your behaviour? In the 1950s, a marketing researcher named James Vicary suggested such persuasion can indeed occur. Vicary claimed that by presenting the messages “Eat popcorn” and “Drink Coca-Cola” on a movie screen, he was able to increase the sales of popcorn and Coke at the theatre. Although later exposed as a hoax, Vicary’s claims received a great deal of attention from both the public and the CIA and spawned a huge subliminal self-
help industry. But, does subliminal perception—meaning perception
below the threshold of conscious awareness—really exist? And if so, can it really control our motivations, beliefs, and behaviours?
Numerous companies selling subliminal self-help products would like you to believe so. However, research by Canadian psychologists suggests
that these claims may be inaccurate. For example, Merikle and Skanes (1992) tested the usefulness of subliminal weight-loss tapes. Female participants were randomly assigned to one of three experimental conditions: (1) subliminal weight-loss tapes, (2) subliminal tapes for the reduction of dental anxiety, and (3) a wait list (no tapes). The women were weighed before and after a six-week period to see if the tapes affected weight loss. The researchers found no difference between the three groups, suggesting that the tapes were entirely ineffective.
A similar study by American researchers suggests that even if some
improvement were to occur after participants heard subliminal tapes, these effects may be due to the participants’ expectations (Greenwald et al., 1991). In this study, participants were given subliminal cassettes that supposedly improved memory or improved self-esteem. Importantly, the labels on the tapes varied such that half of the participants received the correct cassette–label pairing (e.g., a memory cassette with a memory label) and half received the opposite (e.g., a memory cassette with a self- esteem label). Testing conducted after one month of use showed no effects based on the content of the cassettes. However, there was a general overall improvement in all conditions, suggesting that simply being in an experiment helped both self-esteem and memory (a result
similar to the Hawthorne effect discussed in Module 2.1 ). Importantly, there was also a trend for participants to believe that the cassettes had produced the desired effect—but this perceived improvement was for the
ability that was on the cassette’s label, not necessarily what the participants actually heard. In other words, their expectations led them to believe that they had improved an ability even though they hadn’t received any subliminal help for that ability (i.e., a placebo effect).
The allure of subliminal self-help programs is that individuals can improve themselves without putting forth any effort—the subliminal messages will do the changing for the person. Unfortunately, psychological studies suggest that such effects are due more to the individual’s expectations than to subliminal perception. Fuse/Corbis/Getty Images
So far, we have described research about stimuli that individuals consciously perceive. What about information that stimulates the sensory organs but is too weak to reach conscious awareness? Could such weak stimuli still influence our behaviour, thoughts, and feelings? How could we accurately assess such a phenomenon? These questions abound when discussing the myths—and the realities—of subliminal perception.
Priming and Subliminal Perception
The fact that subliminal self-help tapes are unlikely to turn you into a multilingual genius with washboard abs does not mean that all subliminal perception is a
hoax. We can, in fact, perceive subliminal stimuli under strict laboratory conditions. Most laboratory-based studies use a technique known as priming, in
which previous exposure to a stimulus can influence that individual’s later responses, either to the same stimulus or to one that is related to it. Indeed, priming by subliminally presented stimuli has been demonstrated time and again
in cognitive psychology experiments (Van den Bussche et al., 2009). In this type of study, experimenters often present a word or an image for a fraction of a second. This presentation is then immediately followed by another image, known
as a mask, which is displayed for a longer period of time. The mask interferes with the conscious perception of the “subliminal” stimulus—the perceivers are
often unaware that any stimulus appeared before the mask (e.g., Cheesman & Merikle, 1986). Yet, a number of brain imaging studies have shown that these rapidly presented stimuli do in fact influence patterns of brain activity (Critchley et al., 2000). Thus, it appears that subliminal perception can occur, and it can produce small effects in the nervous system.
It is important to note that subliminal priming is unlikely to create motivations that hadn’t previous existed, a grave concern of many people in the 1950s and 1960s. At best, such messages might enhance a motivation or goal that we already have. Erin Strahan and her colleagues at the University of Waterloo examined whether subliminally primed words related to thirst would differentially
affect thirsty and non-thirsty viewers (Strahan et al., 2002). They found that after viewing thirst-related subliminal stimuli (the words “thirst” and “dry”), thirsty participants drank more of a beverage and rated it more positively than did non- thirsty participants (who were not influenced by the subliminal words). No group difference was found when the subliminally presented words were not thirst- related. These results demonstrate that although subliminally primed words can
activate an already existing motivational state, they cannot create a new motivational state.
Module 4.1a Quiz:
Sensing the World Around Us
Know . . . 1. is the study of how physical events relate to psychological
perceptions of those events.
A. Sensation B. Sensory adaptation C. Perception D. Psychophysics
Understand . . . 2. The minimum stimulation required to detect a stimulus is a(n) ,
whereas the minimum required to detect the difference between two
stimuli is a(n) . A. just noticeable difference; difference threshold B. absolute threshold; difference threshold C. difference threshold; absolute threshold D. just noticeable difference; absolute threshold
3. Signal detection theory improves on simple thresholds by including the influence of
A. psychological factors, such as a willingness to guess if uncertain. B. engineering factors, such as how well a set of speakers is
designed.
C. whether an individual has hearing or visual impairments. D. the actual intensity of the stimulus.
Apply . . . 4. Walking on a crowded downtown sidewalk, Ben thinks he hears his name
called, but when he turns around, he cannot find anyone who might be speaking to him. In terms of signal detection theory, mistakenly believing
he heard his name is an example of a . A. hit B. miss C. bogus hit D. false alarm
Analyze . . . 5. Is it reasonable to conclude that subliminal messages have a strong
effect on behaviour?
A. No, research shows that they have no effect whatsoever. B. No, although research shows they might have mild effects. C. Yes, the research shows that subliminal ads are powerful. D. Conclusions about subliminal messages have not been reached
by psychologists.
Perceiving the World Around Us
The study of thresholds, signal detection, and subliminal perception has given us answers to many basic questions about how we sense and perceive our environment. But, how do we actually form perceptions from all of this sensory information? The attempt to answer this question has a rich history in psychology, taking us back to the first half of the 20th century.
Gestalt Principles of Perception
In 1910, Max Wertheimer was riding on a train from Vienna, Austria, to Frankfurt, Germany. As he stared out the window at the Central European countryside, he noticed that the buildings in the distance appeared to be moving backwards. Wertheimer was intrigued by this obvious illusion, and decided to investigate the experience when he arrived in Frankfurt later that day. That evening, he bought himself a stroboscope, a toy that displayed pictures in rapid succession. He noticed that individual pictures did not move; but, when presented within a fraction of a second of each other, the individual images created the perception of movement. This simple observation had an astounding impact on the study of perception, and led to the development of the Gestalt school of psychology.
Gestalt psychology is an approach to perception that emphasizes that “the whole is greater than the sum of its parts.” In other words, the individual parts of an image may have little meaning on their own, but when combined, the whole takes on a significant perceived form. Gestalt psychologists identified several key principles to describe how we organize features that we perceive.
One basic Gestalt principle is that objects or “figures” in our environment tend to stand out against a background. Gestalt psychologists refer to this basic
perceptual rule as the figure–ground principle. The text in front of you is a figure set against a background, but you may also consider the individual letters you see to be figures against the background of the page. This perceptual tendency is particularly apparent when the distinction between figure and ground is
ambiguous, as can be seen in the face–vase illusion in Figure 4.5 (a). Do you see a vase or two faces in profile? At the level of sensation, there is neither a vase nor two faces—there is just a pattern. What makes it a perceptual illusion is the recognition that there are two objects, but there is some ambiguity as to which is figure and which is ground. The figure–ground principle applies to hearing as well. When you are holding a conversation with one individual in a crowded party, you are attending to the figure (the voice of the individual) against the background noise (the ground). If the person you are speaking with is uninteresting, you may attend to the music instead of what he or she is saying to you. In this case, the music would become the figure and the droning voice would become the ground. Exactly which object is the figure and which is the ground at any given moment therefore depends on many factors, including what you are motivated to pay attention to.
Figure 4.5 Gestalt Principles of Form Perception (a) Figure and ground. (b) Proximity helps us group items together so that we
see three columns instead of six rows. (c) Similarity occurs when we perceive the similar dots as forming alternating rows of yellow and red, not as columns of alternating colours. (d) Continuity is the tendency to view items as whole figures even if the image is broken into multiple segments. (e) Closure is the tendency to fill in gaps so as to see a whole object.
Animals and insects take advantage of figure–ground ambiguity to camouflage themselves from predators. Can you see the walking stick insect in this photo? Brian Lasenby/123RF
Proximity and similarity are two additional Gestalt principles that influence perception. We tend to treat two or more objects that are in close proximity to each other as a group. Because of their proximity, people standing next to each other in a photograph are assumed to be a group. Similarity can be experienced by viewing groups of people in uniform, such as two different teams on a soccer
field or police facing off against protesters at the 2010 G20 Summit in Toronto. We tend to group together individuals wearing the same uniform based on their visual similarity.
Some other key Gestalt principles are also illustrated in Figure 4.5 . Continuity, or “good continuation,” refers to the perceptual rule that lines and other objects tend to be continuous, rather than abruptly changing direction. The black object snaking its way around the white object is viewed as one continuous
object rather than as two separate ones. A related principle, called closure, refers to the tendency to fill in gaps to complete a whole object.
The principle of similarity in action. We perceive groups of police (who are dressed similarly) and protesters, rather than hundreds of individuals. Christian Lapid/The Canadian Press
It is important to note that Gestalt concepts are not simply a collection of isolated examples. Rather, when put together, they demonstrate an incredibly important characteristic of the perceptual system: we create our own organized perceptions out of the different sensory inputs that we experience. The next time
you go outside, look at how we create organized perceptions of architecture, interior design, fashion, and even corporate logos. All of these examples show how much of “you” is in your perceptual experience of the world.
The illusions and figures you have viewed in this section reveal some common principles that guide how we perceive the world. We can take this exploration a step further by discussing the cognitive processes that underlie these principles, a topic that brings us back to the controversial court case discussed at the beginning of this module.
Working the Scientific Literacy Model Backward Messages in Music
Humans are experts at pattern recognition. This ability to detect patterns is the basis for our ability to understand speech. To newborn babies, speech is a series of nonsense sounds. With experience, we are able to group together different sounds, which leads to the perception of spoken words. But, how sophisticated are these pattern-recognition abilities? This question is central to the issue of backward messages in music.
What do we know about backward messages in music? The idea that music can contain backward messages has a long history. Fans have reported finding evidence of these messages in a few songs from The Beatles. “Messages” have also been found in 1970s songs by Led Zeppelin and Queen. For example, when Queen’s song “Another One Bites the Dust” is played backwards, some listeners claim to hear “It’s fun to smoke marijuana.” However, most examples of backward messages are
due to phonetic reversal, where a word pronounced backwards sounds like another word (e.g., dog and god). Indeed, in most cases, the bands claim to be unaware that any backward
messages exist (although a few bands, such as Pink Floyd, intentionally inserted messages, oftentimes to poke fun at conspiracy theorists).
Importantly, until the 1980s, few people believed that these
messages could be perceived when the music was played forward (i.e., properly), let alone that these messages could
influence people’s behaviour. This changed with the Judas Priest lawsuit discussed at the beginning of this module. In that case, the prosecution claimed that “backward messages” in the music caused two boys to attempt suicide. Could psychology research explain whether these claims were valid?
How can science explain backward messages?
John Vokey and Don Read (1985) from the University of Lethbridge conducted a series of studies that related to the backward messages controversy. These researchers recorded a number of passages onto audio cassettes and then played the cassettes backwards for participants. They found that people could make superficial judgments about the gender of the speaker (98.9% correct), about whether two speakers were the same (78.5% correct), and about the language being spoken— English, French, or German (46.7% correct, where chance performance is 33.3%). However, when asked to make
judgments about the content of the backward messages, performance fell to chance levels. Participants were unable to distinguish between nursery rhymes, Christian, satanic, pornographic, or advertising messages (19.1% correct, where chance performance is 20%).
But, what if the participants knew what patterns to listen for? It is a common experience that when a backward message is identified in a song and people are told the message in advance, they are able to identify it. To test whether such expectations could influence perception, Vokey and Read asked participants to
listen for specific phrases in the backward messages (these were “phrases” that the researchers had picked out after repeatedly listening to the backward stimuli). When asked to listen for “Saw a girl with a weasel in her mouth” and “I saw Satan,” 84.6% of the participants agreed that the phrases were perceivable.
Can we critically evaluate this research? One concern with Vokey and Read’s experiments was that the participants may have been experiencing demand characteristics, producing responses that they thought the experimenter wanted to hear. Such an explanation could easily be tested using more modern technology than was available in the mid-1980s. If participants listened to audio files using headphones and were prompted by a question on a computer rather than by an experimenter, it would help rule out this alternative explanation of the results.
This minor criticism aside, the results do provide a nice demonstration of the fact that our perceptions of the world are influenced both by the stimuli themselves as well as by our own
mindset. For example, the centre of Figure 4.6 can be perceived as either the number 13 or the letter B depending upon whether you’re reading numbers (12 and 14) or letters (A and C).
This is an example of top-down processing , when our perceptions are influenced by our expectations or by our prior knowledge. Reading “12” and “14” gives us the expectation that the ambiguous stimulus in between them must be “13.” In the backward messages experiment, participants used top-down processing to perceive specific phrases.
Figure 4.6 Top-Down Processing
Is the centre the letter B or the number 13? Source: Copyright 1955 From Perceptual Identification and Perceptual Organization, The Journal of
General Psychology, 53(1): 21-28 by Jerome S. Bruner and A. Leigh Minturn. Reproduced by
permission of Taylor & Francis LLC, (http://www.tandfonline.com).
If the participants were not given any directions from the experimenters and instead simply listened to the music backwards and tried to detect messages based on the different sounds that could be heard, they would be engaging in a different
type of processing. Bottom-up processing occurs when we perceive individual bits of sensory information (e.g., sounds) and use them to construct a more complex perception (e.g., a message). As you might expect, bottom-up processing would occur when you encounter something that is unfamiliar or difficult to recognize.
Top-down and bottom-up processing can be studied using some
interesting stimuli, such as the image in Figure 4.7 . When you initially looked at this image, you may have seen either a rat or a man. Unless you were surrounded by animals or a lot of people, there was very little to guide your perception of the image—you used bottom-up processing and were just as likely to have thought the image was a rat or a man. However, when people first look at pictures of animals and then look at this ambiguous image, they tend to see the rat first; if they first look at pictures of
people, they tend to see the man first. Thus, top-down processes can influence the perception of the image as well. In short, the way we perceive the world is a combination of both top-down and
bottom-up processing (Beck & Kastner, 2009).
Figure 4.7 Expectations Influence Perception
Is this a rat or a man’s face? People who look at pictures of animals before seeing this image see a rat, whereas those looking at pictures of faces see the image as a man’s face. Source: Canadian Journal of Psychology, 15, 5-211. Copyright ©1961 by Canadian Psychological
Association Inc. Reprinted by permission of Canadian Psychological Association Inc.
Incidentally, Vokey and Read were asked to testify in the Judas Priest case in order to explain how their psychology experiments related to the legal proceedings. Judas Priest was found not guilty.
Why is this relevant? These results suggest that we interpret patterns of stimuli in ways that are consistent with our expectations. Several researchers
have demonstrated that it is possible to form a perceptual set—a filter that influences what aspects of a scene we perceive or pay attention to. But, focusing on particular patterns of stimuli also
means that we are not focusing on other patterns; in some cases, we ignore pieces of information that don’t fit with our expectations. In the backward messages study, participants had to ignore many different sounds in order to detect the sounds that resembled “Saw a girl with a weasel in her mouth.” As we’ll see in the next section, sometimes our perceptual sets are so fixed that we fail to notice unexpected objects that are clearly visible . . . and very interesting.
Attention and Perception
The example of backward messages shows us that what we pay attention to can
affect what we perceive. In fact, in many cases, we are paying attention to more than one stimulus or task at the same time, a phenomenon known as divided attention . Simultaneously playing a video game and holding a conversation involves divided attention; so does using Facebook and Twitter while you are listening to your psychology professor lecture, or attempting to text and drive. Although we often feel that dividing our attention is not affecting our performance, there is substantial evidence from both laboratory and real-world
studies telling us otherwise (Pashler, 1998; Stevenson et al., 2013).
In contrast, selective attention involves focusing on one particular event or task, such as focused studying, driving without distraction, or attentively listening to music or watching a movie. In this case, you are paying more attention to one part of your environment so that you can accurately sense and perceive the information it might provide (e.g., watching the road while driving). While useful, this process comes at a cost—your perception of other parts of your environment suffers (e.g., you don’t notice the birds in the trees, or you walk into a fountain in the mall because you’re focused on texting). Most of the time, selective attention is quite beneficial; however, there are times when this focus is so powerful that we fail to perceive some very obvious things.
Imagine you are watching your favourite team play basketball. You’re a big fan of a particular player and are intently watching his every move. Would you notice if a person in a gorilla suit ran onto the court for a few seconds? Most people would say “yes.” However, psychological research suggests otherwise. Missing the obvious can be surprisingly easy—especially if you are focused on just one particular aspect of your environment. For example, researchers asked undergraduate students to watch a video of students dressed in white t-shirts actively moving around while passing a ball to one another. The participants’ task was to count the number of times the ball was passed. To complicate matters, there were also students in black t-shirts doing the same thing with another ball; however, the participants were instructed to ignore them. This is a top-down task because the participants selectively attended to a single set of events. The participants in this study found the task very easy; most were able to accurately count the number of passes, give or take a few.
But what if a student wearing a gorilla suit walked through the video, stopped, pounded her chest, and walked off screen? Who could miss that? Surprisingly,
about half the participants failed to even notice the gorilla (Simons & Chabris, 1999). This number was even higher in elderly populations (Graham & Burke, 2011). This result is an example of inattentional blindness , a failure to notice clearly visible events or objects because attention is directed elsewhere (Mack & Rock, 1998). You can imagine how shocked the participants were when they watched the film again without selectively attending to one thing and realized they had completely missed the gorilla. Inattentional blindness shows that when we focus on a limited number of features, we might not pay much attention to anything else.
Inattentional blindness accounts for many common phenomena. For example, people who witness automobile accidents or criminal behaviour may offer faulty or incomplete testimony. In sports, athletes and referees often miss aspects of a
game because they are focusing on one area of action (Memmert & Furley, 2007); inattentional blindness decreases as expertise with the game increases (Furley et al., 2010). Interestingly, research conducted at Dalhousie University has shown that stimuli that were not perceived in an inattentional blindness study still influenced performance on later memory tasks, suggesting that these stimuli
can in fact influence our perceptual system (Butler & Klein, 2009). Although this doesn’t necessarily mean that referees will be haunted by missed calls, it does mean that the refs weren’t blind—just inattentionally blind.
Do you think you would fail to notice the student in the gorilla suit at a basketball
game (top photo, Simons & Chabris, 1999)? In another study of inattentional blindness, researchers discovered that when participants were focused on running after a confederate at night, only 35% of the subjects noticed a staged fight going on right in their pathway, and during the day only 56% noticed
(Chabris et al., 2011). Top: Simons, D. J., & Chabris, C. F. (1999). Gorillas in our midst: Sustained inattentional blindness for dynamic events.
Perception, 28, 1059–1074. Figure provided by Daniel Simons; bottom: Photo by Matt Milless.
Module 4.1b Quiz:
Perceiving the World Around Us
Know . . . 1. Which Gestalt principle refers to the perceptual rule that things that are
close together are likely part of the same object or group?
A. Figure–ground B. Proximity C. Continuity D. Similarity
Understand . . . 2. Failure to notice particular stimuli when paying close attention to others is
known as . A. misattention B. divided attention C. multitasking D. intentional blindness
Analyze . . . 3. While watching television, you see a report about a group of parents
complaining that backward messages in music are making their children misbehave. According to research, you would tell these parents that
A. only backward messages containing emotional information can influence people.
B. there is no evidence that backward messages can be perceived unless people are told what to listen for.
C. previous research has shown that backward messages can influence behaviour, but only if they are embedded within music.
D. researchers have not come to a definitive conclusion about the effects of backward messages.
Module 4.1 Summary
absolute threshold
bottom-up processing
difference threshold
divided attention
doctrine of specific nerve energies
inattentional blindness
perception
psychophysics
selective attention
sensation
sensory adaptation
signal detection theory
top-down processing
transduction
Weber’s law
Stimulus thresholds can be either absolute (the minimum amount of energy to notice a stimulus) or based on difference (the minimum change between stimuli required to notice they are different).
Know . . . the key terminology of sensation and perception.4.1a
Understand . . . what stimulus thresholds are.4.1b
Understand . . . the principles of Gestalt psychology.4.1c
A key principle of Gestalt psychology is that although the individual parts of a stimulus may have little meaning on their own, these parts can be grouped together in ways that are perceived as distinct patterns or objects. For instance, individual stimuli can be grouped together according to principles of figure and ground, proximity, similarity, continuity, and closure.
Apply Activity For practice, consider Figure 4.4 , along with this example: Imagine a girl who has seen a scary television program and then while trying to go to sleep, worries about a monster in the closet. Identify which of the four events (A–D) goes within the correct box; that is, identify it as a hit, a miss, a false alarm, or a correct rejection. Warning: For half of these events, you may have to assume there really is a monster in the closet.
Hit: False alarm:
Miss: Correct rejection:
A. There is no monster in the closet and the girl is confident that she has not heard anything.
B. There really is a monster in the closet but the girl has not heard it. C. There really is a monster in the closet and the girl hears it. D. There is no monster in the closet, but the girl insists that she heard
something.
As you read in the Priming and Subliminal Perception section of this module, we
can sometimes perceive stimuli below the level of conscious awareness, and this perception can affect our behaviour in some ways. However, as noted in the
Apply . . . your knowledge of signal detection theory to identify hits, misses, and correct responses in examples.
4.1d
Analyze . . . claims that subliminal advertising and backward messages can influence your behaviour.
4.1e
Myths in Mind feature, research suggests that subliminal advertising has little effect on one’s consumer behaviour. Similarly, studies of backward messages in music have shown that individuals typically do not perceive the meaning of these
messages unless they are specifically told what they should listen for, suggesting that the Devil in heavy metal music is really just top-down processing.
Module 4.2 The Visual System
Facundo Arrizabalaga/EPA/Newscom
Learning Objectives
Know . . . the key terminology relating to the eye and vision. Understand . . . how visual information travels from the eye through the brain to give us the experience of sight. Understand . . . the theories of colour vision. Apply . . . your knowledge to explain how we perceive depth in our visual field.
4.2a 4.2b
4.2c 4.2d
On Canada Day in 2015, Canadian tennis star Milos Raonic hit a serve that was clocked at 145 mph (233 km/h) against his opponent, German Tommy Haas. At the time, it was the third fastest serve in the 138-year history of the Wimbledon championship. Remarkably, Haas managed to return the serve, although he ended up losing the point to the powerful Canadian. Although spectators were impressed by the skill and athleticism of both athletes on that sunny July afternoon, they were also witness to something equally stunning: the power and complexity of the human visual system.
In order for Haas to return Raonic’s serve, he had to identify a yellowish- green tennis ball against a dark green background, follow the ball as it landed on a light-green grass-court surface, and track its trajectory as it bounced toward him. Doing so required him to be able to perceive different colours, perceive and identify particular objects in his visual field, and perceive motion. Haas’ visual system also had to work with his motoric (movement) system so that he could move his racquet (and thus his hand and arm) in order to return the serve.
Although both Raonic and Haas are professional athletes, their exceptional visual abilities did not develop overnight; they are the product of years of training. Vision—and the movements and cognition that go with it—is something we fine-tune with experience.
Focus Questions
1. Which brain areas are involved with identifying your coffee cup versus reaching for your coffee cup?
2. What tricks can artists use to make two-dimensional paintings appear three dimensional?
Analyze . . . how we perceive objects and faces.4.2e
The world is a visual place to most humans. We use vision to navigate through beautiful landscapes, city centres, and the interiors of buildings. We also use vision to communicate via facial expressions and the written word (such as this text, which you undoubtedly photocopy and tape to your bedroom walls). In this module, we explore how vision works—starting out as patterns of light entering the eye, and ending up as a complex, perceptual experi ence. We begin with an overview of the basic physical structures of the eye and brain that make vision
possible, and then discuss the experience of seeing.
The Human Eye
The eye is one of the most remarkable of the human body’s physical structures. It senses an amazing array of information, translates that information into neural impulses, and transfers it to the brain for complex perceptual processing. To ensure that this sequence of events begins correctly, the eye needs specialized structures that allow us to regulate how much light comes in, to respond to different wavelengths of light, to maintain a focus on the most important objects in a scene, and to turn physical energy into action potentials, the method by which information is transmitted in the brain.
How the Eye Gathers Light
The primary function of the eye is to gather light and change it into an action potential. But, “light” itself is quite complex. Although physicists have written vast tomes on the topic of light, for the purposes of human perception, “light” actually refers to radiation that occupies a relatively narrow band of the electromagnetic
spectrum, shown in Figure 4.8 a. Light travels in waves that vary in terms of two different properties: length and amplitude. The term wavelength refers to the distance between peaks of a wave—differences in wavelength correspond to
different colours on the electromagnetic spectrum. As you can see from Figure 4.8 a, long wavelengths correspond to our perception of reddish colours and short wavelengths correspond to our perception of bluish colours. The different shades of green found in the tennis match described in the opening of this
module would represent wavelengths of light in between the wavelengths of red and blue. Interestingly, some organisms, such as bees, can see ultraviolet light and some reptiles can see infrared light. These interspecies differences are likely due to the different evolutionary demands these species have faced. What pressures do you think led humans to develop their specific visual system? Although no one can answer this question with absolute certainty, some researchers have suggested that our red–green vision allowed us to distinguish
between types of edible vegetation (Regan et al., 2001).
Figure 4.8 Light Waves in the Electromagnetic Spectrum (a) The electromagnetic spectrum: When white light travels through a prism, the bending of the light reveals the visible light spectrum. The visible spectrum falls within a continuum of other waves of the electromagnetic spectrum. (b) Wavelength is measured by distance between the peaks (or the troughs) of the waves. Source: Ciccarelli, Saundra K.; White, J. Noland, Psychology: An Exploration, 1st Ed., ©2010, p. 79. Reprinted and
Electronically reproduced by permission of Pearson Education, Inc., New York, NY.
Wavelength is not the only characteristic that is important for vision. Amplitude refers to the height of a wave (see Figure 4.8 b). Low-amplitude waves are
seen as dim colours, whereas high-amplitude waves are seen as bright colours. Light waves can also differ in terms of how many different wavelengths are being viewed at once. When you look at a clear blue sky, you are viewing many different wavelengths of light at the same time—but the blue wavelengths are more prevalent and therefore dominate your impression; when our visual angle to the sun changes at dusk, different light frequencies are more apparent, giving the sky a reddish colour. If a large proportion of the light waves are clustered around one wavelength, you will see an intense, vivid colour. If there are a large variety of wavelengths being viewed at the same time, the colour will appear to
be “washed out.” Figure 4.9 depicts these different characteristics of light— wavelength, amplitude, and purity—as we generally perceive them. These
characteristics of light will be experienced by us as hue (colour of the spectrum), intensity (brightness), and saturation (colourfulness or purity). It is in the eye that this transformation from sensation to perception takes place.
Figure 4.9 Hue, Intensity, and Saturation Colours vary by hue (colour), intensity (brightness), and saturation (colourfulness
or “purity”).
The Structure of the Eye
The eye consists of specialized structures that regulate the amount of light that enters the eye and organizes it into a pattern that the brain can interpret (see Figure 4.10 ). The sclera is the white, outer surface of the eye and the cornea is the clear layer that covers the front portion of the eye and also contributes to the eye’s ability to focus. Light enters the eye through the cornea and passes through an opening called the pupil. The pupil regulates the amount of light that enters by changing its size; it dilates (expands) to allow more light to enter and constricts (shrinks) to allow less light into the eye. The changes in the pupil’s size are performed by the iris , a round muscle that adjusts the size of the pupil; it also gives the eyes their characteristic colour. Behind the pupil is the lens , a clear structure that focuses light onto the back of the eye. The lens can change its shape to ensure that the light entering the eye is refracted in such a way that it is focused when it reaches the back of the eye.
This process is known as accommodation. When the light reaches the back of the eye, it will stimulate a layer of specialized receptors that convert light into a
message that the brain can then interpret, a process known as transduction (see Module 4.1 ). These receptors are part of a complex structure known as the retina.
Figure 4.10 The Human Eye and Its Structures Notice how the lens inverts the image that appears on the retina (see inset). The visual centres of the brain correct the inversion.
The retina lines the inner surface of the back of the eye and consists of specialized receptors that absorb light and send signals related to the properties of light to the brain. The retina contains a number of different layers, each performing a slightly different function. At the back of the retina are specialized
receptors called photoreceptors. These receptors, which will be discussed in more depth below, are where light will be transformed into a neural signal that the brain can understand. It may seem strange that light would stimulate the deepest layer of the retina, with the neural signal then turning around and
Figure 4.11
moving forward in the eye (see ); however, there is a reason for this design. Having the photoreceptors wedged into the back of the eye protects them and provides them with a constant blood supply, both of which are useful to your ability to see.
Figure 4.11 Arrangement of Photoreceptors in the Retina Bipolar and ganglion cells collect messages from the light-sensitive photoreceptors and converge on the optic nerve, which then carries the messages to the brain. Source: Ciccarelli, Saundra K.; White, J. Noland, Psychology: An Exploration, 1st Ed., ©2010, p. 81. Reprinted and
Electronically reproduced by permission of Pearson Education, Inc., New York, NY.
Information from the photoreceptors at the back of the retina is transmitted to the ganglion cells closer to the front of the retina. The ganglion cells gather up information from the photoreceptors; this information will then alter the rate at which the ganglion cells fire. The activity of all of the ganglion cells is then sent
out of the eye through the optic nerve , a dense bundle of fibres that connect to the brain. This nerve presents a challenge to the brain. Because it travels through the back of the eye, it creates an area on the retina with no
photoreceptors, called the optic disc. The result is a blind spot—a space in the retina that lacks photoreceptors. You can discover your own blind spot by
performing the activity described in Figure 4.12 .
Figure 4.12 Finding Your Blind Spot To find your blind spot, close your left eye and, with your right eye, fix your gaze on the + in the green square. Slowly move the page toward you. When the page is approximately 6 inches (15 cm) away, you will notice that the black dot on the right disappears because of your blind spot. Not only does the black dot disappear, but its vacancy is replaced by yellow: The brain “fills it in” for you.
The blind spot illustrates just how distinct the processes of sensation and perception are. Why do we fail to notice a completely blank area of our visual field? If we consider only the process of sensation, we cannot answer this question. We have to invoke perception: The visual areas of the brain are able to
“fill in” the missing information for us (Ramachandran & Gregory, 1991). Not only does the brain fill in the missing information, but it does so in context. Thus,
once the black dot at the right of Figure 4.12 reaches the blind spot, the brain automatically fills in the vacancy with yellow.
The Retina: From Light to Nerve Impulse
Now that you have read an overview of the eye’s structures, we can ask an
important question: How can the firing of millions of little photoreceptors in the retina produce vivid visual experiences like seeing white-clad tennis players running around a light-green court surrounded by thousands of spectators in different-coloured clothes? The simple answer is that not all photoreceptors are
the same. There are two general types of photoreceptors—rods and cones— each of which responds to different characteristics of light. Rods are photoreceptors that occupy peripheral regions of the retina; they are highly sensitive under low light levels (see Figure 4.13 ). This type of sensitivity makes rods particularly responsive to black and grey. In contrast, cones are photoreceptors that are sensitive to the different wavelengths of light that we perceive as colour. Cones tend to be clustered around the fovea , the central region of the retina.
Figure 4.13 Distribution of Rods and Cones on the Retina Cones are concentrated at the fovea, the centre of the retina, while rods are more abundant in the periphery. There are approximately 120 million rods and approximately 6 to 8 million cones in the adult retina.
When the rods and cones are stimulated by light, their physical structure briefly changes. This change decreases the amount of the neurotransmitter glutamate being released, which alters the activity of neurons in the different layers of the retina. The final layer to receive this changed input consists of ganglion cells, which will eventually output to the optic nerve. Interestingly, the ratio of ganglion cells to cones in the fovea is approximately one to one; in contrast, there are roughly 10 rods for every ganglion cell. So, all of the input from a cone is clearly transmitted to a ganglion cell whereas the input from a rod must compete with input from other rods (similar to ten people talking at you at the same time). So, cones are clustered in the fovea (i.e., at the centre of our visual field) and have a one-to-one ratio with ganglion cells, while rods are limited to the periphery of the retina and have a ten-to-one ratio with ganglion cells. These differences help explain why colourful stimuli are often perceived as sharp images while shadowy grey images are perceived as being hazy or unclear.
In daylight or under artificial light, the cones in the retina are more active than rods—they help us to detect differences in the colour of objects and to discriminate the objects’ fine details. In contrast, if the lights suddenly go out or if you enter a dark room, at first you see next to nothing. Over time, however, you
gradually begin to see your surroundings more clearly. Dark adaptation is the process by which the rods and cones become increasingly sensitive to light under low levels of illumination. What is actually happening during dark adaptation is that the photoreceptors are slowly becoming regenerated after having been exposed to light. Cones regenerate more quickly than do rods, often within about ten minutes. However, after this time, the rods become more sensitive than the cones. Indeed, we do not see colour at night or in darkness because rods are more active than cones under low light levels.
The phenomenon of dark adaptation explains why we can find our friends in a dark movie theatre. It does not, however, explain why we perceive the sky as being blue or a stop sign as being red. Luckily, 200 years of vision research has provided answers to such questions.
The Retina and the Perception of Colours
Our experience of colour is based on how our visual system interprets different
wavelengths on the electromagnetic spectrum (refer back to Figure 4.8 ). Colour is not actually a characteristic of the objects themselves, but is rather an interpretation of these wavelengths by the visual system. As you learned earlier, the cones of the retina are specialized for responding to different wavelengths of light that correspond to different colours. However, the subjective experience of colour occurs in the brain. Currently, two theories exist to explain how neurons in the eye can produce these colourful experiences.
One theory suggests that three different types of cones exist, each of which is sensitive to a different range of wavelengths on the electromagnetic spectrum. These three types of cones were initially identified in the 18th century by physicist Thomas Young and then independently rediscovered in the 19th
century by Hermann von Helmholtz. The resulting trichromatic theory (or Young-Helmholtz theory ) maintains that colour vision is determined by three different cone types that are sensitive to short, medium, and long wavelengths of light. These cones respond to wavelengths associated with the colours blue, green, and red. The relative responses of the three types of cones allow us to
perceive many different colours on the spectrum (see Figure 4.14 ) and allow us to experience the vast array of colours seen in environments ranging from flower gardens to dance clubs. For example, yellow is perceived by combining the stimulation of red- and green-sensitive cones, whereas light that stimulates all cones equally is perceived as white. (Note: mixing different wavelengths of light produces different colours than when you mix different colours of paint.) Modern technology has been used to measure the amount of light that can be absorbed in cones and has confirmed that each type responds to different
wavelengths. Thus, some aspects of our colour vision can be explained by the characteristics of the cones in our retinas.
Figure 4.14 The Trichromatic Theory of Colour Vision According to this theory, humans have three types of cones that respond maximally to different regions of the colour spectrum. Colour is experienced by the combined activity of cones sensitive to short, medium, and long wavelengths.
However, not all colour-related experiences can be explained by the trichromatic
theory. For instance, stare at the image in Figure 4.15 for about a minute and then look toward a white background. After switching your gaze to a white background, you will see the colours red, white, and blue rather than green,
black, and yellow. How can we explain this tendency to see such a negative afterimage, a different colour from the one you actually viewed? In the 19th century, Ewald Hering proposed the opponent-process theory of colour
perception, which states that we perceive colour in terms of opposing pairs: red to green, yellow to blue, and white to black. This type of perception is consistent with the activity patterns of retinal ganglion cells. A cell that is stimulated by red is inhibited by green; when red is no longer perceived (as when you suddenly look at a white wall), a “rebound” effect occurs. Suddenly, the previously inhibited cells that fire during the perception of green are free to fire, whereas the previously active cells related to red no longer do so. The same relationship occurs for yellow and blue as well as for white and black.
Figure 4.15 The Negative Afterimage: Experiencing Opponent-Process Theory Stare directly at the white dot within the flag and avoid looking away. After about a minute, immediately shift your focus to a white background. What do you see? What colours would you use to create a Canadian flag afterimage? Source: Lilienfeld, Scott O.; Lynn, Steven J; Namy, Laura L.; Woolf, Nancy J., Psychology: From Inquiry To Understanding,
2nd Ed., ©2011. Reprinted And Electronically Reproduced By Permission Of Pearson Education, Inc., New York, NY.
The trichromatic and opponent-process theories are said to be complementary because both are required to explain how we see colour. The trichromatic theory explains colour vision in terms of the activity of cones. The opponent-process theory of colour vision explains what happens when ganglion cells process signals from a number of different cones at the same time. Together, they allow
us to see the intense world of colours that we experience every day.
Common Visual Disorders
Of course, not everyone can see colours. In fact, many people reading this book
will have some form of colour blindness. Most forms of colour blindness affect the ability to distinguish between red and green. In people who have normal colour vision, some cones contain proteins that are sensitive to red and some contain proteins that are sensitive to green. However, in most forms of colour blindness, one of these types of cones does not contain the correct protein (e.g., “green cones” contain proteins that are sensitive to wavelengths of light that produce the colour red). Most forms of colour blindness are genetic in origin.
There are also visual disorders caused by the shape of the eye itself. Changes to the shape of the eye sometimes prevent a focused image from reaching the
photoreceptors in the retina. Nearsightedness, or myopia, occurs when the eyeball is slightly elongated, causing the image that the cornea and lens focus
on to fall short of the retina (see Figure 4.16 ). People who are nearsighted can see objects that are relatively close up but have difficulty focusing on distant objects. Alternatively, if the length of the eye is shorter than normal, the result is
farsightedness or hyperopia. In this case, the image is focused behind the retina. Farsighted people can see distant objects clearly but not those that are close by. Both types of impairments can be corrected with contact lenses or glasses, thus allowing a focused visual image to stimulate the retina at the back of the eye, where light energy is converted into neural impulses.
Figure 4.16 Nearsightedness and Farsightedness Nearsightedness and farsightedness result from misshapen eyes. If the eye is elongated or too short, images are not centred on the retina.
Source: Lilienfeld, Scott O.; Lynn, Steven J; Namy, Laural L.; Woolf, Nancy J., Psychology: From Inquiry to Understanding,
Books A La Carte Edtion, 2nd Ed., ©2011. Reprinted and Electronically reproduced by permission of Pearson Education,
Inc., New York, NY.
In the last 20 years, an increasing number of people have undergone laser eye surgery in order to correct near- or farsightedness. In this type of surgery, surgeons use a laser to reshape the cornea so that incoming light focuses on the retina, which produces close to perfect vision. In nearsighted patients, the doctors attempt to flatten the cornea, whereas in farsighted patients the doctors attempt to make the cornea steeper. Although the idea of having a laser fire into your eyes sounds frightening, approximately 95% of the patients who undergo
these surgeries report being completely satisfied with the results (Solomon et al., 2009). Seeing is believing.
Module 4.2a Quiz:
The Human Eye
Know . . . 1. Cones are predominantly gathered in a central part of the retina known
as the . A. fovea B. photoreceptor C. blind spot D. optic chiasm
2. Which of the following conditions occurs when the eye becomes elongated, causing the image to fall short of the retina?
A. Prosopagnosia B. Motion parallax C. Farsightedness D. Nearsightedness
Understand . . . 3. Crystal was at a modern art gallery. After staring at a large, red square
(that was somehow worth $20 million), she looked at the wall and briefly saw the colour green. Which theory can explain Crystal’s experience?
A. Opponent-process theory B. Hyperopia C. Trichromatic theory D. Motion parallax
Apply . . . 4. Jacob cannot distinguish between the colours red and green. What
structure(s) of the eye is/are most likely not functioning properly?
A. Rods B. Cornea C. Cones D. Lens
It is important to remember that the initial sensations of light that are processed in the eye itself provide very specific information about the environment that we are viewing. But, in order for this raw sensory information to be perceived, it needs to exit the eye and enter the brain.
Visual Perception and the Brain
Information from the optic nerve travels to numerous areas of the brain. The first
major destination is the optic chiasm, the point at which the optic nerves cross at the midline of the brain (see Figure 4.17 ). For each optic nerve, about half of the nerve fibres travel to the same side of the brain (ipsilateral), and half of them
travel to the opposite side of the brain (contralateral). As can be seen in Figure 4.17 , the outside half of the retina (closest to your temples) sends its optic nerve projections ipsilaterally. In contrast, the inside half of the retina (closest to your nose) sends its optic nerve projections contralaterally. The result of this distribution is that the left half of your visual field is initially processed by the right hemisphere of your brain, whereas the right half of your visual field is initially
processed by the left hemisphere of your brain. Although this system might sound like it was designed by someone who had had a few drinks, it serves important functions, particularly if a person’s brain is damaged. In this case,
having both eyes send some information to both hemispheres increases the likelihood that some visual abilities will be preserved.
Figure 4.17 Pathways of the Visual System in the Brain The optic nerves route messages to the visual cortex. At the optic chiasm, some of the cells remain on the same side and some cross to the opposite side of the brain. This organization results in images appearing in the left visual field being processed on the right side of the brain, and images appearing in the right visual field being processed on the left side of the brain. Source: Ciccarelli, Saundra K.; White, J. Noland, Psychology, 3rd Ed., ©2012, pp.96. Reprinted and Electronically
reproduced by permission of Pearson Education, Inc., New York, NY.
Fibres from the optic nerve first connect with the thalamus, the brain’s “sensory relay station.” The thalamus is made up of over 20 different nuclei with
specialized functions. The lateral geniculate nucleus (LGN) is specialized for processing visual information. Fibres from this nucleus send messages to the visual cortex, located in the occipital lobe, where the complex processes of visual perception begin.
How does the visual cortex make sense of all this incoming information? It starts with a division of labour among specialized cells. One set of cells in the visual
cortex—first discovered by Canadian David Hubel and his colleague Torsten Wiesel in 1959—are referred to as feature detection cells; these cells respond selectively to simple and specific aspects of a stimulus, such as angles and
edges (Hubel & Wiesel, 1962). Researchers have been able to map which feature detection cells respond to specific aspects of an image by measuring the
firing rates of groups of neurons in the visual cortex in lab animals (Figure 4.18 ). Feature detection cells of the visual cortex are thought to be where visual input is organized for perception; however, additional processing is required for us to accurately perceive our visual world. From the primary visual cortex, information about different features is sent for further processing in the surrounding secondary visual cortex. This area consists of a number of specialized regions that perform specific functions, such as the perception of colour and movement. These regions begin the process of putting together primitive visual information into a bigger picture.
Figure 4.18 Measuring the Activity of Feature Detection Cells Scientists can measure the activity of individual feature detector cells by inserting a microscopic electrode into the visual cortex of an animal. The activity level will peak when the animal is shown the specific feature corresponding to that specific cell. Source: Lilienfeld, Scott O.; Lynn, Steven; Namy, Laura L.; Woolf, Nancy J., Psychology: From Inquiry To Understanding,
Books A La Carte Edition, 2nd Ed., © 2011. Reprinted and Electronically reproduced by permission of Pearson Education,
Inc., New York, NY.
These specialized areas are the beginning of two streams of vision, each of
which performs different visual functions (see Figure 4.19 ). The ventral stream extends from the visual cortex to the lower part of the temporal lobe. The dorsal stream, on the other hand, extends from the visual cortex to the parietal lobe. Both streams are essential for our ability to function normally in our visual world.
Figure 4.19 The Two Streams of Vision Neural impulses leave the visual centres in the occipital lobe along two different pathways. The ventral (bottom) stream extends to the temporal lobe and the dorsal (top) stream extends to the parietal lobe. Source: Figure 4.18, p. 139 in Psychology: From Inquiry to Understanding, 2nd ed. by Scott O. Lilienfeld, Steven J. Lynn,
Laura L. Namy, and Nancy J. Woolf. Copyright © 2011. Printed and electronically reproduced by permission of Pearson
Education, Inc., Upper Saddle River, New Jersey.
The Ventral Stream
The ventral stream of vision extends from the visual cortex in the occipital lobe to the anterior (front) portions of the temporal lobe. This division of our visual system performs a critical function: object recognition. Groups of neurons in the temporal lobe gather shape and colour information from different regions of the secondary visual cortex and combine it into a neural representation of an object. Brain imaging experiments have shown that damage to this stream of vision
causes dramatic impairments in object recognition (James et al., 2003). Other studies have noted that different categories of objects—such as tools, animals, and instruments—are represented in distinct areas of the anterior temporal lobes
(Tranel et al., 1997). Indeed, researchers have identified rare cases where brain-damaged individuals show a striking inability to name items from one
category while being unimpaired at naming other categories (e.g., Caramazza &
Mahon, 2003; Dixon et al., 1997); this deficit only affects the visual perception of those objects (e.g., a guitar), not the knowledge about those objects (e.g., that a guitar has six strings). But tools, animals, and musical instruments are not the only categories that are represented in distinct areas of the ventral stream of vision. One group of stimuli—possibly the most evolutionarily important one in our visual world—may have an entire region of the brain dedicated to its perception.
Working the Scientific Literacy Model Are Faces Special?
Faces provide us with an incredible amount of social information. In addition to using faces to identify specific other people, we can use them as a source of important social information, such as someone’s emotional state. Other people’s faces could therefore give you hints as to how you should respond to them, or to the situation you are both in. Given their importance, it seems logical that faces would be processed differently than many less important types of visual stimuli.
What do we know about face perception?
Look at the painting in Figure 4.20 . What do you see? When you look at the image on the left, you will likely see a somewhat dreary bowl filled with vegetables. However, when most people see the image on the right, they perceive a face. They can obviously tell that the “face” is just the bowl of vegetables turned upside down, but the different items in the bowl do resemble the general shape of a face. The Italian artist Guiseppe Archimboldo produced a number of similar paintings in which “faces” could be perceived within other structures. What Archimboldo was highlighting was the fact that faces appear to stand out relative to other objects in our visual world.
Figure 4.20 Seeing Faces
At left is a painting of turnips and other vegetables by the Italian artist Giuseppe Archimboldo. The image at right is the same image rotated 180 degrees—does it resemble a human face? Source: The Vegetable Gardener, c.1590 (oil on panel), Arcimboldo, Giuseppe (1527–93)/Museo
Civico Ala Ponzone, Cremona, Italy/Bridgeman Images.
How can science explain how we perceive faces? Not everyone sees the faces in Archimboldo’s painting. In fact, some neurological patients don’t see faces at all. Specific genetic problems or brain damage can lead to an inability to recognize
faces, a condition known as prosopagnosia, or face blindness. People with face blindness are able to recognize voices and other defining features of individuals (e.g., Angelina Jolie’s lips), but not faces. Importantly, these patients tend to have damage or dysfunction in the same general area of the brain: the bottom of the right temporal lobe. So, although prosopagnosia is a relatively rare clinical condition, it does help us understand some basic processes that are involved in perceiving faces.
Brain imaging studies have corroborated the location of the “face
area” of the brain (Kanwisher et al., 1997). Using fMRI, researchers have consistently detected activity in this region, now
known as the fusiform face area (FFA). The FFA responds more strongly to the entire face than to individual features; unlike other types of stimuli, faces are processed holistically rather than as a
nose, eyes, ears, chin, and so on (Tanaka & Farah, 1993). However, the FFA shows a much smaller response when we
perceive inverted (upside down) faces. In this case, people tend to perceive the individual components of the face (e.g., eyes, mouth, etc.) rather than perceiving the faces as a holistic unit. Figure 4.21 provides an interesting—and somewhat jarring— visual phenomenon demonstrating this difference in our perception of upright and inverted faces.
Figure 4.21 The Face Inversion Effect
After viewing both upside-down faces, you probably noticed a difference between the two pictures. The face on the left probably seemed as a bit “off.” Now turn your book upside down and notice how the distortion of one of the faces is amplified when viewed from this perspective. The reason the distorted face didn’t seem as bizarre when viewed upside down is that you likely focused on the individual components of Beyoncé’s face, none of which are strange on their own. When you viewed the stimuli as upright faces, you would have put the different features together into a more holistic view of Beyoncé’s entire face. At this point,
the distorted face would definitely not look flawless. Left: PA Photos/Landov; right: PA Photos/Landov.
Interestingly, the FFA is also active when we perceive images of faces in everyday objects, such as when people see images of
Jesus in a piece of toast (Liu et al., 2014). The fact that these illusory perceptions of faces, known as face pareidolia, also activate the FFA suggests that this structure is influenced by top- down processing that treats any face-like pattern as a face.
Like many other sensory functions, the ability to perceive faces is dependent upon experience. Researchers at McMaster and Brock Universities have found that early visual input to the right, but not left, hemisphere of the brain is essential for the
development of normal face perception (Le Grand et al., 2004, 2005). Our face perception skills also develop as we grow up— adults out-perform children on tests of face recognition
(Mondloch et al., 2006) and the fusiform face area does not show special sensitivity to faces until approximately age 10
(Aylward et al., 2005).
Can we critically evaluate this evidence? Although no one doubts that faces are processed by the FFA, there are alternative explanations for these effects. One possibility is that the FFA is being activated by one of the cognitive or perceptual processes that help us perceive faces rather than by the perception of faces themselves. One such process is expertise. We are all experts at recognizing faces. Think of all of the people that you’ve gone to school with over the years. Think of all of the entertainers, athletes, and politicians you can recognize. You have the ability to distinguish between thousands of different faces. Canadian psychologist Isabel Gauthier and her colleagues have suggested that face recognition isn’t all that special. Instead, the FFA may simply be
an area related to processing stimuli that we have become experts at recognizing. To test this hypothesis, she trained undergraduate students to recognize different types of a novel
group of objects called Greebles (see Figure 4.22 ). Before training, these stimuli did not trigger activity in the FFA; however,
after training, this area did become active (Gauthier et al., 1999). Further support for this expertise hypothesis comes from studies
of bird and car experts (Gauthier et al., 2000). Both groups showed greater levels of brain activity in the FFA in response to stimuli related to their area of expertise (e.g., cars for car enthusiasts). Although this research doesn’t negate the studies showing face-specific processing in this area, it does suggest that more research is necessary to see just how specialized this region of the ventral stream of vision really is.
Figure 4.22 Expertise for Faces and “Greebles”
The images below are Greebles, faceless stimuli used to test
whether the FFA responds only to faces (Gauthier & Tarr, 1997). Participants in these studies are taught to classify the Greebles on a number of characteristics such as sex (“male” and “female”). Although this task seems difficult, after several training sessions participants can rapidly make such a decision. These “Greeble experts” also show increased activity in the region of the brain associated with processing faces. Source: Expertise and the Fusiform Face Area. Reprinted with permission of Dr. Isabel Gauthier.
World-renowned chimpanzee researcher Jane Goodall has face blindness (prosopagnosia). Her sister also has it—there appear to be genetic links to the condition. Despite being face blind, Dr. Goodall and others with this condition use nonfacial characteristics to recognize people, or, in her case, hundreds of
individual chimpanzees (Goodall & Berman, 1999). Michael Nichols/National Geographic/ Getty Images
Why is this relevant? The fact that a specific brain region is linked with the perception of faces is very useful information for neurologists and
emergency room physicians. If a patient has trouble recognizing people, it could be a sign that he has damage to the bottom of the right temporal lobe. Indeed, based on studies of prosopagnosia, tests of face memory are now part of most assessment tools used by doctors and researchers. The fact that fMRI studies corroborate the location of the FFA increases our confidence that such tools are in fact valid.
At this point in the module, we have looked at how we sense visual information and how this information is constructed by our brain-based perceptual system into objects that can influence our behaviour, such as a face or an animal. But, our visual system has even more tricks for us. Somehow, we can identify objects even when they are viewed in different lighting conditions or at different angles— your cat is still your cat, regardless of whether it is noon or midnight. This
observation is an example of what is called perceptual constancy , the ability to perceive objects as having constant shape, size, and colour despite changes in perspective. What makes perceptual constancy possible is our ability to make relative judgments about shape, size, and lightness. For shape constancy, we judge the angle of the object relative to our position (see Figure 4.23 ). Size constancy is based on judgments of how close an object is relative to one’s position as well as to the positions of other objects. Colour constancy allows us to recognize an object’s colour under varying levels of illumination. For example, a bright red car is recognized as bright red whether in the shade or in full sunlight.
Figure 4.23 Perceptual Constancies (a) Shape constancy: We perceive the door to be a rectangle despite the fact that the two-dimensional outline of the image on the retina is not always rectangular. (b) Colour constancy: We perceive colours to be constant despite changing levels of illumination. (c) Size constancy: the person in the red shirt appears normal in size when in the background. A replica of this individual placed in the foreground appears unusually small because of size constancy. Source: Lilienfeld, Scott O.; Lynn, Steven J; Namy, Laura L.; Woolf, Nancy J., Psychology: From Inquiry To Understanding,
2nd Ed., ©2011. Reprinted And Electronically reproduced by permission Of Pearson Education, Inc., New York, NY.
Middle: Brian Prawl/Shutterstock; Right: FORGET Patrick/SAGAPHOTO.COM/ Alamy Stock photo
The phenomenon of colour constancy recently gained international attention during “The Great Dress Debate” of 2015. As you may recall, a photograph of a dress became an international sensation when different people perceived it as being either blue and black or white and gold. A large-scale survey involving over 1400 respondents found that 57% of people perceived the dress as black and blue, 30% saw it as white and gold, 10% saw it as blue and brown, and 10%
readily switched between colours (Lafer-Sousa et al., 2015). These striking differences in how different people perceived the dress captured the attention of both the general public and vision experts. Researchers quickly noted that colour constancy was a key factor in determining how the dress was perceived. When we view an object, we naturally try to account for the quality of the surrounding light. If we view something at dawn, our visual system attempts to discount some of the redness of objects because we know that sunrise makes everything appear redder than normal. It turns out that there are individual biases in which types of light people tend to discount. Individuals with a tendency to discount bluish light will perceive the dress as white and gold, whereas individuals who
discount yellowish light will perceive the dress as blue and black (Brainard & Hurlbert, 2015; Gegenfurtner et al., 2015). Thus, “the dress” helps us demonstrate that our perceptual biases, along with our previous experiences and expectations, help structure and organize our visual experiences.
Indeed, all types of perceptual constancy are influenced by our previous
experience with the objects as well as the presence of other objects that can serve as comparisons. In other words, constancies are affected by top-down
processing (see Module 4.1 ). If we know that a golden retriever is 60 cm tall or that a door is rectangular (or that a dress is blue and black), our visual system will use this knowledge when it organizes our perceptions in the brain. This top- down processing is also important when we have to decide how we plan to interact with the objects we are perceiving, a function performed by the dorsal stream of our visual system.
The Dorsal Stream
The dorsal stream of vision extends from the visual cortex in our occipital lobe upwards to the parietal lobe. Its function is less intuitive than that of the ventral stream, but is just as important. Imagine looking at your morning cup of coffee sitting on the table you’re working at. You immediately recognize that the object is a cup, and that the liquid inside of it is coffee, something you drink. You also decide that it is time to have a sip, thus requiring your arm to move so that your hand can grasp the mug of caffeinated goodness. Someone with a healthy brain can do this effortlessly. However, someone with damage to the dorsal stream of vision would have great difficulty performing this simple function. How can we explain this impairment?
Leslie Ungerleider and Mortimer Mishkin (1982) suggested that the ventral and dorsal stream of vision could be referred to as the “what” and “where” pathways. The ventral stream identifies the object, and the dorsal stream locates it in space and allows you to interact with it. Although this description is accurate, researchers at Western University have suggested that the function of the
“where” pathway is more specific (Goodale et al., 1991; Milner & Goodale, 2006). Their initial research was based on studies involving a patient known as “D.F.” (in order to preserve patients’ anonymity, their names are never provided in research papers). D.F. was a healthy middle-aged woman who suffered damage to her temporal lobe that interfered with the ventral stream of vision. As a result, her ability to recognize objects was severely impaired; indeed, she could not recognize letters or line drawings. However, she could still reach for objects
as though she had perfect vision. For instance, when asked to put a letter in a mailbox, she was able to do so, even if the angle of the mail slot was changed by
a sneaky researcher (see Figure 4.24 ). Goodale and colleagues correctly hypothesized that D.F.’s dorsal stream was preserved, and that this pathway
was involved with visually guided movement. So, the next time you reach out to grab your caffeinated beverage from the table, remember that the “simple” ability to recognize and reach for the object requires multiple pathways in the brain.
Some people see “The Dress” as being blue and black (left); other people see the same dress as being white and gold (right). Amina Khan/NSF
Figure 4.24 Testing the Dorsal Stream Patient D.F. was able to rotate her hand to fit an envelope into a mail slot despite having difficulties identifying either object. Her preserved dorsal stream of vision allowed her to use vision to guide her arm’s motions. Source: Reprinted by permission from Melvyn A. Goodale.
Depth Perception
Our ability to use vision to guide our actions is dependent on our depth perception. We need to be able to gauge the distances between different objects as well as to determine where different objects are located relative to each other. Without this ability, it would be difficult to return a tennis serve, drive a car, or even walk through a crowded university hallway. Information related to depth perception can be detected in a number of ways.
Binocular depth cues are distance cues that are based on the differing perspectives of both eyes. One type of binocular depth cue, called convergence , occurs when the eye muscles contract so that both eyes focus on a single object. Convergence typically occurs for objects that are relatively close to you. For example, if you move your fingertip toward your nose, your eyes will move inward and will turn toward each other. The sensations that occur as these muscles contract to focus on a single object provide the brain with additional information used to create the perception of depth.
One reason humans have such a fine-tuned ability to see in three dimensions is that both of our eyes face forward. This arrangement means that we perceive objects from slightly different angles, which in turn enhances depth perception. For example, choose an object in front of you, such as a pen held at arm’s length from your body, and focus on that object with one eye while keeping the other eye closed. Then open your other eye to look at the object (and close the eye you were just using). You will notice that the position of your pen appears to
change. This effect demonstrates retinal disparity (also called binocular disparity), the difference in relative position of an object as seen by both eyes, which provides information to the brain about depth. Your brain relies on cues from each eye individually and from both eyes working in concert—that is, in
stereo. Most primates, including humans, have stereoscopic vision, which results from overlapping visual fields. The brain can use the difference between the information provided by the left and right eye to make judgments about the distance of the objects being viewed. Species that have eyes with no overlap in their visual field, such as some fish, likely do not require as much depth information in order to survive in their particular environment. These species might also be able to make use of depth information perceived by each eye individually.
Monocular cues are depth cues that we can perceive with only one eye. We have already discussed one such cue, called accommodation, earlier in this module. During accommodation, the lens of your eye curves to allow you to focus on nearby objects. Close one eye and focus on a nearby object, and then slightly change your focus to an object that is farther away; the lens changes
shape again so the next object comes into focus (see Figure 4.27 a). The brain receives feedback about this movement which it can then use to help make
judgments about depth. Another monocular cue is motion parallax; it is used when you or your surroundings are in motion. For example, as you sit in a moving vehicle and look out of the passenger window, you will notice objects closer to you, such as the roadside, parked cars, and nearby buildings, appear to move rapidly in the opposite direction of your travel. By comparison, far-off objects such as foothills and mountains in the distance appear to move much more slowly, and in the same direction as your vehicle. The disparity in the directions travelled by near and far-off objects provides a monocular cue about
depth.
PSYCH@ The Artist’s Studio Although we often think of painters as being eccentric people prone to cutting off their ears, they are actually very clever amateur vision scientists. Rembrandt (1606–1669) varied the texture and colour details of different parts of portraits in order to guide the viewer’s gaze toward the clearest object. The result is that more detailed regions of a painting attract attention and receive more eye fixations than less detailed areas
(DiPaola et al., 2011).
In addition to manipulating a viewer’s eye movements, painters also use a variety of depth cues to transform their two-dimensional painting into a
three-dimensional perception. This use of pictorial depth cues is quite challenging, which is why some paintings seem vibrant and multilayered (like nature) while others seem flat and artificial. So what are some strategies that artists use to influence our visual perception?
To understand how artists work, view the painting by Gustave Caillebotte
shown in Figure 4.25 . In this painting, you will notice that the artist used numerous cues to depict depth:
Linear perspective: Parallel lines stretching to the horizon appear to move closer together as they travel farther away. This effect can be seen in the narrowing of the streets and the converging lines of the sidewalks and the top of the building in the distance. This effect is
nicely demonstrated by the illusion in Figure 4.26 . Interposition: Nearby objects block our view of far-off objects, such as the umbrellas blocking the view of buildings behind them.
Light and shadow: The shadow cast by an object allows us to detect both the size of the object and the relative locations of objects. In addition, closer objects reflect more light than far-away objects.
Texture gradient: Objects that are coarse and distinct at close range become fine and grainy at greater distances. In the painting, for example, the texture of the brick street varies from clear to blurred as
distance increases.
Height in plane: Objects that are higher in our visual field are perceived as farther away than objects low in our visual field. The base of the main building in the background of the painting is at about the same level as the man’s shoulder, but we interpret this effect as distance, not as height.
Relative size: If two objects in an image are known to be of the same actual size, the larger of the two must be closer. This can be seen in the various sizes of the pedestrians.
Figure 4.25 Pictorial Depth Cues Artists make use of cues such as linear perspective, texture gradient, relative size, and others to create the sense of depth. Source: Sketch for Paris, a Rainy Day, 1877 (oil on canvas), pre-restoration (see 181504), Caillebotte, Gustave
(1848–94)/Musee Marmottan Monet, Paris, France/Bridgeman Images.
Figure 4.26 The Corridor Illusion Linear perspective and height in plane create the perception of depth here. The result is that the object at the “back” of the drawing appears to be larger than the one in the foreground; in reality, they are identical in size.
Interestingly, Harvard neurobiologists recently speculated that Rembrandt suffered from “stereo blindness,” an inability to form binocular
images (Livingstone & Conway, 2004). He would therefore have had to rely on monocular cues to form the perceptions that led to his innovative depictions of the visual world.
Figure 4.27 Two Monocular Depth Cues (a) Accommodation. From the top left image light comes from a distant object, and the lens focuses the light on the retina. From the bottom left image the lens
changes shape to accommodate the light when the same object is moved closer. (b) Motion parallax. As you look out the train window, objects close to you race past quickly and in the opposite direction that you are headed. At the same time, distant objects appear to move slowly and in the same direction that you are travelling.
Module 4.2b Quiz:
Visual Perception and the Brain
Know . . . 1. Also called face blindness, which of the following conditions is the
inability to recognize faces?
A. Prosopagnosia B. Farsightedness C. Trichromatism D. Astigmatism
2. The in the thalamus is where the optic nerves from the left and right eyes converge.
A. foveal nucleus B. occipital nuclei C. lateral geniculate nucleus D. retinal geniculate nucleus
Understand . . . 3. A familiar person walks into the room. Which of the following choices
places the structures in the appropriate sequence required to recognize the individual?
A. Thalamus, visual cortex, photoreceptors, optic nerve B. Visual cortex, thalamus, photoreceptors, optic nerve C. Photoreceptors, optic nerve, thalamus, visual cortex D. Photoreceptors, thalamus, optic nerve, visual cortex
Apply . . . 4. A patient with brain damage can recognize different objects but is unable
to reach out to grasp the object that she sees. This impairment is best explained by the difference between the
A. primary and secondary visual cortices. B. rods and cones. C. temporal lobe and the frontal lobes. D. ventral and dorsal streams.
Analyze . . . 5. Some people claim that there is a brain area dedicated to the perception
of faces. Although there is a great deal of evidence in favour of this claim,
what is the best evidence against it? A. Doctors have yet to find a brain-damaged patient who cannot
recognize faces.
B. The neuroimaging studies of face perception do not show consistent results.
C. The brain area related to face processing is also active when people see images from categories in which they have expertise.
D. The brain area related to face processing is equally sensitive to faces that are upright or upside down.
Module 4.2 Summary
binocular depth cues
cones
convergence
cornea
dark adaptation
fovea
iris
lens
monocular cues
opponent-process theory
optic nerve
perceptual constancy
pupil
retina
retinal disparity
rods
sclera
trichromatic theory (Young-Helmholtz theory)
Know . . . the key terminology relating to the eye and vision.4.2a
Understand . . . how visual information travels from the eye through the brain to give us the experience of sight.
4.2b
Light is transformed into a neural signal by photoreceptors in the retina. This information is then relayed via the optic nerve through the thalamus and then to the occipital lobe of the cortex. From this location in the brain, neural circuits travel to other regions for specific levels of processing. These include the temporal lobe for object recognition and the parietal lobe for visually guided movement.
The two theories reviewed in this module are the trichromatic and opponent- process theories. According to trichromatic theory, the retina contains three different types of cones that are sensitive to different wavelengths of light. Colour is experienced as the net combined stimulation of these receptors. The trichromatic theory is not supported by phenomena such as the negative afterimage. Opponent-process theory, which emphasizes how colour perception is based on excitation and inhibition of opposing colours (e.g., red–green, blue– yellow, white–black), explains this phenomenon. Taken together, both theories help explain how we perceive colour.
Apply Activity For practice, take a look at the accompanying photo. Can you identify at least four monocular depth cues that are present in the image below?
Understand . . . the theories of colour vision.4.2c
Apply . . . your knowledge to explain how we perceive depth in our visual field.
4.2d
Thinkstock/Getty Images
Object perception is accomplished by specialized perceptual regions of the temporal lobe (the ventral stream of vision). Damage to this region can lead to impairments in recognizing specific categories of objects. Facial recognition is a specialized perceptual process, which is supported by evidence from people who are face blind but are otherwise successful at recognizing objects.
Analyze . . . how we perceive objects and faces.4.2e
Module 4.3 The Auditory and Vestibular Systems
Francey/Shutterstock
Learning Objectives
Know . . . the key terminology relating to the ear, hearing, and the vestibular system. Understand . . . different characteristics of sound and how they correspond to perception. Understand . . . how the vestibular system affects our sense of balance. Apply . . . your knowledge of sound localization.
4.3a
4.3b
4.3c 4.3d
Imagine watching an action movie like Star Wars: The Force Awakens in a movie theatre with Dolby™ Surround Sound. Your body would feel the powerful vibrations of the sound waves as spaceships enter hyperspace and the characters shoot phaser guns during an exciting battle. Now imagine watching a scary movie with a killer in a Halloween mask chasing a young couple through the woods. The music becomes louder and faster, adding anxiety and emotion to the scene. Now imagine watching these movies with the sound muted. You’ll have lost more than the sound waves. . .
Sounds have a dramatic effect on our experience of movies (and to a lesser extent, television). Paramount among these is music. Can you
imagine Star Wars without the familiar John Williams theme, or a horror movie without tension-inducing music? The movies would lose their emotional impact almost immediately. This is because music perception
activates regions of the brain related to emotional perception (Bhatara et al., 2011; Gosselin et al., 2005). Indeed, in a novel study, researchers at the Université de Montréal and Concordia University found that patients with damage to the amygdala, an area of the brain related to the experience of fear, were impaired in their ability to recognize that
particular pieces of music, such as the theme to Jaws, were scary. Studies such as this imply that in healthy brains, the emotion centres respond during the perception of music in order to help us understand its meaning. They also show us how important the auditory system is to how we experience our world.
Focus Questions
1. How does the auditory system sense and perceive something complex like music?
2. How do we localize sounds in our environment?
Analyze . . . how musical beats are related to movement.4.3e
In this module we will explore characteristics of sound, the physical structures that support the sensation of sound, and the pathways involved in its perceptual processing. We will also examine how music affects memory and emotion, and how this relationship can influence our behaviour.
Sound and the Structures of the Ear
The function of the ear is to gather sound waves. The function of hearing is to extract some sort of meaning from those sound waves; this meaning informs you about the nature of the sound source, such as someone calling your name, a referee’s whistle, or a vehicle coming toward you. How do people gain so much information from invisible waves that travel through the air?
Sound
The function of that remarkably sensitive and delicate device, the human ear, is
to detect sound waves and to transform them into neural signals. Sound waves are simply changes in mechanical pressure transmitted through solids, liquids, or gases. Sound waves have two important characteristics: frequency and
amplitude (see Figure 4.28 ). Frequency refers to wavelength and is measured in hertz (Hz), the number of cycles a sound wave travels per second. Pitch is the perceptual experience of sound wave frequencies. High- frequency sounds, such as tires screeching on the road, have short wavelengths and a high pitch. Low-frequency sounds, such as those produced by a bass
guitar, have long wavelengths and a low pitch. The amplitude of a sound wave determines its loudness: High-amplitude sound waves are louder than low- amplitude waves. Both types of information are gathered and analyzed by our ears.
Figure 4.28 Characteristics of Sound: Frequency and Amplitude The frequency of a sound wave (cycles per second) is associated with pitch, while amplitude (the height of the sound wave) is associated with loudness. Source: Lilienfeld, Scott O.; Lynn, Steven J; Namy, Laura L.; Woolf, Nancy J., Psychology: From Inquiry To Understanding,
2nd Ed., ©2011. Reprinted And Electronically Reproduced By Permission Of Pearson Education, Inc., New York, NY.
Humans are able to detect sounds in the frequency range from 20 Hz to 20 000
Hz. Figure 4.29 compares the hearing ranges of several different species. Look closely at the scale of the figure—the differences are of a much greater magnitude than could possibly fit on this page using a standard scale. The comparisons show that mice, for example, can hear frequencies close to five times greater than humans, but have difficulty hearing lower frequencies that we can easily detect.
Figure 4.29 A Comparison of Hearing Ranges in Different Species Source: Based on Fay, R.R. (1988) and Warfield, D. (1973).
Loudness—a function of sound wave amplitude—is typically expressed in units
called decibels (dB). Table 4.2 compares decibel levels ranging from nearly inaudible to injury inducing. Although we doubt you spend much time beside jet engines, we do suggest wearing earplugs to concerts to protect your ears, even if they don’t match your always-stylish “I’m a Belieber” t-shirt.
Table 4.2 Decibel Levels for Some Familiar Sounds
Sound Noise
Level
(dB)
Effect
Jet engines
(near)
140 We begin to feel pain at about 125 dB
Rock concerts 110–
(varies) 140
Thunderclap
(near)
120 Regular exposure to sound over 100 dB for more than
one minute risks permanent hearing loss
Power saw
(chainsaw)
110
Garbage
truck/Cement
mixer
100 No more than 15 minutes of unprotected exposure is
recommended for sounds between 90 and 100 dB
Motorcycle (25
ft)
88 85 dB is the level at which hearing damage (after eight
hours) begins
Lawn mower 85–90
Average city
traffic
80 Annoying; interferes with conversation; constant
exposure may cause damage
Vacuum
cleaner
70 Intrusive; interferes with telephone conversation
Normal
conversation
50–65 Comfortable hearing levels are under 60 dB
Whisper 30 Very quiet
Rustling
leaves
20 Just audible
The Human Ear
The human ear is divided into outer, middle, and inner regions (see Figure
4.30 ). The most noticeable part of your ear is the pinna, the outer region that helps channel sound waves to the ear and allows you to determine the source or
location of a sound. The auditory canal extends from the pinna to the eardrum. Sound waves reaching the eardrum cause it to vibrate. Even very soft sounds, such as a faint whisper, produce vibrations of the eardrum. The middle ear
consists of three tiny moveable bones called ossicles, known individually as the malleus (hammer), incus (anvil), and stapes (stirrup). The eardrum is attached to these bones, so any movement of the eardrum due to sound vibrations results in movement of the ossicles.
Figure 4.30 The Human Ear Sound waves travel from the outer ear to the eardrum and middle ear, and then through the inner ear. The cochlea of the inner ear is the site at which transduction takes place through movement of the tiny hair cells lining the basilar membrane. The auditory cortex of the brain is a primary brain region where sound is perceived.
The ossicles attach to an inner ear structure called the cochlea —a fluid-filled membrane that is coiled in a snail-like shape and contains the structures that convert sound into neural impulses. Converting sound vibrations to neural impulses is possible because of hair-like projections that line the basilar membrane of the cochlea. The pressing and pulling action of the ossicles causes parts of the basilar membrane to flex. This causes the fluid within the cochlea to move, displacing these tiny hair cells. When hair cells move, they stimulate the cells that comprise the auditory nerves. The auditory nerves are composed of bundles of neurons that fire as a result of hair cell movements. These auditory nerves send signals to the thalamus—the sensory relay station of the brain—and then to the auditory cortex, located within the temporal lobes.
As you might expect, damage to any part of the auditory system will result in hearing impairments. However, recent technological advances are allowing
individuals to compensate for this hearing loss. Cochlear implants are now quite common and have been used to help tens of thousands of individuals regain some of their hearing. These devices typically consist of a small microphone that detects sounds from the outside world and electronically stimulates parts of the
membranes in the cochlea (see Figure 4.31 ). Although these devices are not a perfect substitute for a normally functioning auditory system, they do allow individuals to hear low-frequency sounds such as those used in human speech.
These devices are particularly useful for young children (Fitzpatrick et al., 2011; Peterson et al., 2010), as the brains of children more easily form new pathways in response to the stimulation from the implants.
Figure 4.31 A Cochlear Implant The speech processor and microphone are located just above the pinna. A wire with tiny electrodes attached is routed through the cochlea. Carlos Osorio/Toronto Star/Getty Images
Module 4.3a Quiz:
Sound and the Structures of the Ear
Know . . . 1. The is the quality of sound waves that is associated with changes in
pitch.
A. frequency B. amplitude C. pinna D. decibel
2. The is a snail-shaped, fluid-filled organ that converts sound waves
into neural signals.
A. ossicle B. pinna C. cochlea D. outer ear
Understand . . . 3. The amplitude of a sound wave determines its loudness; -amplitude
sound waves are louder than -amplitude waves. A. low; high B. short; tall C. wide; narrow D. high; low
The Perception of Sound
It is quite remarkable that we are able to determine what makes a sound and where the sound comes from by simply registering and processing sound waves. In this section we examine how the auditory system accomplishes these two tasks, starting with the ability to locate a sound in the environment.
Sound Localization: Finding the Source
Accurately identifying and orienting oneself toward a sound source has some obvious adaptive benefits. Over the course of evolution, failure to do so could result in an organism becoming someone else’s dinner, or failing to catch dinner of one’s own. Thus, auditory systems have developed to allow organisms,
including humans, to orient toward sounds in the environment. This sound localization , the process of identifying where sound comes from, is handled by parts of the brainstem as well as by a midbrain structure called the inferior colliculus.
There are two ways that we localize sound. First, we take advantage of the slight time difference between a sound hitting both ears to estimate the direction of the source. If your friend shouts your name from your left side, the left ear will receive the information a fraction of a second before the right ear. Second, we localize sound by using differences in the intensity in which sound is heard by
both ears—a phenomenon known as a sound shadow (Figure 4.32 ). If the source of the sound is to your left, the left ear will experience the sound more intensely than the right because the right ear will be in the sound shadow. Nuclei in the brainstem detect differences in the times when sound reaches the left
versus the right ear (Carr & Konishi, 1990), as well as the intensity of the sound between one side and the other, allowing us to identify where it is coming from.
Figure 4.32 How We Localize Sound To localize sound, the brain computes the small difference in time at which the sound reaches each of the ears. The brain also registers differences in loudness that reach both ears. Source: Lilienfeld, Scott O.; Lynn, Steven J; Namy, Laura L.; Woolf, Nancy J., Psychology: From Inquiry To Understanding,
2nd Ed., ©2011. Reprinted And Electronically reproduced by permission Of Pearson Education, Inc., New York, NY.
Theories of Pitch Perception
To explain how we perceive pitch, we will begin in the cochlea and work toward brain centres that are specialized for hearing. How does the cochlea pave the way for pitch perception? One explanation involves the specific arrangement of hair cells along the basilar membrane. Not all hair cells along the basilar membrane are equally responsive to sounds within the 20 to 20 000 Hz range of human hearing. High-frequency sounds stimulate hair cells closest to the ossicles, whereas lower-frequency sounds stimulate hair cells toward the end of
the cochlea (see Figure 4.33 ). Thus, how we perceive pitch is based on the location (place) along the basilar membrane that sound stimulates, a tendency known as the place theory of hearing .
Figure 4.33 The Basilar Membrane of the Cochlea and Theories of Hearing Source: “A Cochlear Implant” “Cochlear Implant” (Fig. 3.9, p. 104) from Psychology, 3rd edition, by Saundra Ciccarelli & J.
Noland White. Copyright © 2012. Printed and electronically reproduced by permission of Pearson Education, Inc., Upper
Saddle River, New Jersey.
Another determinant of how and what we hear is the rate at which the ossicles press into the cochlea, sending a wave of activity down the basilar membrane.
According to frequency theory , the perception of pitch is related to the frequency at which the basilar membrane vibrates. A 70-Hz sound stimulates the hair cells 70 times per second. Thus, 70 nerve impulses per second travel from the auditory nerves to the brain, which interprets the sound frequency in terms of
pitch (Figure 4.33 ). However, we quickly reach an upper limit on the capacity of the auditory nerves to send signals to the brain: Neurons cannot fire more than 1000 times per second. Given this limit, how can we hear sounds exceeding
1000 Hz? The answer lies in the volley principle. According to the volley principle, groups of neurons fire in alternating (hence the term “volley”) fashion. A sound measuring 5000 Hz can be perceived because groups of neurons fire in
rapid succession (Wever & Bray, 1930).
Currently, the place, frequency, and volley theories are all needed to explain our experience of hearing. When we hear complex stimuli, such as music, the place, frequency, and volley principles are likely all functioning at the sensory level. However, turning this sensory information into the perception of music, voices, and other important sounds occurs in specialized regions of the brain.
Auditory Perception and the Brain
The primary auditory cortex is a major perceptual centre of the brain involved in perceiving what we hear. The auditory cortex is organized in very similar fashion to the cochlea. Cells within different areas across the auditory cortex respond to specific frequencies. For example, high musical notes are processed at one end of the auditory cortex, and progressively lower notes are
heard as you move to the opposite end (Wang, Lu, et al., 2005). As in the visual system, the primary auditory cortex is surrounded by brain regions that provide
additional sensory processing. This secondary auditory cortex helps us to interpret complex sounds, including those found in speech and music. Interestingly, the auditory cortices in the two hemispheres of the brain are not equally sensitive. In most individuals the right hemisphere is able to detect smaller changes in pitch than the left hemisphere (Hyde et al., 2007). Given this fact, it is not surprising that the right hemisphere is also superior at detecting
sarcasm, as this type of humour is linked to the tone of voice used (Voyer et al.,
2008).
However, we are not born with a fully developed auditory cortex. In order to
perceive our complex auditory world, the auditory cortices must learn to analyze different patterns of sounds. Researchers have identified a number of different changes in the brain’s responses to sounds during the course of development. Brain imaging studies have shown that infants as young as three months of age
are able to detect simple changes in pitch (He et al., 2007, 2009). Infants can detect silent gaps in a tone (an ability that may help us learn languages) between
the ages of 4 to 6 months (Trainor et al., 2003), and develop the ability to localize sound at approximately 8 months of age (Trainor, 2010). By 12 months of age, the auditory system starts to become specialized for the culture in which the infant is living. Infants who are 10–12 months of age do not recognize sound
patterns that are not meaningful in their native language or culture (Werker & Lalonde, 1988); indeed, children in this age group show different patterns of brain activity when hearing culturally familiar and unfamiliar sounds (Fujioka et al., 2011). This brain plasticity explains why many of us have difficulty hearing fine distinctions in the sounds of languages we are exposed to later in life. Interestingly, this fine-tuning of the auditory cortex also influences how we perceive music.
The Perception of Music
Because our auditory systems have evolved to be able to distinguish between different rapidly changing pitches that are important for understanding speech, we also have a brain that is nicely designed for perceiving different elements of music, particularly the differences in sound frequencies that we perceive as pitch
(Levitin, 2006). As noted in the previous section of this module, this function is performed by the primary auditory cortex in the temporal lobes. Our ability to compare different pitches also uses the secondary auditory cortex, the brain
areas immediately in front of and behind the primary auditory cortex (see Zatorre & Zarate, 2010). Both neuroimaging studies and studies with brain-damaged patients have shown that the auditory cortices in the right hemisphere are
particularly sensitive to nuances in pitch (Hyde, Peretz, et al., 2008; Johnsrude
et al., 2000).
However, music perception requires more than just perceiving different frequencies. It also uses one of the human brain’s most amazing skills—the ability to organize information into a coherent structure or pattern.
Working the Scientific Literacy Model The Perception of Musical Beats
The next time you listen to music, concentrate on what you are thinking and on how your body is responding. Do you find yourself subtly moving with the music? Are you tapping your fingers or feet to the beat? Do you sing (or hum) along to the music? Most people are able to perform some or all of these musical responses, even if they have no musical training. In the last decade, psychologists have begun to unravel the perceptual and neural processes that allow us to do so.
What do we know about the perception of musical beats? Our brains are pattern-recognition machines. In terms of music, this ability is most clearly shown by our ability to detect metrical structure, or groups of stronger and weaker events that we perceive as musical beats. When we listen to music, most people are able to detect the fact that certain patterns tend to repeat; as a result, our brains begin to expect beats to occur at specific
times (Large & Palmer, 2002). This is the basis of our ability to detect musical beats or rhythms. As a result, we can tap our fingers to any song we hear on the radio, from Nicky Minaj to Nickelback.
This ability to detect rhythms or beats appears to be innate— even babies can do it! In one study, babies were exposed to a series of musical beats. Babies showed distinct changes in brain
activity when they heard sound files that skipped a beat (Winkler et al., 2008). Interestingly, this ability appears to be linked to motion. In an innovative study conducted at McMaster University, seven-month-old infants heard a two-minute musical piece that did not have a difference between a strong beat (e.g., a bass drum) and a weak beat (e.g., a cymbal). Some of the babies were bounced every second beat and some were bounced every third beat. During a later test, the babies heard versions of the music that stressed every second beat or every third beat. Overall, the babies showed behavioural preferences for the rhythms that
matched the beats on which they were bounced (Phillips-Silver & Trainor, 2005). The fact that motion influences how humans perceive musical beats suggests that detection of these beats likely involves brain systems related to movement.
How can science explain the perception of musical beats? A number of brain imaging studies have shown that perceiving musical beats leads to activity in brain areas that are involved
with coordinating movements (Merchant et al., 2015). For example, researchers have shown that individual differences in the ability to detect musical beats are linked to differences in
activity in the basal ganglia (Grahn & McAuley, 2009), a group of brain structures in the centre of the brain that are related to the coordination of movement. Additional studies have tried to figure
out if the basal ganglia are involved with discovering a beat or maintaining an internal representation of a beat, an ability that would allow the individual to predict future beats once the rhythm has been discovered. In one study by Jessica Grahn of Western University, brain activity was measured while participants first learned a beat (i.e., discovered a beat) and when participants were familiar with a beat (i.e., maintained an internal representation). Activity in the putamen, one part of the basal ganglia, was much higher when a familiar beat was repeatedly
presented to the participants (Grahn & Rowe, 2013).
Importantly, the basal ganglia do not work alone. As with most of our behaviours, detecting musical beats involves a number of brain areas working together as a team. When we perceive beats, there is an increase in connectivity (brain areas firing together) between the basal ganglia and areas of the frontal lobe
related to the planning of movements (Grahn & Rowe, 2009). In fact, one study showed that this coordinated brain activity
increased as the beat became more noticeable (Chen et al., 2008); however, more research is needed before we draw any definitive conclusions.
Can we critically evaluate this information? Although the evidence linking the basal ganglia to our ability to maintain a musical beat is compelling, we need to remember that brain imaging experiments show which areas of the brain are
active; this does not guarantee that these regions are necessary for a function to occur. We therefore need evidence from other types of research studies to support this finding. Recently, researchers found that individuals with Parkinson’s disease—who have damage to structures that input to the basal ganglia—have
difficulty picking out subtle musical beats (Grahn, 2009).
The basal ganglia is a group of structures in the centre of your brain. Activity in this region is related to our ability to detect musical beats.
However, it is still possible that previous experience influenced these results to some degree. Almost everyone has heard musical beats; this previous knowledge might influence how we perceive new beats. Although this problem might seem impossible to solve, music researchers have found an interesting solution: play musical beats to animals. To do this, researchers measured the firing rates of brain cells in monkeys while they listened to repeated beats and random noise. Greater firing occurred in the putamen (basal ganglia) of monkeys when they
heard a familiar beat (Barolo et al., 2014). Therefore, there is evidence from multiple types of research studies linking the perception of music to brain areas related to movement, specifically the basal ganglia.
Why is this relevant? The link between musical beats and movement systems should
make intuitive sense to most of you; it’s almost impossible to listen to music without moving in some way. Musical beats allows people to synchronize movements with each other, leading to coordinated behaviours ranging from dancing to rocking a baby to sleep. Interestingly, this ability is influenced by culture. Growing up in a given culture leads us to be more familiar with some musical rules and patterns than others; as a result, people from different cultures will have different rhythmic expectations and will
therefore be more sensitive to certain musical rhythms (Levitin, 2006).
As you can see, the detection of musical beats influences many aspects of our lives. But, discussing beats in terms of movement systems only tells part of the story. Think about the last time you danced; as you were moving, your body was adjusting its position so that you were (hopefully) able to avoid falling on your face. The body’s ability to do so leads us to a discussion of another role played by the structures found within our ears: balance.
The vestibular system in the inner ear provides information about the head’s movement and spatial orientation. It is crucial for our sense of balance. Sports such as gymnastics and freestyle skiing rely heavily on this system.
Brian Peterson/ZUMA Press Inc/Alamy Stock Photo
Module 4.3b Quiz:
The Perception of Sound
Know . . . 1. The primary auditory cortex is found in which lobe of the brain?
A. Frontal B. Temporal C. Occipital D. Parietal
Understand . . . 2. explains pitch perception when hair cells are stimulated at the same
rate that a sound wave cycles.
A. Place theory B. Frequency theory C. The volley principle D. Switch theory
3. Neurons cannot fire fast enough to keep up with high-pitched sound waves. Therefore, they alternate firing according to the .
A. place theory B. frequency theory C. volley principle D. switch theory
Apply . . . 4. While crossing the street, you know a car is approaching on your left side
because
A. the left ear got the information just a fraction of a second before the right ear.
B. the right ear got the information just a fraction of a second before
the left ear.
C. the right ear experienced the sound more intensely than the left ear.
D. both ears experienced the sound at the same intensity.
The Vestibular System
On February 10, 2014, Canadian freestyle skier Alexandre Bilodeau stood at the top of the moguls course at the Rosa Khudor Extreme Park in Sochi, Russia. His Russian rival, Alexandr Smyshlyaev, had just amazed the crowd by performing a
flip while grabbing his skis after going over one of the two jumps on the course. Bilodeau needed to put in an almost perfect run if he was to repeat as Olympic gold medallist. As he began the course, Bilodeau maintained his balance while carving perfect turns around the moguls. As his descent continued, he picked up more speed and hurtled toward the first jump, which had caused many of his competitors to fall. Undaunted, he leapt up, performed multiple twists in the air, and landed with his feet again in perfect moguls stance. He continued down the course and picked up even more speed before taunting gravity again with a dazzling display of twists and flips before racing down across the finish line. The gold was his. When we watch breathtaking feats of athleticism like Bilodeau’s, it’s easy to forget that these abilities rely on our perceptual abilities. In the case of freestyle skiing, the ability to maintain one’s balance is related to the activity of two structures in the inner part of the ears.
Sensation and the Vestibular System
Our sense of balance is controlled, at least in part, by our vestibular system , a sensory system in the ear that provides information about spatial orientation of the head as well as head motion. This system consists of two groups of structures (see Figure 4.34 ). The vestibular sacs are structures that influence your ability to detect when your head is no longer in an upright position. This section of your vestibular system is made up of two parts, the utricle (“little pouch”) and the saccule (“little sac”). The bottom of both of these sacs is lined
with cilia (small hair cells) embedded in a gelatinous substance. When you tilt your head, the gelatin moves and causes the cilia to bend. This bending of the cilia opens up ion channels, leading to an action potential.
Figure 4.34 The Vestibular System The vestibular system consists of two groups of structures. The vestibular sacs detect our head’s position, particularly when it is no longer upright. The semicircular canals—shown in detail on the left—detect when our head is in motion. Both structures send information to nuclei in the brainstem.
Your ability to perceive when your head is in motion involves a separate group of
vestibular structures. The semicircular canals are three fluid-filled canals found in the inner ear that respond when your head moves in different directions (up-down, left-right, forward-backward). Receptors in each of these canals respond to movement along one of these planes. At the base of each of these
canals is an enlarged area called the ampulla. The neural activity within the ampulla is similar to that of the vestibular sacs—cilia (hair cells) are embedded within a gelatinous mass. When you move your head in different directions, as Alexandre Bilodeau did during his flips, the gelatin moves and causes the cilia to bend. This bending, again, makes an action potential more likely to occur.
Although it may seem as though the vestibular system would only fire when we moved our heads in different directions, the vestibular sacs and semicircular
canals actually provide the brain with a continuous flow of information about the
head’s position and movement (Tascioglu, 2005). This constant input from the vestibular system allows us to keep our head upright and to maintain our balance. When you have an inner ear infection, this stream of input can be disrupted. The result is dizziness and a loss of balance.
The Vestibular System and the Brain
Of course, for the activity of the vestibular sacs and semicircular canals to have an effect on our perceptual experiences, they need to transmit information from the inner ear to the brain. These two parts of the vestibular system send information along the vestibular ganglion, a large nerve fibre, to nuclei in the brainstem. Vestibular nuclei can then influence activity in a number of brain areas. For instance, the panic we feel when we lean too far back in a chair is likely due to the fact that vestibular nuclei in the brainstem influence the activity of your autonomic nervous system (“fight or flight”) as well as the amygdala, an
emotion centre of the brain (Petrovich & Swanson, 1997; Carmona et al., 2009). The vestibular nuclei also project to part of the insula, an area of cortex that is folded in the interior of the brain (de Waele et al., 2001; Guldin & Grusser, 1998). This region helps us link together visual, somatosensory, and vestibular information. At times, however, this process goes awry.
Have you ever experienced motion sickness, perhaps when trying to read while in moving vehicle? One reason for this feeling is an inconsistency in the input from your visual and vestibular systems. The visual input (i.e., the words on the page) is not moving, yet your vestibular system is sending signals to your brain saying that your body is in a moving car. The driver, on the other hand, sees (and controls) the movement of the car; he or she therefore has the same movement-related information arriving from both sensory systems.
This link between the vestibular system and other senses brings us back to the example of Alexandre Bilodeau, the freestyle skier discussed earlier in this section. In order to maintain balance, Bilodeau had to receive input from his vestibular sacs and semicircular canals. But, he also needed to have information
about kinesthesis, the sense of bodily motion and position (see Module 4.4 ).
Together, this input allowed Bilodeau to maintain his balance while he performed his gravity-defying jumps and to continue skiing around the moguls when he landed. Without these inner ear structures and feedback from his body, Bilodeau’s trip to the Sochi Olympics would certainly have been less golden.
Module 4.3c Quiz:
The Vestibular System
Know . . . 1. The structures that detect head motion are known as the .
A. vestibular sacs B. ossicles C. tympanic membranes D. semicircular canals
Apply . . . 2. Mr. Cerveaux went to his doctor to complain about dizziness and
problems with balance. Which of the following is NOT a likely explanation for his symptoms?
A. Mr. Cerveaux might have a tumour affecting his vestibular nerve. B. Mr. Cerveaux experienced brain damage that affected his left and
right occipital lobes.
C. Mr. Cerveaux might have an inner ear infection. D. Mr. Cerveaux might have had a small stroke (a blockage of a
blood vessel in the brain) that damaged his insula.
Module 4.3 Summary
cochlea
frequency theory
pitch
Know . . . the key terminology relating to the ear and hearing.4.3a
place theory of hearing
primary auditory cortex
semicircular canals
sound localization
vestibular sacs
vestibular system
Sound can be analyzed based on its frequency (the number of cycles a sound wave travels per second) as well as on its amplitude (the height of a sound wave). Our experience of pitch is based on sound wave frequencies. Amplitude corresponds to loudness: The higher the amplitude, the louder the sound.
The vestibular system consists of two components, the vestibular sacs and the semicircular canals. The vestibular sacs note the position of the head relative to the body. The semicircular canals note when the head is in motion. Both structures send information to brain regions that integrate vestibular information with input from other senses; this process allows us to maintain our balance.
Apply Activity Get a friend to participate in a quick localization demonstration. Have her sit with her eyes closed, covering her right ear with her hand. Now walk quietly in a circle around your friend, stopping occasionally to snap your fingers. When you do this, your friend should point to where you are standing, based solely on the sound. If her right ear is covered, at which points will she be most accurate? At which
Understand . . . different characteristics of sound and how they correspond to perception.
4.3b
Understand . . . how the vestibular system affects our sense of balance.
4.3c
Apply . . . your knowledge of sound localization.4.3d
points will she have the most errors? Use the principles of sound localization to make your predictions.
It seems intuitive that music and movement are related. However, testing this relationship involves critical thinking. Although brain imaging studies in healthy individuals have shown basal ganglia activity when people follow beats, we must
remember that this activity does not mean that the basal ganglia are necessary for beat perception. However, studies of patients with damage to the basal ganglia, structures in the middle of the brain related to movement, show that
these structures are likely necessary for us to be able to follow a musical beat. Together, these studies provide a scientific explanation for our ability to tap our fingers to the rhythm of our favourite songs.
Analyze . . . how musical beats are related to movement.4.3e
Module 4.4 Touch and the Chemical Senses
tuja66/Getty Images
Learning Objectives
Would you ever describe your breakfast cereal as tasting pointy or round? Probably not. Touch, taste, and smell combine together to make your favourite foods, yet most of us can still identify the separate components associated with what is felt, tasted, and smelled. Individuals with a condition called synesthesia experience blended perceptions, such that affected individuals might actually hear
colours or feel sounds (Cytowic, 1993). For the individuals who experience this condition, even letters or numbers may have a colour associated with them. To illustrate this effect, find the number 2 below:
People who have a type of synesthesia in which words or numbers have unique colours associated with them find the 2 faster than people without synesthesia because the colours cause the 2 to “pop
out” (Blake et al., 2005). In some individuals, even the idea of a number can elicit a colourful response (Dixon et al., 2000). Synesthesia can also involve blending taste and touch, which certainly can influence dining experiences. People may avoid oatmeal because it tastes bland, but can you imagine avoiding a food because it tastes “pointy,” or relishing another food because of its delicate hints of corduroy? Synesthesia occurs in an estimated 1 in 500 people. For the 499 others, touch,
Know . . . the key terminology of touch and chemical senses. Understand . . . how pain messages travel to the brain. Understand . . . the relationship between smell, taste, and food flavour experience. Apply . . . your knowledge about touch to describe the acuity of different areas of skin. Apply . . . your knowledge to determine whether you or someone you know is a “supertaster.” Analyze . . . how different senses are combined together.
4.4a 4.4b 4.4c 4.4d 4.4e 4.4f
55555555555555555555555555555555555555555555555555555555555552555555555555555555555555555555
taste, and smell are distinct senses.
Focus Questions
1. How are our experiences of touch, taste, and smell distinct? 2. What are the different types of sensations that are detected by our sense of touch?
Generally speaking, vision and hearing are the senses that we seem to be aware of the most and, therefore, have received the most attention from researchers. In this module, we will explore the senses of touch, taste, and smell. Putting them together in a single module is not meant to diminish their importance, however. Our quality of life, and possibly our survival, would be severely compromised without these senses. We will also
examine how we combine information from our different senses into vibrant multimodal experiences, such as when taste and smell are combined to create a perception of flavour.
The Sense of Touch
The sense of touch allows us to actively investigate our environment and the objects that are in it (Lederman & Klatzky, 2004; Lederman et al., 2007). Using touch, we can acquire information about texture, temperature, and pressure upon the skin. These different forms of stimulation are combined to give us a vivid
physical sense of every moment. Imagine you’re at a concert. You don’t just hear music. You feel the vibrations of the bass rippling through you. You feel the heat of the crowd. You feel other people brushing up against you. And, you feel your own body moving to the rhythm of the music. These sensual experiences— which seem so social and so distant from the nervous system—are dependent on the actions of several
types of receptors located just beneath the surface of the skin, and also in the muscles, joints, and tendons.
These receptors send information to the somatosensory cortex in the parietal lobes of the brain, the neural region associated with your sense of touch.
Sensitivity to touch varies across different regions of the body. One simple method of testing sensitivity, or
acuity, is to use the two-point threshold test shown in Figure 4.35 . Regions with high acuity, such as the fingertips, can detect the two separate, but closely spaced, pressure points of the device, whereas less sensitive regions such as the lower back will perceive the same stimuli as only one pressure point. Body parts such as the fingertips, palms, and lips are highly sensitive to touch compared to regions such as the calves and forearm. Research has shown that women have a slightly more refined sense of touch than men,
precisely because their fingers (and therefore their receptors) are smaller (Peters et al., 2009). Importantly, the sensitivity of different parts of the body also influences how much space in the somatosensory cortex is
dedicated to analyzing each body part’s sensations (see Figure 3.27 in Module 3.3 ). Regions of the body that send a lot of sensory input to the brain such as the lips have taken over large portions of the
somatosensory cortex while less sensitive regions like the thigh use much less neural space (see Figure 4.36 ).
Figure 4.35 Two-Point Threshold Device for Measuring Touch Acuity The more sensitive regions of the body can detect two points even when they are spaced very close together. Less sensitive parts of the body have much larger two-point thresholds.
Figure 4.36 The Sensory Homunculus
Sensitive areas of the body used to acquire somatosensory information use larger portions of the somatosensory cortex than less sensitive body parts. The amount of cortex used by each body part is represented in the homunculus (“little man”) depicted below. BSIP SA/Alamy Stock Photo
Like vision and hearing, touch is very sensitive to change. Merely laying your hand on the surface of an object does little to help identify it. What we need is an active exploration that stimulates receptors in the
hand. Haptics is the active, exploratory aspect of touch sensation and perception. Active touch involves feedback. For example, as you handle an object, such as a piece of fruit, you move your fingers over its surface to identify whether any faults may be present. Your fingertips can help you determine whether the object is the appropriate shape and can detect bruising or abnormalities that may make it unsuitable to eat. Haptics allows us not only to identify objects, but also to avoid damaging or dropping them. Fingers and
hands coordinate their movements using a complementary body sense called kinesthesis , the sense of bodily motion and position. Receptors for kinesthesis reside in the muscles, joints, and tendons. These receptors transmit information about movement and the position of your muscles, limbs, and joints to the
brain (Figure 4.37 ). As you handle an object, your kinesthetic sense allows you to hold it with enough resistance to avoid dropping it, and to keep your hands and fingers set in such a way as to avoid letting it roll out of your hands. Touch, therefore, provides us with a great deal of information about our bodies and the world around us.
Figure 4.37 The Sense of Kinesthesis Receptors in muscles and joints send sensory messages to the brain, helping us maintain awareness and control of our movements. Muscle spindles and Golgi tendon organs are sensory receptors that provide information about changes in muscle length and tension. Source: From KALAT. Biological Psychology, 10E. © 2009 South-Western, a part of Cengage Learning, Inc. Reproduced by permission. www.cengage.com/permissions
Feeling Pain
Of course, not all of the information we receive from our sense of touch is pleasant. Nociception is the activity of nerve pathways that respond to uncomfortable stimulation. Our skin, teeth, corneas, and internal organs contain nerve endings called nociceptors, which are receptors that initiate pain messages that travel to the central nervous system (see Figure 4.38 ). Nociceptors come in varieties that respond to various types of stimuli—for example, to sharp stimulation, such as a pin prick, or to extreme heat or cold (Julius & Basbaum, 2001).
Figure 4.38 Cross-Section of Skin and Free Nerve Endings That Respond to Pain The nerve endings that respond to pain reside very close to the surface of the skin and, as you are likely aware, are very sensitive to stimulation. Source: Ciccarelli, Saundra K.; White, J. Noland, Psychology, 3rd Ed., © 2012, pp. 96, 109. Reprinted and electronically reproduced by permission of Pearson
Education, Inc., New York, NY.
Two types of nerve fibres transmit pain messages. Fast fibres register sharp, immediate pain, such as the pain felt when your skin is scraped or cut. Slow fibres register chronic, dull pain, such as the lingering
feelings of bumping your knee into the coffee table. Although both slow and fast fibres eventually send input to the brain, these impulses first must travel to cells in the spinal cord; the firing of neurons within the spinal cord will influence how this pain is experienced.
The activity of pathways in the spinal cord can explain several interesting characteristics of pain perception, including why you feel better if you rub your toe after stubbing it on your coffee table. One long-held theory of
pain perception is the gate-control theory , which explains our experience of pain as an interaction between nerves that transmit pain messages and those that inhibit these messages. According to this theory, cells in the spinal cord regulate how much pain signalling reaches the brain. The spinal cord serves as a
“neural gate” that pain messages must pass through (Melzack & Wall, 1965, 1982). The spinal cord contains small nerve fibres that conduct pain messages and larger nerve fibres that conduct other sensory signals such as those associated with rubbing, pinching, and tickling sensations. Stimulation of the small pain fibres results in the experience of pain, whereas the larger fibres inhibit pain signals so that other sensory information can be sent to the brain. Thus, the large fibres close the gate that is opened by the smaller fibres. According to gate-control theory, if you stub your toe, rubbing the area around the toe may alleviate some of the pain because the large fibres carrying the message about touch inhibit the firing of smaller fibres carrying pain signals. Likewise, putting ice on an injury reduces pain by overriding the signals transmitted by the small fibres.
The gate-control theory provided an important first step in our understanding of pain. Updates of this theory
have allowed researchers to explain even more pain-related experiences (Melzack & Katz, 2013). Our experience of pain obviously involves input from the spinal cord to the somatosensory cortex—this provides our brain with information about the location of the aversive stimulation. However, pain is not just sensation gone awry. Expectations and memory can both increase (or decrease) your feelings of pain. Attention, too, can influence how painful a stimulus seems. If you focus all of your attention on the pain, it will feel worse than if you’re focusing on something else. Pain is also related to emotions; negative emotions increase the
perception of pain (Loggia et al., 2008b). As shown in Figure 4.39 , these cognitive, sensory, and emotional factors all interact to influence nociception. This interaction is why the same painful stimulus might rate as a 5/10 on a pain scale one day and as a 7/10 another day—cognitive and emotional factors likely differed between the two days.
Figure 4.39 Multiple Factors Influence Pain-Related Behaviours Cognitive, sensory, and emotional factors all influence how we experience pain. Importantly, pain also leads to multiple behavioural responses, including stress. This likely explains why different people—including some patient populations—are particularly sensitive to painful stimuli. Source: From Pain, WIREs Cognitive Science, Vol 4, Issue 1 by Ronald Melzack, Joel Katz. Copyright © 2012 John Wiley & Sons, Inc. Reproduced with permission of
John Wiley & Sons, Inc.
This updated view of pain also helps explain why different people produce different pain-related responses. Our response to pain isn’t simply, “Ouch!” It involves the feeling of pain, as well as some form of movement and an emotional or stress-related response to being in pain. Many of these responses involve the anterior
cingulate gyrus, a brain area above the corpus callosum that forms networks with many structures in the limbic system.
Our discussion thus far has focused on how we perceive pain when it affects our own body. But, how do you
feel when you see someone else in pain? And, does the pain of other people affect how your own pain feels? Psychology researchers have begun to address these complicated—and fascinating—questions.
Working the Scientific Literacy Model Empathy and Pain
A running theme of this chapter has been that sensation and perception involve an interaction
with your environment. While the term environment often makes people think of birds, trees, and buildings, a key part of our environment is other people. Is it possible for one person’s somatosensory experiences to influence those of another person?
What do we know about empathy and pain? We’ve all seen someone in pain. Sometimes it’s a friend stubbing his toe on a chair; other times it’s a person rubbing her foot after stepping on a piece of Lego. Our experi ence of these situations differs a great deal. If we see someone we care about in pain, we experience negative emotions and sometimes even feel pain ourselves. If it is a stranger or someone we don’t like, our reaction might be less intense. This leads to several interesting questions. Are we able to feel the pain of others? Under what conditions? And how does the presence of another person influence how we experience pain?
How does science explain the influence of empathy on pain perception?
The power of emotion in the experience of pain is profound. In one study, researchers at McGill University asked participants to immerse their right hand in hot water while viewing emotionally negative videos (disaster scenes) and neutral videos (cityscape scenes). Participants rated the unpleasantness of the pain as being higher when they watched disaster
scenes (Loggia et al., 2008a). These results suggest that the emotional component of pain can influence our physical sensations, particularly when it involves seeing the suffering of others.
In another study, these researchers asked participants to feel either high or low levels of empathy for an actor in a video. The researchers then measured the participants’ sensitivity to painful heat stimuli while they watched the actor experience similar stimulation. Participants who felt empathy for the actor reported experiencing higher levels of pain than did low- empathy participants. This result suggests that emotionally connecting with someone else in
pain can influence our own sensitivity (Loggia et al., 2008b).
Can we critically evaluate the research? An obvious criticism of research studies involving emotion and the experience of pain is that the participants may simply be reporting what they think the experimenters want to hear. If you were in a study in which someone was manipulating your mood, you would likely be able to predict the hypotheses being tested in that study. It is therefore necessary to find additional support for these self-report experiments. Numerous neuroimaging studies have found that activity in a brain structure called the insula (near the junction of the frontal lobes and the top
of the temporal lobes) is related to the awareness of bodily sensations (Wiens, 2005). Activity in the insula also increases when people are performing empathy-related tasks (Fukushima et al., 2011). Thus, there might be a biological link between feeling pain and feeling empathy.
Stronger support comes from studies that show an effect of empathy on pain perception in
individuals that are much less likely to be influenced by the experimenter’s expectations: mice! When injected with a pain-inducing substance, mice that were tested in pairs showed more pain-related behaviours than did mice that were tested alone. But, this effect only occurred when the mice were cagemates with their test partner (i.e., they knew the other mouse)! Additionally, observing a cagemate in pain altered the mouse’s own pain sensitivity,
suggesting that these animals are capable of some form of empathy (Langford et al., 2006). Even more remarkable, some male mice refused to show pain responses in the presence of mice they didn’t know (a mouse version of acting tough); this effect, not surprisingly, appears
to be dependent upon the hormone testosterone (Langford et al., 2011; see Module 3.2 ). Taken together, these neuroimaging and animal-based studies suggest that our own pain can be dramatically influenced by the pain of those around us.
Why is this relevant? These studies demonstrate that our sensations, particularly pain, can be influenced by the experiences of other people. Feeling negative emotions or seeing someone else feel pain makes our own pain more unpleasant. Although these studies might seem a bit morbid, they do offer an incredibly important insight that could affect the well-being of many people. If people can influence each other’s negative sensations, then it should be possible to influence each other’s positive sensations. Just as pain can be “contagious,” so too might happiness and well-being.
Phantom Limb Pain
Astonishingly, it is possible for people to feel pain in body parts that no longer exist. Phantom limb
sensations are frequently experienced by amputees, who report pain and other sensations coming from the absent limb. Amputees describe such sensations as itching, muscle contractions, and, most unfortunately, pain. One explanation for phantom pain suggests that rewiring occurs in the brain following the loss of the limb. After limb amputation, the area of the somatosensory cortex formerly associated with that body part is no longer stimulated by the lost limb. Thus, if someone has her left arm amputated, the right somatosensory cortex that registers sensations from the left arm no longer has any input from this limb. Healthy nerve cells become hypersensitive when they lose connections. The phantom sensations, including pain, may occur because the nerve cells in the cortex continue to be active, despite the absence of any input from the body.
One ingenious treatment for phantom pain involves the mirror box (Figure 4.40 ). This apparatus uses the reflection of the amputee’s existing limb, such as an arm and hand, to create the visual appearance of having both limbs. Amputees often find that watching themselves move and stretch the phantom hand, which is actually the mirror image of the real hand, results in a significant decrease in phantom pain and in both
physical and emotional discomfort (Ramachandran & Altschuler, 2009).
Figure 4.40 A Mirror Box Used in Therapy for People with Limb Amputation In this case, a woman who has lost her left arm can experience some relief from phantom pain by moving her intact hand, such as by unclenching her fist. In turn, she will experience relief from phantom pain corresponding to her left side. Source: Lilienfeld, Scott O.; Lynn, Steven J; Namy, Laura L.; Woolf, Nancy J., Psychology: From Inquiry to Understanding, 2nd Ed., ©2011, pp.157. Reprinted and
Electronically reproduced by permission of Pearson Education, Inc., New York, NY.
Researchers have conducted experiments to determine how well mirror box therapy works compared both to a control condition and to mentally visualizing the presence of a phantom hand. Over the course of four weeks of regular testing, the people who used the mirror box had significantly reduced pain compared to a control group who used the same mirror apparatus, except the mirror was covered; they also had less pain
than a group who used mental visualization (Figure 4.41 ; Chan et al., 2007). Notice in Figure 4.40
that everyone was given mirror therapy after the fourth week of the study, and that the procedure seemed to have lasting, positive benefits. No one is sure why mirror box therapy works, but evidence suggests that the short-term benefits are due to how compelling the illusion is; in the long term, this therapy may actually result
in reorganization of the somatosensory cortex (Ramachandran & Altschuler, 2009).
Figure 4.41 Mirror Box Therapy Compared to Mental Visualization and a Control Condition Source: Chan, B. L ., et. al., (2006). Mirror Therapy for Phantom Limb Pain, The New England Journal of Medicine, 357 (21), 2206, Massachusetts Medical Society,
2007.
Module 4.4a Quiz:
The Sense of Touch
Know . . . 1. The sense associated with actively touching objects is known as .
A. tactile agnosia B. haptics C. nociception D. gestation
2. Phantom limb sensations are A. sensations that arise from a limb that has been amputated. B. sensations that are not perceived. C. sensations from stimuli that do not reach conscious awareness. D. sensations from stimuli that you typically identify as intense, such as a burn, but that feel dull.
Understand . . . 3. Nociceptors send pain signals to both the and the .
A. occipital lobe; hypothalamus B. cerebellum; somatosensory cortex C. somatosensory cortex; anterior cingulate gyrus D. occipital lobe; cochlea
Apply . . . 4. A student gently touches a staple to her fingertip and to the back of her arm near her elbow. How are
these sensations likely to differ? Or would they feel similar?
A. The sensation would feel like two points on the fingertip but is likely to feel like only one point
on the arm.
B. The sensations would feel identical because the same object touches both locations. C. The sensation would feel like touch on the fingertips but like pain on the elbow. D. The sensation would feel like two points on the arm but is likely to feel like only one point on
the fingertip.
The Chemical Senses: Taste and Smell
The chemical senses comprise a combination of both taste and smell. Although they are distinct sensory systems, both begin the sensory process with chemicals activating receptors on the tongue and mouth, as well as in the nose.
The Gustatory System: Taste
The gustatory system functions in the sensation and perception of taste. But, what exactly is this system tasting? Approximately 2500 identifiable chemical compounds are found in the food we eat (Taylor & Hort, 2004). When combined, these compounds give us an enormous diversity of taste sensations. The primary tastes include salty, sweet, bitter, and sour. In addition, a fifth taste, called umami, has been identified (Chaudhari et al., 2000). Umami, sometimes referred to as “savouriness,” is a Japanese word that refers to tastes associated with seaweed, the seasoning monosodium glutamate (MSG), and protein-rich foods such as milk and aged cheese.
Taste is registered primarily on the tongue, where roughly 9000 taste buds reside. On average,
approximately 1000 taste buds are also found throughout the sides and roof of the mouth (Miller & Reedy, 1990). Sensory neurons that transmit signals from the taste buds respond to different types of stimuli, but most tend to respond best to a particular taste. Our experience of taste reflects an overall pattern of activity
across many neurons, and generally comes from stimulation of the entire tongue rather than just specific, localized regions. The middle of the tongue has very few taste receptors, giving it a similar character to the
blind spot on the retina (Module 4.2 ). We do not feel or sense the blind spot of the tongue because the sensory information is filled in, just as we find with vision. Taste receptors replenish themselves every 10 days throughout the life span—the only type of sensory receptor to do so.
Receptors for taste are located in the visible, small bumps (papillae) that are distributed over the surface of the tongue. The papillae are lined with taste buds. Figure 4.42 shows papillae, taste buds, and an enlarged view of an individual taste bud and a sensory neuron’s dendrites and axon that sends a message to the brain. The bundles of nerves that register taste at the taste buds send the signal through the thalamus
and on to higher-level regions of the brain, including the gustatory cortex; this region is located in the back of the frontal lobes and extends inward to the insula (near the top of the temporal lobe). Another region, the
secondary gustatory cortex, processes the pleasurable experiences associated with food.
Figure 4.42 Papillae and Taste Buds The tongue is lined with papillae (the bumpy surfaces). Within these papillae are your taste buds, the tiny receptors to which chemicals bind. Source: Lilienfeld, Scott O.; Lynn, Steven; Namy, Laura L.; Woolf, Nancy J., Psychology: From Inquiry To Understanding, Books A La Carte Edition, 2nd Ed., ©2011.
Reprinted and Electronically reproduced by permission of Pearson Education, Inc., New York, NY.
Why do some people experience tastes vividly while other people do not? One reason is that the number of taste buds present on the tongue influences the psychological experience of taste. Although approximately 9000 taste buds is the average number found on the human tongue, there is wide variation among
individuals. Some people may have many times this number. Supertasters, who account for approximately 25% of the population, are especially sensitive to bitter tastes such as those of broccoli and black coffee.
They typically have lower rates of obesity and cardiovascular disease, possibly because they tend not to
prefer fatty and sweet foods. Figure 4.43 shows the number of papillae, and hence taste buds, possessed by a supertaster compared to those without this ability.
Figure 4.43 Density of Papillae, and Hence Taste Buds, in a Supertaster and in a Normal Taster Some of the individual differences in taste sensitivity may be due to the number of taste buds found on the
tongue. Supertasters (left tongue) have many more taste buds than the average person (right tongue). Source: Lilienfeld, Scott O.; Lynn, Steven; Namy, Laura L.; Woolf, Nancy J., Psychology: From Inquiry To Understanding, Books A La Carte Edition, 2nd Ed., © 2011.
Reprinted and Electronically reproduced by permission of Pearson Education, Inc., New York, NY.
How much of our taste preferences are learned and how much are innate? Like most of our behaviours, there is no simple answer. Human infants tend to prefer the foods consumed by their mothers during
gestation (Beauchamp & Mennella, 2009). Soon after starting solid foods, children begin to acquire a taste for the foods prevalent in their culture. Would you eat a piece of bread smeared with a sticky brown paste that was processed from wasted yeast from a brewery? This product, called vegemite, is actually quite popular among people in Switzerland, Australia, and New Zealand. People brought up eating vegemite may love it, while most others find it tastes like death. The Masai people of Kenya and Tanzania enjoy eating a coagulated mixture of cow’s blood and milk. These foods may sound unappetizing to you. Of course, non- Canadians are often repulsed by poutine, a decadent mixture of french fries, cheese curds, and gravy, so we should be careful not to judge . . . too much.
Closely related to taste is our sense of smell, which senses the chemical environment via a different mode than does taste.
The Olfactory System: Smell
The olfactory system is involved in smell—the detection of airborne particles with specialized receptors located in the nose. Our sensation of smell begins with nasal air flow bringing in molecules that bind with receptors at the top of the nasal cavity. (So, when you smell something, you are actually taking in part of the
environment—including other people—into your body.) Within the nasal cavity is the olfactory epithelium , a thin layer of cells that are lined by sensory receptors called cilia—tiny hair-like projections
that contain specialized proteins that bind with the airborne molecules that enter the nasal cavity (Figure 4.44 ). Humans have roughly 1000 different types of odour receptors in their olfactory system, but can identify approximately 10 000 different smells. How is this possible? The answer is that it is the pattern of the stimulation, involving more than one receptor, which gives rise to the experience of a particular smell (Buck & Axel, 1991). Different combinations of cilia are stimulated in response to different odours.
Figure 4.44 The Olfactory System Lining the olfactory epithelium are tiny cilia that collect airborne chemicals, sending sensory messages to the nerve fibres that make up the olfactory bulb.
These groups of cilia then transmit messages directly to neurons that converge on the olfactory bulb on the bottom surface of the frontal lobes, which serves as the brain’s central region for processing smells.
(Unlike our other senses, olfaction does not involve the thalamus.) The olfactory bulb connects with several regions of the brain through the olfactory tract, including the limbic system (emotion) as well as regions of the cortex where the subjective experience of pleasure (or disgust) occurs.
Module 4.4b Quiz:
The Chemical Senses: Taste and Smell
Know . . . 1. The bumps that line the tongue surface and house our taste buds are called .
A. epithelia B. gustates C. the gustatory cortex D. papillae
2. Where are the receptor cells for smell located? A. The papillae B. The olfactory epithelium C. The olfactory bulb D. The odour buds
Apply . . . 3. After eating grape lollipops, you and a friend notice that your tongues have turned purple. With the
change in colour, it is easy to notice that there are many more papillae on your friend’s tongue. Who is more likely to be a supertaster?
A. You are, because you have fewer, and therefore more distinct, papillae. B. Your friend is, because she has many more papillae, and therefore many more taste buds, to
taste with.
C. You are, because less dye stuck to your tongue, allowing you to taste more. D. It could be either of you because supertasting is unrelated to the number of papillae.
Multimodal Integration
Modules 4.2 –4.4 have described our five different, most commonly discussed, sensory systems. After reading about them, it is quite tempting to view the five systems as being distinct from one another. After all, our brains are set up in such a way that it is simple to separate the different senses. Indeed, the doctrine of
specific energies stated in 1826 that our senses are separated in the brain (see Module 4.1 ). However, this view is at odds with some of our sensory experiences. Many of these experiences are actually combinations of multiple types of sensations, just as they are in individuals with synesthesia, the condition discussed at the beginning of this module. For example, the perceptual experience of flavour combines taste
and smell (Small et al., 1997). You have probably noticed that when you have nasal congestion, your experience of flavour is diminished. You may also have noticed a child plugging his nose when he has to eat or drink something that tastes bad. This loss of taste occurs because approximately 80% of our information
about food comes from olfaction (Murphy et al., 1977). This link between taste and smell is a perfect example of multimodal integration , the ability to combine sensation from different modalities such as vision and hearing into a single integrated perception.
What Is Multimodal Integration? Multimodal integration is so much more than simply combining different senses. In fact, it’s a form of problem-solving performed by your brain hundreds of times each day. We must decide, almost instantaneously, if two types of sensation should be integrated into a multimodal perception. How do we do this? One factor is whether the different sensations are in a similar location. If you hear a “meow” and see a
cat with its mouth open, you infer that the movements of the cat’s mouth and the “meow” sound were linked together. We also make use of temporal information. Sensations that occur in roughly the same time period are more likely to be linked than those that are not. If you hear a “meow” five seconds before the cat’s mouth moved, you will not likely combine the sound with the sight of the cat (unless you know your cat is a ventriloquist).
Multimodal integration occurs quite naturally—we’re often unaware of these perceptions until some outside force interferes with it. You may have experienced watching a television show or YouTube clip in which the movement of the characters’ lips didn’t match up with the sound of their voices. These perceptions are often annoying because the lag between the image and the sound makes it difficult to combine the two into the expected multimodal perception. In fact, sometimes this mismatch can interfere with perception, even to the point of producing new perceptions that did not actually occur.
This result occurred by accident in a study conducted by Harry McGurk and John MacDonald in 1976. These researchers were investigating language perception in infants and had videos of different actors producing sounds such as /ba-ba/. However, when the sound /ba-ba/ was presented during the video of someone mouthing the sound /ga-ga/, the experimenters noticed that it seemed to produce an entirely different multimodal stimulus: /da-da/. It was as though the movement of the speaker’s lips provided the viewer with the expectation of a particular sound; this expectation biased the perception of the presented
sounds. This phenomenon is now known as the McGurk Effect.
Expectations and multimodal integration can also influence our social interactions. We routinely integrate visual and auditory information when we are speaking with someone. Researchers have found that both women and men rated masculine faces (i.e., tough, rugged faces) as being more attractive when they were
matched with a masculine voice (Feinberg et al., 2008). Other studies have shown that heterosexual men preferred viewing female faces that were paired with high-pitched rather than low-pitched voices (Feinberg et al., 2005). Facial expressions of a singer also influence judgments of the emotional content of songs
(Thompson et al., 2008). These studies show us that we naturally form auditory expectations when we visually perceive a face.
Synesthesia
If our brains are set up to perceive our senses separately and then combine them only when it seems appropriate (due to location, time, and expectations), how can we explain synesthesia, the condition discussed in the opening of this module? These blended multimodal associations (e.g., chicken that tastes “pointy”) do not come and go. Rather, they occur automatically and are consistent over time
(Ramachandran & Hubbard, 2003). Why does synesthesia occur?
This question has puzzled scientists since the first reported case of synesthesia in 1812 (Sachs, 1812; Jewanski et al., 2009). To date, there is still no clear answer. Researchers have noted that synesthesia does run in families (Baron-Cohen et al., 1996). However, the exact genes involved with this condition are still unknown. In fact, researchers at the University of Waterloo found a pair of identical twins, only one of whom had synesthesia (Smilek et al., 2001)!
Synesthetes who experience colours when they see letters or numbers have stronger connections between brain areas related to colour (red) and letters/numbers (green). Source: Figure 4 from Ramachandran, V.S., and Hubbard, E.M. (2001). “Synaesthesia—A window into perception, thought and language.” JCS, 8, No. 12, pp. 3–34.
Neuroimaging studies have provided some insight into this condition. For instance, one research group tested synesthetes who have specific colour perceptions appear whenever they read a number (e.g., every time they see “2”, it appears with a yellow border). These researchers found activity in areas of the brain
related to colour perception in synesthetes, but not in non-synesthetes (Nunn et al., 2002). More recent studies suggest that the brains of people with synesthesia may contain networks that link different sensory
areas in ways not found in other people (Dovern et al., 2012).
A similar cross-wiring of brain networks may explain another unusual example of multimodal integration. Autonomous sensory meridian response (ASMR) is a condition in which specific auditory or visual stimuli trigger tingling sensations in the scalp and neck, sometimes extending across the back and shoulders (see Figure 4.45 ). What makes this condition so unusual is that many of the stimuli that trigger ASMR are social in nature, such as whispering or watching someone slowly brush her hair (Barratt & Davis, 2015). Like synesthesia, ASMR appears to be caused by unusual patterns of connections between different brain
areas (Smith et al., 2016).
Figure 4.45 Autonomous Sensory Meridian Response (ASMR) Individuals with ASMR experience tingling sensations on the scalp, shoulders, and back when they hear specific auditory and visual stimuli such as someone whispering or performing socially intimate acts such as braiding someone’s hair. Dmytro Zinkevych/123RF
Source (right): Barratt EL, Davis NJ. (2014). Autonomous Sensory Meridian Response (ASMR): A flow-like mental state. PeerJ PrePrints 2:e719v1 https://doi.org/
10.7287/peerj.preprints.719v1.
Together, these findings demonstrate a point made repeatedly in this text: Our experiences involve groups of brain areas working together. This point holds for all five of our senses, as well as for their multimodal integration.
Module 4.4c Quiz:
Multimodal Integration
Know . . . 1. Multimodal integration involves:
A. combining sensations from different senses into a single integrated perception. B. keeping different sensory inputs separate in the brain. C. different sensory inputs competing to see which one will reach conscious awareness. D. certain parts of the body being more sensitive to touch than other regions.
Understand . . . 2. The perceptual experience of flavour originates from:
A. taste cues alone. B. olfactory cues alone. C. olfactory and taste cues together. D. haptic and olfactory cues together.
Apply . . . 3. Lexi is watching a movie with her friends. When one of the characters starts whispering, Lexi
experiences a sudden tingling sensation on her scalp and neck. She has never been diagnosed with seizures or any psychological disorder. What condition would you diagnose her with?
A. Epilepsy B. Synesthesia C. Autonomous sensory meridian response D. McGurk Syndrome
Module 4.4 Summary
Know . . . the key terminology of touch and chemical senses.4.4a
Autonomous sensory meridian response
gate-control theory
gustatory system
haptics
kinesthesis
multimodal integration
nociception
olfactory bulb
olfactory epithelium
olfactory system
phantom limb sensations
According to gate-control theory, small nerve fibres carry pain messages from their source to the spinal cord, and then up to, among other regions, the anterior cingulate gyrus and somatosensory cortex. However, large nerve cells that register other types of touch sensations (such as rubbing) can override signals sent by small pain fibres.
Both senses combine to give us flavour experiences. Contact with food activates patterns of neural activity
Understand . . . how pain messages travel to the brain.4.4b
Understand . . . the relationship between smell, taste, and food flavour experience.4.4c
among nerve cells connected to the taste buds, and food odours activate patterns of nerve activity in the olfactory epithelium. The primary and secondary gustatory cortex and the olfactory bulb are involved in the perceptual experience of flavour.
Apply Activity Try creating a two-point threshold device like the one shown earlier in Figure 4.35 by straightening a paper clip and then bending it so the two points are about 5 mm apart. Gently apply them to different parts of the body—your fingertips, elbow, cheek, etc. Which parts of your body are sensitive enough to feel both points, and on which parts does it feel like a single object is touching you? Now try the experiment again with the two points closer together. Can you detect a change in acuity?
Scientists use a very precise measurement system to identify supertasters, but one less complicated way to do so is to dye your tongue by placing a drop of food colouring on it, or by eating or drinking something dark blue or purple. Next, count the number of papillae you can see in a 4 mm circle. You can accomplish this by viewing the dyed portion of your tongue through the punched hole in a sheet of loose-leaf notebook paper. If you can count more than 30 papillae, then chances are you are a supertaster. Of course, if you already know that you do not like bitter vegetables like broccoli or asparagus, then perhaps you would expect to find a high number of papillae.
Humans have five distinct types of senses. However, that does not mean that these senses always operate independently—they often interact to form more vivid experiences. The flavour of food is an experience that
Apply . . . your knowledge about touch to describe the acuity of different areas of skin.4.4d
Apply . . . your knowledge to determine whether you or someone you know is a “supertaster.”4.4e
Analyze . . . how different senses are combined together.4.4f
involves both taste and smell. Numerous other studies have shown that our visual perception interacts with our auditory system, leading us to be surprised when sounds (such as the pitch of someone’s voice) don’t match our visual expectations.
Chapter 5 Consciousness
5.1 Biological Rhythms of Consciousness: Wakefulness and Sleep What Is Sleep? 182
Module 5.1a Quiz 186
Why Do We Need Sleep? 186
Module 5.1b Quiz 189
Theories of Dreaming 190
Working the Scientific Literacy Model: Dreams, REM Sleep, and Learning 191
Module 5.1c Quiz 193
Disorders and Problems with Sleep 193
Module 5.1d Quiz 197
Module 5.1 Summary 197
5.2 Altered States of Consciousness: Hypnosis, Mind-Wandering, and Disorders of Consciousness
Hypnosis 200
Module 5.2a Quiz 202
Mind-Wandering 203
Module 5.2b Quiz 205
Disorders of Consciousness 205
Working the Scientific Literacy Model: Assessing Consciousness in the Vegetative State 207
Module 5.2c Quiz 210
Module 5.2 Summary 210
5.3 Drugs and Conscious Experience Physical and Psychological Effects of Drugs 212
Module 5.3a Quiz 214
Commonly Abused “Recreational” Drugs 215
Working the Scientific Literacy Model: Marijuana, Memory, and Cognition 219
Module 5.3b Quiz 222
Legal Drugs and Their Effects on Consciousness 222
Module 5.3c Quiz 225
Module 5.3 Summary 226
Module 5.1 Biological Rhythms of Consciousness: Wakefulness and Sleep
es/Sylvia Serrado/PhotoAlto/Alamy Stock Photo
Learning Objectives
Know . . . the key terminology associated with sleep, dreams, and sleep disorders. Understand . . . how the sleep cycle works. Understand . . . theories of why we sleep.
5.1a
5.1b 5.1c
Smashing through a window in your sleep seems perfectly plausible if it occurs as part of a dream. Mike Birbiglia did just this—but in his case, it was both dream and reality. Birbiglia is a comedian whose show, Sleepwalk with Me, is full of stories of personal and embarrassing moments, which include jumping through a second-storey window of his hotel room while he was asleep. He awoke upon landing; picked his bloodied, half-naked self up; and went to the hotel front desk to notify personnel of what happened. Perhaps his comedy is just his way of dealing with an otherwise troubling sleep problem—a serious condition called REM behaviour disorder. People with REM behaviour disorder act out their dreams, which clearly has the potential to be very dangerous. In Mike’s case, the injury was self-inflicted. Other people with the condition, however, have been known to hit or choke their bed partner. As it turns out, jumping through windows is not entirely uncommon for people with
REM behaviour disorder (Schenck et al., 2009). In this module, we explore how normal sleep works and we explain how and why sleep disorders, such as Mike Birbiglia’s, occur.
Focus Questions
1. How do body rhythms affect memory and thinking? 2. What is REM and how is it related to dreaming?
Consciousness is a person’s subjective awareness, including thoughts, perceptions, experiences of the world, and self-awareness. Every day we go through many changes in consciousness—our thoughts and perceptions are constantly adapting to new situations. In some cases, when we are paying close attention to something, we seem to be more in control of conscious experiences. In other situations, such as when we are daydreaming, consciousness seems to
Apply . . . your knowledge to identify and practise good sleep habits. Analyze . . . different theories about why we dream.
5.1d 5.1e
wander. These changes in our subjective experiences, and the difficulty in defining them, make consciousness one of the most challenging areas of psychological study. We will begin this module by exploring the alternating cycles of consciousness—sleeping and waking.
What Is Sleep?
It makes perfect sense to devote a module to a behaviour that humans spend approximately one-third of their lives doing. What happens during sleep can be just as fascinating as what happens during wakefulness. Psychologists and non- psychologists alike have long pondered some basic questions about sleep, such as “Why do we need sleep?” and “Why do we dream?” But perhaps we should begin with the most basic question: “What is sleep?”
Biological Rhythms
Life involves patterns—patterns that cycle within days, weeks, months, or years.
Organisms have evolved biological rhythms that are neatly adapted to the cycles in their environment. For example, bears are well known for hibernating during the cold winter months. Because this behaviour happens on a yearly basis, it is
part of a circannual rhythm (a term that literally means “a yearly cycle”). This type of rhythm is an example of an infradian rhythm, which is any rhythm that occurs over a period of time longer than a day. In humans, the best-known infradian rhythm is the menstrual cycle. However, most biological rhythms occur with a much greater frequency than once a month. For instance, heart rate, urination, and some hormonal activity occur in 90–120-minute cycles. These more frequent
biological rhythms are referred to as ultradian rhythms.
However, the biological rhythm that appears to have the most obvious impact
upon our lives is a cycle that occurs over the course of a day. Circadian rhythms are internally driven daily cycles of approximately 24 hours affecting physiological and behavioural processes (Halberg et al., 1959). They involve the tendency to be asleep or awake at specific times, to feel hungrier during some
parts of the day, and even the ability to concentrate better at certain times than
at others (Lavie, 2001; Verwey & Amir, 2009).
Think about your own circadian rhythms: When are you most alert? At which times of day do you feel the most tired? Night shift workers and night owls aside, we tend to get most of our sleep when it is dark outside because our circadian rhythms are regulated by daylight interacting with our nervous and endocrine (hormonal) systems. One key brain structure in this process is the
suprachiasmatic nucleus (SCN) of the hypothalamus. Cells in the retina of the eye relay messages about light levels in the environment to the SCN
(Hendrickson et al., 1972; Morin, 2013). The SCN, in turn, communicates signals about light levels with the pineal gland (see Figure 5.1 ). The pineal gland releases a hormone called melatonin, which peaks in concentration at nighttime and is reduced during wakefulness. Information about melatonin levels feeds back to the hypothalamus; this feedback helps the hypothalamus monitor melatonin levels so that the appropriate amount of this hormone is released at different times of the day.
Figure 5.1 Pathways Involved in Circadian Rhythms
Cells in the retina send messages about light levels to the suprachiasmatic nucleus, which in turn relays the information to the pineal gland, which secretes melatonin.
But what actually causes us to adopt these circadian rhythms? Why don’t we stay awake for days and then sleep all weekend? There are two explanations for
our 24-hour rhythms. One is entrainment , when biological rhythms become synchronized to external cues such as light, temperature, or even a clock. Because of its effects on the SCN-melatonin system, light is the primary
entrainment mechanism for most mammals (Rusak, 1979; Wever et al., 1983). We tend to be awake during daylight and asleep during darkness. We’re also
influenced by the time on our clocks. If you’re tired at 8 P.M., you likely try to fight your fatigue until a “normal” bed time such as 10 P.M. Why? Because we’ve been trained to believe that some times of day are associated with sleep and others are not.
However, not all of our body rhythms are products of entrainment. Instead, some
are endogenous rhythms , biological rhythms that are generated by our body independent of external cues such as light. Studying endogenous rhythms is tricky because it is difficult to remove all of the external cues from a person’s world. To overcome this problem, researchers in the 1960s and 1970s asked motivated volunteers to spend extended periods of time (months) in caves or in
isolation chambers. For instance, Jürgen Aschoff (1965; Aschoff et al., 1967; Aschoff & Wever, 1962) had participants stay in an underground chamber for four weeks. He noted that individuals tended to adopt a 25-hour day. Michel Siffre, a French cave expert, remained by himself in a dark cave for much longer durations than Aschoff’s participants: two months in 1962 and six months in 1972
(Foer & Siffre, 2008). Whenever he woke up or intended to go to sleep, he called his support team who were stationed at the entrance to the cave. Data from Siffre and a number of his subsequent participants indicated that most people fell into a 24.5-hour circadian rhythm. Although a few participants would briefly enter longer cycles—sometimes as long as 48-hour days—most people
possess an endogenous circadian rhythm that is 24–25 hours in length (Lavie, 2001; Mills, 1964).
Although our sleep–wake cycle remains relatively close to 24 hours in length throughout our lives, some patterns within our circadian rhythms do change with
age (Caci et al., 2009). As shown in Figure 5.2 , researchers have found that we need much less sleep—especially a type called REM sleep—as we move from infancy and early childhood into adulthood. Moreover, people generally experience a change in when they prefer to sleep. In your teens and 20s, many of you have (or will) become night owls who prefer to stay up late and sleep in. When given the choice, most people in this age range prefer to work, study, and
play late in the day, and then awake later in the morning (Galambos et al., 2013). Later in adulthood, many of you will find yourselves going to bed earlier and getting up earlier, and you may begin to prefer working or exercising before teenagers even begin to stir. Research shows that these patterns are more than just preferences: People actually do show higher alertness and cognitive
functioning during their preferred time of day (Cavallera & Giudici, 2008; Hahn et al., 2012). For instance, researchers at the University of Toronto have found that when older adults (approximately 60–80 years of age) are tested later in the day as opposed to early in the morning, they have a greater difficulty separating
new from old information (Hasher et al., 2002) and have a larger variability in their reaction times on a test in which they learned to pair together a digit and a
symbol (Hogan et al., 2009). These results have implications for the cognitive testing older patients receive in hospitals; clearly, these individuals will appear healthier if tested in the morning as opposed to later in the day, when their bodies are preparing to go to sleep.
Figure 5.2 Sleep Requirements Change with Age People tend to spend progressively less time sleeping as they age. The amount of a certain type of sleep, REM sleep, declines the most. Source: Based on Ontogenetic Development of the Human Sleep–Dream Cycle, Science, 152(3722): 604–619. 29 Apr 1966.
The Stages of Sleep
We have already seen how sleep fits into the daily rhythm, but if we take a closer look, we will see that sleep itself has rhythms. In order to measure these
rhythms, scientists use polysomnography , a set of objective measurements used to examine physiological variables during sleep. Some of the devices used in this type of study are familiar, such as one to measure respiration and a thermometer to measure body temperature. In addition, electrical sensors attached to the skin measure muscle activity around the eyes and other parts of the body. However, sleep cycles themselves are most often defined by the
electroencephalogram (EEG), a device that measures brain activity using sensors attached to the scalp (see Module 3.4 ).
EEGs detect changes involving the ion channels on neurons. As you read in Module 3.2 , ion channels are involved with receiving excitatory and inhibitory potentials from other cells and are also involved with the transmission of an
action potential down the axon. Each EEG sensor would receive input from hundreds (possibly thousands) of cells. The output of an EEG is a waveform, like
that shown in Figure 5.3 , representing the overall activity of these groups of neurons. These waves can be described by their frequency—the number of up- down cycles every second—and their amplitude—the height and depth of the up- down cycle. Beta waves—high-frequency, low-amplitude waves (15–30 Hz)—are characteristic of wakefulness. Their irregular nature reflects the bursts of activity in different regions of the cortex, and they are often interpreted as a sign that a person is alert. As the individual begins to shift into sleep, the waves start to
become slower, larger, and more predictable; these alpha waves (8–14 Hz) signal that a person may be daydreaming, meditating, or starting to fall asleep. These changes in the characteristics of the waves continue as we enter deeper and deeper stages of sleep.
Figure 5.3 EEG Recordings during Wakefulness and Sleep Brain waves, as measured by the frequency and amplitude of electrical activity, change over the course of the normal circadian rhythm. Beta waves are predominant during wakefulness but give way to alpha waves during periods of calm and as we drift into sleep. Theta waves are characteristic of stage 1 sleep. As we reach stage 2 sleep, the amplitude (height) of brain waves increases. During deep sleep (stages 3 and 4), the brain waves are at their highest amplitude. During REM sleep, they appear similar to the brain waves occurring when we are awake.
The EEG signals during sleep move through four different stages. In stage 1,
brain waves slow down and become higher in amplitude—these are known as
theta waves (4–8 Hz). Breathing, blood pressure, and heart rate all decrease slightly as an individual begins to sleep. However, at this stage of sleep, you are still sensitive to noises such as the television in the next room. After approximately 10 to 15 minutes, the sleeper enters stage 2, during which brain
waves continue to slow. As shown in Figure 5.3 , stage 2 includes sleep spindles (clusters of high-frequency but low-amplitude waves) and K complexes (small groups of larger amplitude waves), which are detected as periodic bursts of EEG activity. What these bursts in brain activity mean is not completely understood, but evidence suggests they may play a role in helping maintain a
state of sleep and in the process of memory storage (Fogel et al., 2007; Gais et al., 2002)—a topic we cover more fully later on.
Using physiological recording devices, sleep researchers and doctors can monitor eye movements, brain waves, and other physiological processes.
Hank Morgan/Photo Researchers, Inc./Science Source
As stage 2 sleep progresses, we respond to fewer and fewer external stimuli, such as lights and sounds. Approximately 20 minutes later, we enter stage 3 sleep, in which brain waves continue to slow down and assume a new form
called delta waves (large, looping waves that are high-amplitude and low- frequency—typically less than 3 Hz). The process continues with the deepest stage of sleep, stage 4, during which time the sleeper will be difficult to awaken.
About an hour after falling asleep, we reach the end of our first stage 4 sleep phase. At this point, the sleep cycle goes in reverse and we move back toward
stage 2. From there, we move into a unique stage of REM sleep —a stage of sleep characterized by quickening brain waves, inhibited body movement, and rapid eye movements (REM). This stage is sometimes known as paradoxical sleep because the EEG waves appear to represent a state of wakefulness despite the fact that we remain asleep. The REM pattern is so distinct that the
first four stages are known collectively as non-REM (NREM) sleep. At the end of the first REM phase, we cycle back toward deep sleep stages and back into REM sleep again every 90 to 100 minutes. (Think back to the beginning of this module: What type of biological rhythm would a 90–100-minute cycle represent?)
The sleep cycle through a typical night of sleep is summarized in Figure 5.4 . As shown in the figure, the deeper stages of sleep (3 and 4) predominate during the earlier portions of the sleep cycle, but gradually give way to longer REM periods.
Figure 5.4 Order and Duration of Sleep Stages through a Typical Night Our sleep stages progress through a characteristic pattern. The first half of a normal night of sleep is dominated by deep, slow-wave sleep. REM sleep increases in duration relative to deep sleep during the second half of the night. Source: Based on Some Must Watch while Some Must Sleep by W.D. Dement. WC Freeman & Company, 1974. URL:
http://socrates.berkeley.edu/~kihlstrm/ConsciousnessWeb/SleepDreams/images/DementSuccession.JPG.
Module 5.1a Quiz:
What Is Sleep?
Know . . . 1. Large, periodic bursts of brain activity that occur during stage 2 sleep are
known as . A. beta waves B. sleep spindles C. delta waves D. alpha waves
Understand . . .
2. Why is REM sleep known as paradoxical sleep? A. The brain waves appear to be those of an awake person but the
individual seems to be in a deep sleep.
B. The brain waves resemble those of a sleeping individual but the person behaves as if he is nearly awake.
C. The brain wave patterns in REM sleep are totally unlike those produced by brain activity at any other time.
D. The brain waves resemble those of a sleeping individual and the person seems to be in a very deep sleep.
Apply . . . 3. Which of the following is the most likely order of sleep stages during the
first 90 minutes of a night of rest?
A. Stages 1–2–3–4–1–2–3–4–REM B. Stages 1–2–3–4–REM–1–2–3–4 C. Stages 1–2–3–4–3–2–1–REM D. Stages REM–4–3–2–1
Why Do We Need Sleep?
Sleep is such a natural part of life that it is difficult to imagine what the world would be like if there were no such thing. It raises another question: Why do humans and other animals need to sleep in the first place?
Theories of Sleep
The most intuitive explanation for why we sleep is probably the restore and repair hypothesis , the idea that the body needs to restore energy levels and repair any wear and tear experienced during the day’s activities. Research on sleep deprivation clearly shows that sleep is a physical and psychological necessity, not just a pleasant way to relax. A lack of sleep eventually leads to cognitive decline, emotional disturbances, and impaired functioning of the
immune system (Born et al., 1997). It appears that sleeping helps animals,
including humans, clear waste products and excess proteins from the brains. In a study using rodents, the researchers found that the pathways of the brain’s waste removal system were enlarged during sleep, making the removal of these waste products more efficient. This effect was largest when the animal was
sleeping on its side (Lee, Xie, et al., 2015). Such findings may explain why for some species, sleep deprivation can be as dangerous as food deprivation
(Rechtschaffen, 1998).
Although there is good evidence supporting the restore and repair hypothesis, it does not account for all the reasons why we sleep. Imagine you have had an unusually active day on Saturday and then spend all day Sunday relaxing. Research shows that you are likely to feel sleepier on Saturday night, but you will need only slightly more sleep after the high-activity day, despite what the restore
and repair hypothesis would suggest (Horne & Minard, 1985). The same is true for days filled with mentally challenging activities (De Bruin et al., 2002). Rather than requiring more sleep, it could be that sleep is more efficient after an
exhausting day (Montgomery et al., 1987); in other words, more restoring and repairing may go on in the same amount of time.
A second explanation for sleep, the preserve and protect hypothesis , suggests that two more adaptive functions of sleep are preserving energy and protecting the organism from harm (Berger & Philips, 1995; Siegel, 2005). To support this hypothesis, researchers note that the animals most vulnerable to predators sleep in safe hideaways during the time of day when their predators
are most likely to hunt (Siegel, 1995). Because humans are quite dependent upon vision, it made sense for us to sleep at night, when we would be at a disadvantage compared to nocturnal predators.
The quantity of sleep required differs between animal species. Hoofed species like antelope (the species you always see getting killed in nature programs) sleep less than four hours per day, primarily because they have to remain alert in case a predator attacks. Conversely, animals such as lions and bears rarely fall victim to predators and can therefore afford a luxurious 15 hours of sleep per day. (The sleepiest animal appears to be the brown bat. It sleeps an average of 19.9 hours out of each 24 hours . . . because really, who would eat a bat?) The
underlying message from this theory is that each species’ sleep patterns have evolved to match their sensory abilities and their environment.
Thus, there are complementary theories that answer the question of why we sleep. The amount that any animal sleeps is a combination of its need for restoration and repair along with its need for preservation and protection. Each theory explains part of our reasons for drifting off each night. Importantly, both theories would produce sleep patterns that would improve a species’ evolutionary fitness. Of course, this discussion of the reasons for sleep leads to an equally important discussion, particularly for students: What happens when we don’t get enough sleep?
Sleep Deprivation and Sleep Displacement
Chances are you have experienced disruptions to your sleep due to jet lag or to an “occasional late night” (i.e., life as a student), and we’ve all had that awful feeling in the spring when we are robbed of a precious hour of slumber by Daylight Savings Time. We don’t usually think of time shifts as being anything more than an annoyance. However, researchers have found that switching to Daylight Savings Time in the spring costs workers an average of 40 minutes of sleep and significantly increases work-related injuries on the Monday following
the time change (Barnes & Wagner, 2009). The same analysis showed that returning to standard time in the fall produces no significant changes in sleep or injuries. Similar results have been noted for traffic accidents. Stanley Coren at the University of British Columbia found that there was a significant increase in the number of accidents immediately following the “spring forward,” but not after
the “fall back” (1996a; see Figure 5.5 ). Coren also looked at accidental deaths unrelated to car accidents (Coren, 1996b). Using U.S. data from 1986– 1988, he found a 6.6% increase in accidental deaths in the four days following the “spring forward” of Daylight Savings Time. Importantly, the effects of disrupted sleep aren’t limited to clumsiness; a substantial amount of research
has shown that it can affect our thinking and decision making as well (Lavie, 2001).
Figure 5.5 Car Accident Statistics for the Years 1991 and 1992 These data represent the number of car accidents on the Monday before, the Monday immediately after, and the Monday one week after the spring and fall time changes. Note the dramatic increase in accidents immediately following the spring time change, when we lose one hour of sleep. Astute observers will also note that, overall, there were still more accidents in the fall than in the spring (the
y-axes are different in the two graphs); this is likely due to the inclement weather found in many parts of Canada in October. Poor weather and earlier darkness are also the most likely explanations for the spike in accidents one week after the fall shift (green bar). These data are from the Canadian Ministry of Transport (and exclude Saskatchewan, which doesn’t observe Daylight Savings Time). Source: From The New England Journal of Medicine by Stanley Coren, Daylight Savings Time and Traffic Accidents, 344
(14), 924. Copyright © 1996 Massachusetts Medical Society. Reprinted with permission from Massachusetts Medical Society.
Sleep deprivation occurs when an individual cannot or does not sleep. In other words, it can be due to some external factor that is out of your control (e.g.,
noisy neighbours) or to some self-inflicted factor (e.g., studying, staying up to watch the late hockey game on TV, etc.). Exactly how sleep deprivation affects daily functioning has been the subject of scientific inquiry since 1896, when researchers examined cognitive abilities in people kept awake for 90 consecutive
hours (Patrick & Gilbert, 1896). In almost all of the studies in the past century, the strength of the circadian rhythms was evident; the volunteers generally went through cycles of extreme sleepiness at night, with normal levels of wakefulness in the daytime (especially the afternoon). However, each night saw an increasing level of sleepiness, likely as an attempt by the body to preserve and protect the health of the individual. In addition to feelings of fatigue, researchers have discovered a number of specific impairments resulting from being deprived of sleep. These include difficulties with multitasking, maintaining attention for long periods of time, assessing risks, incorporating new information into a strategy (i.e., “thinking on the fly”), working memory (i.e., keeping information in conscious awareness), inhibiting responses, and keeping information in the
correct temporal order (Durmer & Dinges, 2005; Lavie, 2001; Wimmer et al., 1992). Importantly, these deficits also appear after partial sleep deprivation, such as when you don’t get enough sleep (Cote et al., 2008). In fact, cognitive deficits typically appear when individuals have less than seven hours of sleep for a few
nights in a row (Dinges, 2006; Dinges et al., 2005).
The problems associated with sleep deprivation aren’t limited to your ability to think. Research with adolescents shows that for every hour of sleep deprivation, predictable increases in physical illness, family problems, substance abuse, and
academic problems occur (Roberts et al., 2009). Issues also arise with your coordination, a problem best seen in studies of driving ability. Using a driving simulator, researchers found that participants who had gone a night without sleeping performed at the same level as people who had a blood-alcohol level of
0.07 (Fairclough & Graham, 1999). A study of professional truck drivers accustomed to long shifts found that going 28 hours without sleep produced driving abilities similar to someone with a blood-alcohol level of 0.1, which is
above the legal limit throughout North America (Williamson & Feyer, 2000). Given that sleep deprivation is as dangerous as driving while mildly intoxicated
(Dawson & Reid, 1997; Maruff et al., 2005), it is not surprising that it is one of the most prevalent causes of fatal traffic accidents (Lyznicki et al., 1998;
Sagberg, 1999).
Sleep deprivation has led to some serious errors in the medical field as well. Medical residents (“residency” is the 2- to 5-year internship performed after completing medical school that precedes becoming a licensed, independent physician) and attending physicians often work through the night at hospitals; in some fields such as Internal Medicine, the doctors often don’t even have time for naps. From what you’ve read in the preceding paragraphs, you can see that this is obviously a recipe for disaster. For instance, researchers at Harvard noted a number of critical errors by medical interns who were tired, including draining the wrong lung, prescribing a medication dose 10 times higher than it should have
been, and causing an accidental overdose of benzodiazepines (Landrigan et al., 2004). Exhausted medical interns were also more likely to crash their cars on the way home (Barger et al., 2005) and suffer from job stress and burnout (Chen, Vorona, et al., 2008). These findings have motivated some researchers to investigate potential benefits of alternative work schedules; by limiting the length of shifts and reducing the number of hours worked per week, the number
of medical errors decreased by 36% (Figure 5.6 ; Landrigan et al., 2004). Recently, Canadian medical residents were granted limits on the length of their shifts and on the number of nights they can be “on call” per month. Perhaps someone was reading psychology research . . . or listening to their lawyers.
Figure 5.6 The Costly Effects of Sleep Deprivation The traditional schedule of a medical intern (Group A) requires up to a 31-hour on-call shift, whereas the modified schedule (Group B) divides the 31 hours into two shorter shifts. The latter schedule reduces the effects of prolonged sleep deprivation as measured in terms of medical errors. Source: From “Effect of Reducing Interns’ Work Hours on Serious Medical Errors in Intensive Care Units” by C. P. Landrigan
et al. (2004), New England Journal of Medicine, 351 (18), 1838–1848. Copyright © 2004. Reprinted by permission of
Massachusetts Medical Society.
Cognitive and coordination errors are not limited to situations involving full or
partial sleep deprivation. They can also occur when the timing of our sleep is altered. This phenomenon, sleep displacement , occurs when an individual is prevented from sleeping at the normal time although she may be able to sleep earlier or later in the day than usual. For example, consider a man from balmy Winnipeg who flies to London (U.K.) for a vacation. The first night in London, he
may try to go to bed at his usual 12 A.M. time. However, his body’s rhythms will be operating six hours earlier—they are still at 6 P.M. Winnipeg time. If he is like most travellers, this individual will experience sleep displacement for three or four days until he can get his internal rhythms to synchronize with the external
day–night cycles. Jet lag is the discomfort a person feels when sleep cycles are out of synchronization with light and darkness (Arendt, 2009). How much jet lag people experience is related to how many time zones they cross and how quickly they do so (e.g., driving versus flying). Also, it is typically easier to adjust when travelling west. When travelling east, a person must try to fall asleep earlier than usual, which is difficult to do. Most people find it easier to stay up longer than usual, which is what westward travel requires.
For someone on a long vacation, jet lag may not be too much of an inconvenience. But imagine an athlete who has to be at her physical best, or a business executive who must remain sharp through an afternoon meeting. For these individuals, it is wise to arrive a week early if possible, or to try to adapt to the new time zone before leaving.
Although jet lag has limited implications for our lives (unless you happen to be a pilot or a flight attendant who crosses oceans several times a month), many people will at some point in their lives have jobs that require shift work. In many hospitals, nurses and support staff rotate across three different 8-hour shifts over
the course of a month (e.g., midnight–8 A.M., 8 A.M.–4 P.M., 4 P.M.–midnight). Switching shifts requires a transition similar to jet lag; your day is suddenly altered by several hours. In order to better adapt to these changes, companies
and hospitals are increasingly scheduling the shift rotations so that workers are able to stay up later (similar to travelling westward in the jet lag example). This reduces the negative effects on a worker’s sleep patterns, which reduces the symptoms of sleep deprivation, thus giving the employer a more alert (and friendlier) employee.
It is important to note that sleep deprivation is not always caused by external factors such as world travel or tough work schedules; in fact, it can be caused by our own behaviours. One possible cause of sleep deprivation is consuming caffeine before bedtime. A 49-day study of five individuals found that consuming caffeine—in this case a double espresso—prior to going to bed delayed their
internal clock by 40 minutes (Burke et al., 2015). This shift was twice as large as that caused by exposure to bright lights. (These participants were obviously dedicated and patient people.) A follow-up examination of the cellular mechanisms of this effect found that caffeine influences the levels of cyclic AMP, a molecule involved in the brain’s internal clock. The good news is that the effects of caffeine on your circadian rhythms—and the cognitive impairments that go with it—are entirely under your control. The next time you spend an evening at Starbucks with your favourite psychology textbook, order a decaf.
Module 5.1b Quiz:
Why Do We Need Sleep?
Know . . . 1. When does sleep displacement occur?
A. When an individual tries to sleep in a new location B. When an individual is allowed to sleep only at night C. When an individual is allowed to sleep, but not at his normal time D. When an individual is not allowed to sleep during a controlled
laboratory experiment
Understand . . . 2. Sleep may help animals stay safe and conserve energy for when it is
needed most. This is known as the .
A. preserve and protect hypothesis B. restore and repair hypothesis C. REM rebound hypothesis D. preserve and repair hypothesis
Apply . . . 3. Jamie reports that it is easier for her to adjust to a new time zone when
flying west than when flying east. This occurs because
A. it is easier to get to sleep earlier than dictated by your circadian rhythms.
B. it is easier to stay up later than your circadian rhythms expect. C. there is more sunlight when you travel west. D. there is less sunlight when you travel west.
Theories of Dreaming
It is very difficult to think about sleeping without thinking about dreaming. Dreams are mysterious and have captured our imaginations for most of human history. A study of 1348 Canadian university students found that some patterns emerge
when we analyze the content of our dreams. Using a statistical technique called factor analysis, researchers found that students’ dreams can be reduced to 16 different factors or subtypes. Females tended to have a larger number of negative dreams related to failures, loss of control, and frightening animals. Males, on the other hand, had more positive dreams including those related to
magical abilities and encounters with alien life (Nielsen et al., 2003). However, studies such as this one, despite being conducted properly, do not provide insight into the purpose(s) dreams serve in our lives.
The Psychoanalytic Approach
One of the earliest and most influential theories of dreams was developed by
Sigmund Freud in 1899. His classic work, The Interpretation of Dreams, dramatically transformed the Western world’s view of both the function and
meaning of dreams. Although many ancient societies performed dream interpretations, most viewed the content of dreams as representing connections to specific gods, as omens (good or bad), or as predictors of the future. In
contrast, Freud viewed dreams as an unconscious expression of wish fulfillment. He believed that humans are motivated by primal urges, with sex and aggression being the most dominant. Because giving in to these urges is impractical most of the time (not to mention potentially immoral and illegal), we learn ways of keeping these urges suppressed and outside of our conscious awareness. When we sleep, however, we lose the power to suppress our urges. Without this active suppression, these drives are free to create the vivid imagery found in our
dreams. This imagery can take two forms. Manifest content involves the images and storylines that we dream about. In many of our dreams, the manifest content involves sexuality and aggression, consistent with the view that dreams are a form of wish fulfillment. However, in other cases, the manifest content of dreams might seem like random, bizarre images and events. Freud would argue that these images are anything but random; instead, he believed they have a
hidden meaning. This latent content is the actual symbolic meaning of a dream built on suppressed sexual or aggressive urges. Because the true meaning of the dream is latent, Freud advocated dream work, the recording and interpreting of dreams. Through such work, Freudian analysis would allow you to bring the previously hidden sexual and aggressive elements of your dreams into the forefront, although it might mean you’d never look at the CN Tower the same way again.
It is difficult to overstate the influence that Freud’s ideas have had on our culture’s beliefs about dreaming. There is an abundance of books offering insights into interpreting dreams including dictionaries that claim to define certain symbols found in a dream’s latent content. However, it is important to note that the scientific support for Freud’s work is quite limited. Although his theories are based on extensive interviews with patients, many of these theories are difficult to test in a scientific manner because they cannot be falsified (i.e., there is no way to prove them wrong). Moreover, dream work requires a subjective interpreter to understand dreams rather than using objective measures. Therefore, the analysis of your dream might have more to do with the mindset of the analyst than it does your own hidden demons. Not surprisingly, modern
dream research focuses much more on the biological activity of dreaming. These studies focus primarily on REM sleep, when dreams are most common and complex.
The Activation–Synthesis Hypothesis
Freud saw deep psychological meaning in the latent content of dreams. In
contrast, the activation–synthesis hypothesis suggests that dreams arise from brain activity originating from bursts of excitatory messages from the pons, a part of the brainstem (Hobson & McCarley, 1977). This electrical activity produces the telltale signs of eye movements and patterns of EEG activity during REM sleep that resemble wakefulness; moreover, the burst of activity stimulates the occipital and temporal lobes of the brain, producing imaginary sights and
sounds, as well as numerous other regions of the cortex (see Figure 5.7 ). Thus, the brainstem initiates the activation component of the model. The synthesis component arises as different areas of the cortex of the brain try to make sense of all the images, sounds, emotions, and memories (Hobson et al., 2000). Imagine having a dozen different people each provide you with one randomly selected word, with your task being to organize these words to look like a single message; this is essentially what your cortex is doing every time you dream. Because we are often able to turn these random messages into a coherent story, researchers assume that the frontal lobes—the region of the brain associated with forming narratives—play a key role in the synthesis
process (Eiser, 2005).
Figure 5.7 The Activation–Synthesis Hypothesis of Dreaming The pons, located in the brainstem, sends excitatory messages through the thalamus to the sensory and emotional areas of the cortex. The images and emotions that arise from this activity are then woven into a story. Inhibitory signals are also relayed from the pons down the spinal cord, which prevents movement during dreaming.
The activation–synthesis model, although important in its own right, has some interesting implications. If the cortex is able to provide (temporary) structure to input from the brainstem and other regions of the brain, then that means the brain is able to work with and restructure information while we dream. If that is the case, then is it possible that the neural activity involved with dreaming also influences our ability to learn new information?
Working the Scientific Literacy Model Dreams, REM Sleep, and Learning
The activation–synthesis model of dreaming suggests that our dreams result from random brainstem activity that is organized— to some degree—by the cortex. Although this theory is widely
accepted, it doesn’t provide many specifics about the purpose of dreams. Why do we have these processes occurring and what functions do they serve? Dream researcher Rosalind Cartwright
(Cartwright et al., 2006; Webb & Cartwright, 1978) proposed the problem-solving theory —the theory that thoughts and concerns are continuous from waking to sleeping, and that dreams may function to facilitate finding solutions to problems encountered while awake. This theory suggests that many of the images and thoughts we have during our dreams are relevant to the problems that we face when we are awake. For instance, researchers have found that individuals who are in poor physical health have more dreams about pain, injuries, illnesses, and
medical themes than do healthy individuals (King & DeCicco, 2007). Another study showed that the number of threatening images in participants’ dreams increased immediately following
the September 11 terrorist attacks (Propper et al., 2007). However, although no one doubts that our daily concerns find their way into our dreams, the problem-solving theory does not explain if (or how) any specific cognitive mechanisms are influenced by dreaming. In contrast, increasing evidence suggests that REM sleep, the sleep stage involved with dreaming, is essential for a number of cognitive functions.
What do we know about dreams, REM sleep, and learning? Approximately 20–25% of our total sleep time is taken up by REM, or rapid eye movement, sleep. When we are deprived of
REM sleep, we typically experience a phenomenon called REM rebound—our brains spend increased time in REM-phase sleep
when given the chance. If you usually sleep 8 hours but get only 3 hours of sleep on a particular night, you can recover from the sleep deficit the next time you sleep with only the normal 8 hours; however, your time in REM sleep will increase considerably. The fact that our bodies actively try to catch up on missed REM sleep suggests that it may serve an important function.
As discussed earlier in this module, REM sleep produces
brainwaves similar to being awake, yet we are asleep (Aserinsky & Kleitman, 1953). This similarity suggests that the types of functions being performed by the brain are likely similar during the two states. Studies with animals have shown that REM sleep is associated with a number of different neurotransmitter systems, all of which influence activity in the brainstem. Projections from the brainstem can then affect a number of different functions, including movement (which is inhibited), emotional regulation (through connections to the amygdala and
frontal lobes), and learning (Brown et al., 2012). Clearly REM is not simply about twitching eyes! The challenge for psychologists is to determine the specific functions that are, and are not, affected by REM.
How can science explain the effects of dreams and REM sleep on learning? In the last 25 years, scientists have performed an extraordinary number of experiments in their attempt to understand how REM sleep (and possibly dreaming) influences our thinking. The results of these studies show that REM sleep affects some, but not all, types of memory. If someone were to give you a list of words to remember and then tested you later, this would be an example of
declarative memory (see Module 7.1 ). The effect of REM sleep disruption on declarative memory was tested in a study conducted by Carlyle Smith at Trent University. Different groups of participants had only their REM sleep disrupted, only their non- REM sleep disrupted, or all of their sleep disrupted. When their
memory for the words was tested, there were no differences between the groups, suggesting that REM sleep is not critical for this simple type of memory. However, when researchers gave participants tests that involved a larger number of steps or procedures, a different pattern of results emerged: Being deprived of REM sleep produced large deficits in performance
(Smith, 2001).
Several studies have shown that the amount of REM sleep people experience increases the night after learning a new task
(Smith et al., 2004). For instance, Mandai and colleagues (1989) found increases in REM sleep in individuals the night following a Morse-code learning task. There was a high correlation between retention levels for the Morse code signals, the number of REM episodes, and the density of the REM activity (i.e., the frequency of eye movements made during REM episodes). In a study
directly related to students’ lives, Smith and Lapp (1991) measured REM sleep 3–5 days after senior undergraduate students had completed their fall semester final exams. These students had more REM sleep episodes and a greater REM sleep density than they had when they were tested in the summer, when less learning was taking place. They also had higher sleep-density values than age-matched participants who were not in university. These results suggest that REM sleep may help us consolidate or maintain newly learned information.
Research has also demonstrated that REM sleep and dreaming also influence our ability to problem solve. Depriving people of REM sleep reduces their ability to perform a complex logic task
(Smith, 1993). This may be due to the fact that our ability to form new associations increases during REM sleep (Stickgold et al., 1999; Walker et al., 2002). Indeed, REM sleep, as opposed to non-REM sleep, helps people think creatively to find associations
between words (Cai et al., 2009). REM sleep appears to be involved with linking together steps in the formation of new
memories and in reorganizing information in novel ways.
Can we critically evaluate this evidence? We have to be cautious when we consider the different effects that REM sleep, and perhaps dreaming, have on memory and problem solving. Although there is a great deal of evidence that REM sleep does influence a number of different abilities, most of this research is correlational. As you’ve undoubtedly heard before, correlation does not equal causation. Therefore, we can’t
guarantee that REM sleep is causing the improvements in memory—just that its disruption is related to poor performance on a number of tasks. It is also unclear whether the observed effects are due to dreaming or to some other REM-related function.
In addition to these questions, it is also worth noting that the effects from these studies are not occurring during every period of REM sleep. When it comes to memory, not all REM sleep is created equal. The final few REM periods in the early morning
appear to be critical for learning (Smith, 2001). Stickgold and colleagues (2000) found that performance on a visual search task (in which participants tried to find a particular target image that was hidden amongst distracter images, similar to “Where’s
Waldo?”) correlated with the amount of non-REM sleep a person had in the early part of the night and the amount of REM sleep in the early morning. Therefore, to say that REM sleep, in general, improves some types of learning is an over-simplification. Further research is needed to understand what makes these early morning windows of REM special. Finally, it is possible that it is dreaming, not REM sleep, that is affecting cognition. However,
although dreaming can sometimes occur during non-REM sleep, these dreams tend to be less vivid and emotional than REM-
based dreams and therefore less likely to affect learning (Suzuki et al., 2004).
Why is this relevant?
Studies of REM sleep and learning show us that the benefits of sleep go beyond restoring and repairing the body. Rather, the effect(s) of REM sleep on our ability to learn new tasks should serve as a wake-up call to all of us. Almost everyone in a university setting is working on a less-than-optimal amount of sleep despite the fact that REM sleep is clearly an important part of our ability to learn. This seems counterproductive. Studying and sleeping every night is a much more effective way to retain information than pulling a frantic all-nighter just before an exam, even if we all feel like we’re out of time.
Interestingly, REM sleep is not the only stage of sleep that affects our ability to learn. There is some evidence that the sleep spindles found in stage 2 sleep are
involved with learning new movements (Fogel et al., 2007; Peters et al., 2008). Smith and MacNeil (1994) found that disrupting stage 2 sleep impaired performance on a pursuit-rotor task in which participants tried to move a computer mouse so that the cursor followed an object on the computer screen. However, when participants were asked to move as though the image was in a mirror (so that an object farther away on the screen was closer to their body), REM, and not stage 2 sleep, became essential. The only difference between the two tasks was the cognitive difficulty associated with figuring out which
movement to perform (Aubrey et al., 1999). This suggests that the brain has different systems for processing simple and complex movements and that these
systems are influenced by different stages of sleep (Smith, 2001).
Module 5.1c Quiz:
Theories of Dreaming
Know . . . 1. The problem-solving theory of dreaming proposes that
A. dreams create more problems than they solve. B. the problems and concerns we face in our waking life also appear
in our dreams.
C. the symbols in our dreams represent unconscious urges related to sex and aggression.
D. we cannot solve complex moral or interpersonal problems until we have dreamed about them.
Understand . . . 2. The synthesis part of the activation–synthesis hypothesis suggests that
A. the brain interprets the meaning of symbolic images. B. the brainstem activates the cortex to produce random images. C. the cortex stimulates the brainstem to produce interpretations of
dreams.
D. the brain tries to link together, or make sense of, randomly activated images.
Analyze . . . 3. Scientists are skeptical about the psychoanalytic theory of dreaming
because the of a dream is entirely subject to interpretation. A. latent content B. sleep stage C. activation D. manifest content
Disorders and Problems with Sleep
Throughout this module, we have seen that sleep is an essential biological and psychological process; without sleep, individuals are vulnerable to cognitive, emotional, and physical symptoms. Given these widespread effects, it should come as no surprise that a lot of research has been directed at improving our ability to diagnose and treat sleep disorders. In the final section of this module, we will discuss some of the more common sleep disorders.
Insomnia
The most widely recognized sleeping problem is insomnia , a disorder characterized by an extreme lack of sleep. According to a 2002 Canadian Community Health Survey from Statistics Canada, one in seven Canadian adults (3.3 million people) suffer from insomnia. This number was lowest in the 18–25 age bracket (10%) and highest in individuals 75 years of age and older (20%)
(Statistics Canada, 2003). Although the average adult may need 7 to 8 hours of sleep to feel rested, substantial individual differences exist. For this reason, insomnia is defined not in terms of the number of hours of sleep, but rather in terms of the degree to which a person feels rested during the day. If a person feels that her sleep disturbance is affecting her schoolwork, her job, or her family and social life, then it is indeed a problem. However, for this condition to be
thought of as a sleep disorder, it would have to be present for three months or more—one or two “bad nights” is unpleasant, but is not technically insomnia.
Although insomnia is often thought of as a single disorder, it may be more
appropriate to refer to insomnias in the plural. Onset insomnia occurs when a person has difficulty falling asleep (30 minutes or more), maintenance insomnia occurs when an individual cannot easily return to sleep after waking in the night,
and terminal insomnia or early morning insomnia is a situation in which a person wakes up too early—sometimes hours too early—and cannot return to sleep
(Pallesen et al., 2001).
Insomnia can arise from worrying about sleep. It is among the most common of all sleep disorders. Steve Prezant/Glow Images
It is important to remember that for a sleep disorder to be labelled insomnia, the problems with sleeping must be due to some internal cause; not sleeping because your roommate snores does not count as insomnia. Sometimes insomnia occurs as part of another problem, such as depression, pain, developmental disorders such as attention deficit hyperactivity disorder (ADHD),
or various drugs (Corkum et al., 2014; Schierenbeck et al., 2008); in these cases, the sleep disorder is referred to as a secondary insomnia. When insomnia is the only symptom that a person is showing, and other causes can be ruled out,
physicians would label the sleep disorder as insomnia disorder. If you think back to our earlier discussion of sleep deprivation, you can see why insomnia— despite not seeming serious—can have a profound effect on a person’s ability to function in our demanding world. However, it isn’t the only disorder that can affect our ability to sleep a full eight hours each night.
Nightmares and Night Terrors
Although most of our dreams are interesting and often bizarre, some of our
dreams really scare us. Nightmares are particularly vivid and disturbing dreams that occur during REM sleep. They can be so emotionally charged that they awaken the individual (Levin & Nielsen, 2007). Almost everyone—as many as 85% to 95% of adults—can remember having bad dreams that have negative emotional content, such as feeling lost, sad, or angry, within a one-year period
(Levin, 1994; Schredl, 2003). Data from numerous studies indicate that nightmares are correlated with psychological distress including anxiety (Nielsen et al., 2000; Zadra & Donderi, 2000), negative emotionality (Berquier & Ashton, 1992; Levin & Fireman, 2002), and emotional reactivity (Kramer et al., 1984). They are more common in females (Nielsen et al., 2006), likely because women tend to have higher levels of depression and emotional disturbances. Indeed, in individuals with emotional disorders, the “synthesis” part of dreaming appears to reorganize information in a way consistent with their mental state, with a focus on negative emotion.
Nightmares, although unpleasant, are a normal part of life. In contrast, 1–6% of
children and 1% of adults experience night terrors —intense bouts of panic and arousal that awaken the individual, typically in a heightened emotional state. A person experiencing a night terror may call out or scream, fight back against imaginary attackers, or leap from the bed and start to flee before waking up. Unlike nightmares, night terrors are not dreams. These episodes occur during NREM sleep, and the majority of people who experience them typically do not recall any specific dream content. Night terrors increase in frequency during
stressful periods, such as when parents are separating or divorcing (Schredl, 2001). There is also some evidence linking them to feelings of anxiety, which suggests that for some sufferers, counselling and other means for reducing
anxiety may help reduce the symptoms (Kales et al., 1980; Szelenberger et al., 2005).
Movement Disturbances
To sleep well, an individual needs to remain still. During REM sleep, the brain prevents movement by sending inhibitory signals down the spinal cord. A number of sleep disturbances, however, involve movement and related
sensations. For example, restless legs syndrome is a persistent feeling of discomfort in the legs and the urge to continuously shift them into different positions (Smith & Tolson, 2008). This disorder affects approximately 5% to 10% of the population (generally older adults), and occurs at varying levels of severity. For those individuals who are in constant motion, sleep becomes very difficult. They awake periodically at night to reposition their legs, although they often have no memory of doing so. The mechanism causing RLS is unclear; however, there is some evidence that it is linked to the dopamine system and to
an iron deficiency (Allen, 2004). Therefore, current treatments are focused on keeping dopamine and iron at normal levels in these patients.
A more common movement disturbance is somnambulism , or sleepwalking, a disorder that involves wandering and performing other activities while asleep. It occurs during NREM sleep, stages 3 and 4, and is more prevalent during childhood. Sleepwalking is not necessarily indicative of any type of sleep or emotional disturbance, although it may put people in harm’s way. People who sleepwalk are not acting out dreams, and they typically do not remember the episode. (For the record, it is not dangerous to wake up a sleepwalker, as is commonly thought. At worst, he or she will be disoriented.) There is no reliable medicine that curbs sleepwalking; instead, it is important to add safety measures to the person’s environment so that the sleepwalker doesn’t get hurt.
A similar, but more adult, disorder is sexomnia or sleep sex. Individuals with this condition engage in sexual activity such as the touching of the self or others,
vocalizations, and sex-themed talk while in stages 3 and 4 sleep (Shapiro et al., 2003). In the original case report of this disorder (Motet, 1897, described in Thoinot, 1913), a man exposed his genitals to a policeman (that’s bad). He was unable to recall the incident afterwards and was sentenced to three months in jail. Other reports are more extreme, including sex with strangers and unwanted
contact with sleeping partners (Béjot et al., 2010). The exact cause of sexomnia is unknown, although stress, fatigue, and a history of trauma have all been
mentioned as possible factors (Schenck et al., 2007).
Another potentially dangerous condition is REM behaviour disorder, which was introduced in the beginning of this module. People with this condition do not show the typical restriction of movement during REM sleep; in fact, they appear
to be acting out the content of their dreams (Schenck & Mahowald, 2002). Imagine what happens when an individual dreams of being attacked—the dreamed response of defending oneself or even fighting back can be acted out. Not surprisingly, this action can awaken some individuals. Because it occurs during REM sleep, however, some individuals do not awaken until they have hurt themselves or someone else, as occurred with Mike Birbiglia (Schenck et al., 1989). Unlike sleepwalking and restless legs syndrome, REM behaviour disorder can be treated with medication; benzodiazepines, which inhibit the central nervous system, have proven effective in reducing some of the symptoms
associated with this condition (Paparrigopoulos, 2005). However, given the potential side effects of this class of drug, this option should only be taken if the person is a threat to himself or others.
Sleep Apnea
The disorders discussed thus far have focused on changes in the brain that lead to altered thinking patterns (nightmares and night terrors) and movements. In
contrast, sleep apnea is a disorder characterized by the temporary inability to breathe during sleep (apnea literally translates to “without breathing”). Although a variety of factors contribute to sleep apnea, this condition appears to be most common among overweight and obese individuals, and it is roughly twice as
prevalent among men as among women (Lin et al., 2008; McDaid et al., 2009). In most cases of apnea, the airway becomes physically obstructed at a point
anywhere from the back of the nose and mouth to the neck (Figure 5.8 ). Therefore, treatment for mild apnea generally involves dental devices that hold the mouth in a specific position during sleep. Weight-loss efforts should accompany this treatment in cases in which it is a contributing factor. In moderate to severe cases, a continuous positive airway pressure (CPAP) device can be used to force air through the nose, keeping the airway open through
increased air pressure (McDaid et al., 2009).
Figure 5.8 Sleep Apnea One cause of sleep apnea is the obstruction of air flow, which can seriously disrupt the sleep cycle. Source: Lilienfeld, Scott O.; Lynn, Steven J; Namy, Laura L.; Woolf, Nancy J., Psychology: From Inquiry to Understanding,
2nd ed., © 2011. Reprinted and electronically reproduced by permission of Pearson Education, Inc., New York, NY.
In rare but more serious cases, sleep apnea can also be caused by the brain’s failure to regulate breathing. This failure can happen for many reasons, including damage to or deterioration of the medulla of the brainstem, which is responsible for controlling the chest muscles during breathing.
You might wonder if disorders that stop breathing during sleep can be fatal. They can be, but rarely are. As breathing slows too much or stops altogether, oxygen levels in the blood rapidly decline, resulting in a gasping reflex and resumed oxygen flow. Actually, gasping may not even result in waking up. A person with sleep apnea may not be aware that he is constantly cycling through oxygen loss and gasping as he sleeps, although it would certainly be noticed by anyone sharing a bed with him. It is often the case that affected individuals discover that they have sleep apnea only after visiting their physician to find a solution for their snoring and fatigue.
Although sleep apnea is serious in its own right, it also leads to a number of
other problems. Repeatedly waking up during the night reduces the quality of an
individual’s sleep and can lead to a mild form of sleep deprivation (Naëgelé et al., 1995). In fact, individuals who suffer from sleep apnea often perform more poorly on tests requiring mental flexibility, the control of attention, and memory
(Fulda & Schulz, 2003). Treating sleep apnea will therefore not only improve a person’s physical safety and fatigue levels, but also the person’s ability to think.
Narcolepsy
While movement disorders, sleep apnea, and night terrors can all lead to insomnia, another condition is characterized by nearly the opposite effect. Narcolepsy is a disorder in which a person experiences extreme daytime sleepiness and even sleep attacks. These bouts of sleep may last only a few seconds, especially if the person is standing or driving when she falls asleep and is jarred awake by falling, a nodding head, or swerving of the car. Even without such disturbances, the sleep may last only a few minutes or more, so it is not the same as falling asleep for a night’s rest.
Narcolepsy differs from more typical sleep in a number of other ways. People with a normal sleep pattern generally reach the REM stage after more than an hour of sleep, but a person experiencing narcolepsy is likely to go almost immediately from waking to REM sleep. Also, because REM sleep is associated with dreaming, people with narcolepsy often report vivid dream-like images even if they did not fully fall asleep.
Why does narcolepsy occur? Scientists have investigated a hormone called
orexin that functions to maintain wakefulness. Individuals with narcolepsy have fewer brain cells that produce orexin, resulting in greater difficulty maintaining
wakefulness (Nakamura et al., 2011). Luckily, medications are available to treat this condition, thus allowing these individuals to function relatively normally
(Mayer, 2012).
Overcoming Sleep Problems
Everyone has difficulty sleeping at some point, and there are many myths and anecdotes about what will help. For some people, relief can be as simple as a snack or a warm glass of milk; it can certainly be difficult to sleep if you are hungry. Others might have a nightcap—a drink of alcohol—in hopes of inducing sleep, although the effects can be misleading. Alcohol may make you sleepy, but it disrupts the quality of sleep, especially the REM cycle, and may leave you feeling unrested the next day.
Many people turn to drugs (e.g., sedatives) to help them sleep. A number of sleep aids are available on an over-the-counter basis, and several varieties of prescription drugs have been developed as well. For most of the 20th century, drugs prescribed for insomnia included sedatives such as barbiturates (Phenobarbital) and benzodiazepines (e.g., Valium). Although these drugs managed to put people to sleep, several problems with their use were quickly observed. Notably, people quickly developed tolerance to these agents, meaning they required increasingly higher doses to get the same effect, and many soon came to depend on the drugs so much that they could not sleep without them
(Pallesen et al., 2001). Even though benzodiazepines are generally safer than barbiturates, the risk of dependence and worsening sleep problems makes them suitable only for short-term use—generally for a week or two. Modern sleep drugs are generally thought to be much safer in the short term, and many have been approved for long-term use as well. However, few modern drugs have been studied in placebo-controlled experiments, and even fewer have actually been
studied for long-term use (e.g., for more than a month; Krystal, 2009).
Fortunately, most people respond very well to psychological interventions. By
practising good sleep hygiene—healthy sleep-related habits—they can typically overcome sleep disturbances in a matter of a few weeks (Morin et al., 2006; Murtagh & Greenwood, 1995). The techniques shown in Table 5.1 are effective for many people who prefer self-help methods, but effective help is also available from psychologists, physicians, and even (sometimes) over the Internet
(Ritterband et al., 2009; van Straten & Cuijpers, 2009). So, rather than taking drugs to alter your brain chemistry, it is generally safer to change your sleep hygiene (sleeping routines) if you want to put your sleeping problems to rest.
Table 5.1 Nonpharmacological Techniques for Improving Sleep
1. Use your bed for sleeping only, not for working or studying. (Sexual activity is an appropriate exception to the rule.)
2. Do not turn sleep into work. Putting effort into falling asleep generally leads to arousal instead of sleep.
3. Keep your clock out of sight. Watching the clock increases pressure to sleep and worries about getting enough sleep.
4. Get exercise early during the day. Exercise may not increase the amount of sleep, but it may help you sleep better. Exercising late in the day, however, may
leave you restless and aroused at bedtime.
5. Avoid substances that disrupt sleep. Such substances include caffeine (in coffee, tea, many soft drinks, and other sources), nicotine, and alcohol. Illicit
drugs such as cocaine, marijuana, and ecstasy also disrupt healthy sleep.
6. If you lie in bed worrying at night, schedule evening time to deal with stress. Write down your worries and stressors for approximately 30 minutes prior to
bedtime.
7. If you continue to lie in bed without sleeping for 30 minutes, get up and do something else until you are about to fall asleep, and then return to bed.
8. Get up at the same time every morning. Although this practice may lead to sleepiness the first day or two, eventually it helps set a daily rhythm.
9. If you still have problems sleeping after four weeks, consider seeing a sleep specialist to get tested for sleep apnea, restless legs syndrome, or other sleep
problems that may require more specific interventions.
Source: Based on recommendations from the American Psychological Association, 2004.
Module 5.1d Quiz:
Disorders and Problems with Sleep
Know . . . 1. When people do not show the typical restriction of movement during
REM sleep, they are experiencing . A. somnambulism B. REM behaviour disorder C. insomnia D. restless legs syndrome
2. is(are) a condition in which a person’s breathing becomes obstructed or stops during sleep.
A. Somnambulism B. Night terrors C. Narcolepsy D. Sleep apnea
Apply . . . 3. Which of the following is not good advice for improving your quality of
sleep?
A. Use your bed for sleeping only—not for doing homework or watching TV.
B. Exercise late in the day to make sure you are tired when it is time to sleep.
C. Avoid drinking caffeine, especially late in the day. D. Get up at the same time every morning to make sure you develop
a reliable pattern of sleep and wakefulness.
Module 5.1 Summary
Know . . . the key terminology associated with sleep, dreams, and sleep disorders.
5.1a
activation–synthesis hypothesis
circadian rhythms
consciousness
endogenous rhythms
entrainment
insomnia
jet lag
latent content
manifest content
narcolepsy
night terrors
nightmares
polysomnography
preserve and protect hypothesis
problem-solving theory
REM sleep
restless legs syndrome
restore and repair hypothesis
sleep apnea
sleep deprivation
sleep displacement
somnambulism
Understand . . . how the sleep cycle works.5.1b
The sleep cycle consists of a series of stages going from stage 1 through stage 4, cycles back down again, and is followed by a REM phase. The first sleep cycle lasts approximately 90 minutes. Deep sleep (stages 3 and 4) is longest during the first half of the sleep cycle, whereas REM phases increase in duration during the second half of the sleep cycle.
Sleep theories include the restore and repair hypothesis and the preserve and protect hypothesis. According to the restore and repair hypothesis, we sleep so that the body can recover from the stress and strain on the body that occurs during waking. Waste products are more efficiently removed from the brain during this time as well. According to the preserve and protect hypothesis, sleep has evolved as a way to reduce activity and provide protection from potential threats, and to reduce the amount of energy intake required. Evidence supports both theories, so it is likely that there is more than one reason for sleep.
Apply Activity Try completing the Epworth Sleepiness Scale to make sure you are getting
enough sleep (Table 5.2 ). If you score 10 points or higher, you are probably not getting enough sleep. You can always refer to Table 5.1 for tips on improving your sleep.
Table 5.2 Epworth Sleepiness Scale Use the following scale to choose the most appropriate number for each situation:
0 = would never doze or sleep 1 = slight chance of dozing or sleeping
2 = moderate chance of dozing or sleeping 3 = high chance of dozing or sleeping
Understand . . . theories of why we sleep.5.1c
Apply . . . your knowledge to identify and practise good sleep habits.
5.1d
Situation Chances of Falling Asleep
Sitting and reading 0 1 2 3
Watching TV 0 1 2 3
Sitting inactive in a public place 0 1 2 3
Being a passenger in a motor vehicle for an hour or more 0 1 2 3
Lying down in the afternoon 0 1 2 3
Sitting and talking to someone 0 1 2 3
Sitting quietly after lunch (no alcohol) 0 1 2 3
Stopped for a few minutes in traffic while driving 0 1 2 3
Your total score
Source: Reprinted with permission from SLEEP. Sleep Research Society, Darien, IL, USA 2016.
Dreams have fascinated psychologists since Freud’s time. From his psychoanalytic perspective, Freud believed that the manifest content of dreams could be used to uncover their symbolic, latent content. Contemporary scientists are skeptical about the validity of this approach given the lack of empirical evidence to support it. The activation– synthesis theory eliminates the meaning of dream content, suggesting instead that dreams are just interpretations of haphazard electrical activity in the sleeping brain that are then organized to some degree by the cortex. Increasing evidence suggests that REM sleep, the sleep stage associated with dreaming, improves our ability to form new procedural (step-by-step) memories and to find solutions to problems.
Analyze . . . different theories about why we dream.5.1e
Module 5.2 Altered States of Consciousness: Hypnosis, Mind-Wandering, and Disorders of Consciousness
Gennadiy Poznyakov/Fotolia
Learning Objectives
“Just a moment! I don’t like the patient’s colour. Much too blue. Her lips are very blue. I’m going to give a little more oxygen. . .. There, that’s
better now. You can carry on with the operation” (Levinson, 1965, p. 544). If you were undergoing surgery with a local anesthetic and heard this, you would certainly be worried . . . if not panicking. But, what if you had been given general anesthetic so that you were “unconscious”? Presumably, you should be blissfully unaware of the fact that you were turning blue. However, when prompted by an experimenter one month later, 8 of the 10 patients who heard these statements—which were a script read during real surgeries as part of an experiment—were able to report back some elements of the fake crisis. Four of the patients were able to give an almost verbatim account of what the experimenter said. In other studies, post-operative patients were able to complete word stems (e.g., H O - - -) with words presented under anesthesia (e.g., HORSE, not
HOUSE) at levels far above chance (Bonebakker et al., 1996; Merikle & Daneman, 1996). How is this possible? Brain-imaging studies have noted that anesthesia affects more than just activity related to pain and touch; instead, it affects how different areas of the brain work together to
form networks (MacDonald et al., 2015). Importantly, anesthesia seems to affect brain networks related to complex thought more than it affects
networks related to auditory and visual perception (Boveroux et al., 2010; Liu et al., 2012). This difference may explain why anesthetized patients might, upon coming out of the anesthetic state, use the presented words to complete word stems even though they have no
Know . . . the key terminology associated with hypnosis, mind-wandering, and disorders of consciousness. Understand . . . the competing theories of hypnosis. Apply . . . your knowledge of hypnosis to identify what it can and cannot do. Analyze . . . the effectiveness of using neuroimaging to study mind- wandering. Analyze . . . the ability of researchers to detect consciousness in brain- damaged patients.
5.2a
5.2b 5.2c
5.2d
5.2e
conscious recollection of their presentation.
It is important to note that these studies don’t tell us what consciousness is. What these studies do illustrate, however, is that consciousness does not have a simple on/off switch. Instead, there are a number of possible states of consciousness, each with its own abilities and limitations.
Focus Questions
1. How is information perceived in different states of consciousness?
2. Is information processed in the background of our awareness?
Philosophers have attempted to understand the mysteries of consciousness for thousands of years. Recently, cognitive neuroscience researchers have used methods ranging from brain imaging to computer modelling to examine how the coordinated activity of groups of brain cells can produce our everyday conscious
experiences (Crick, 1994; Ward et al., 2010). Although these investigations have shown great promise, many psychologists use a different strategy to study consciousness: examining situations in which consciousness is altered or impaired. By examining how our abilities and experiences change during altered states of consciousness, we can gain greater insight into our “normal” conscious behaviour. In this module, we will discuss three of these altered states— hypnosis, mind wandering, and disorders of consciousness caused by brain damage.
Hypnosis
The caricature of a hypnotist as an intense-looking bearded man swinging his glistening pocket watch back and forth before an increasingly subdued subject will probably always be around, though it promotes just one of many
misunderstandings about hypnosis. Hypnosis is actually a procedure of inducing a heightened state of suggestibility. According to this definition, hypnosis is not a trance, as is often portrayed in the popular media (Kirsch & Lynn, 1998). Instead, the hypnotist simply suggests changes, and the subject is more likely (but not certain) to comply as a result of the suggestion.
Although one could conceivably make suggestions about almost anything, hypnotic suggestions generally are most effective when they fall into one of three categories:
Ideomotor suggestions are related to specific actions that could be performed, such as adopting a specific position.
Challenge suggestions indicate actions that are not to be performed, so that the subject appears to lose the ability to perform an action.
Cognitive-perceptual suggestions involve a subject remembering or forgetting specific information, or experiencing altered perceptions such as
reduced pain sensations (Kirsch & Lynn, 1998).
People who have not encountered scientific information about hypnosis are often skeptical that hypnosis can actually occur or are very reluctant to be hypnotized
themselves (Capafons et al., 2008; Molina & Mendoza, 2006). It is important to note that hypnotists cannot make someone do something against their will. For example, the hypnotist could not suggest that an honest person rob a bank and expect the subject to comply. Instead, the hypnotist can increase the likelihood that subjects will perform simple behaviours that they have performed or have thought of before, and would be willing to do (in some contexts) when in a normal conscious state.
Theories of Hypnosis
In the previous section, we discussed the types of behaviours that can and cannot be influenced by hypnosis; in this section, we attempt to uncover how this
process actually works. The word hypnosis comes from the Greek word hypno, meaning “sleep.” In reality, scientific research tells us that hypnosis is nothing like sleep. Instead, hypnosis is based on an interaction between (1) automatic
(unconscious) thoughts and behaviours and (2) a supervisory system (Norman & Shallice, 1986), sometimes referred to as executive processing, which is involved in processes such as the control of attention and problem solving. The roles played by these two pieces of the puzzle differ across theories of hypnosis.
Stage hypnotists often use the human plank demonstration with their subjects. They support an audience volunteer on three chairs. To the audience’s amazement, when the chair supporting the mid-body is removed, the hypnotized subject does not fall (even when weight is added, as shown in the photo).
However, nonhypnotized subjects also do not fall. (Please do not try this at home —there is a trick behind it!) Bookstaver/AP Images
Dissociation theory explains hypnosis as a unique state in which consciousness is divided into two parts: a lower-level system involved with perception and movement and an “executive” system that evaluates and monitors these behaviours (Hilgard, 1986; Woody & Farvolden, 1998). It may sound magical, but this kind of divided state is actually quite common. Take any skill that you have mastered, such as driving a car or playing an instrument. When you began, it took every bit of your conscious awareness to focus on the correct movements—you were a highly focused observer of your actions. In this case, your behaviour required a lot of executive processing. After a few years of practice, you can do it automatically while you observe and pay attention to something else. In this case, you require much less executive processing. Although we call the familiar behaviour automatic, part of you is still paying attention to what you are doing in case you suddenly need to change your behaviour. During hypnosis, there appears to be a separation between these two systems. As a result, actions or thoughts suggested by the hypnotist may bypass the evaluation and monitoring system and go directly to the simpler perception
and movement systems (Landry & Raz, 2015). In other words, suggestible individuals will experience less input from the executive system (Jamieson & Sheehan, 2004; Woody & Bowers, 1994). In support of this view, neuroimaging studies have found reduced activity in the anterior cingulate cortex, a region of
the frontal lobe related to executive functions, in hypnotized subjects (McGeown et al., 2009; Raz et al., 2005).
A second approach, social-cognitive theory , explains hypnosis by emphasizing the degree to which beliefs and expectations contribute to increased suggestibility. This perspective is supported by experiments in which individuals who are not yet hypnotized are told either that they will be able to resist ideomotor suggestions or that they will not be able to resist them. In these studies, people tend to conform to what they have been told to expect—a result
that cannot be easily explained by dissociation theory (Lynn et al., 1984;
Spanos et al., 1985). Similarly, research on hypnosis as a treatment for pain shows that response expectancy—whether the individual believes the treatment will work—plays a large role in the actual pain relief experienced (Milling, 2009).
At this point, there appears to be some evidence in favour of both theories. It is possible that expectations might make some people more likely to enter a hypnotic state, but once they enter it, they act in a way consistent with the dissociation theory. These expectations may be why people are more likely to enter a hypnotic state under the guidance of a hypnotist than with a non- hypnotist. However, the exact relationship (if any) between these two theories remains unclear. This lack of clarity is due to the fact that hypnosis did not receive much scientific attention for most of the 20th century. However, despite the fact that there is not a clear answer as to how hypnosis works, most
scientists agree that for some individuals hypnosis can be a powerful therapeutic tool.
Applications of Hypnosis
Although it is used far less frequently than medications or talk-based therapies, hypnosis has been used to treat a number of different physical and psychological conditions. Hypnosis is often used in conjunction with other psychotherapies
such as cognitive-behavioural therapy (CBT; see Module 16.2 ) rather than as a stand-alone treatment. The resulting cognitive hypnotherapy has been used as an effective treatment for depression (Alladin & Alibhai, 2007), anxiety (Abramowitz et al., 2008; Schoenberger et al., 1997), eating disorders (Barabasz, 2007), hot flashes of cancer survivors (Elkins et al., 2008), and irritable bowel syndrome (Golden, 2007), among many others (M. R. Nash et al., 2009). Hypnosis is far from a cure-all, however. For example, researchers found that hypnotherapy combined with a nicotine patch is more effective as a smoking cessation intervention than the patch alone. Nonetheless, only one-fifth of the individuals receiving this kind of therapy managed to remain smoke-free
for a year (Carmody et al., 2008). Moreover, although some therapists combine hypnotherapy with traditional cognitive behavioural therapy when treating depression, much more research is required before this technique becomes a
standard treatment (Alladin, 2012). The best conclusion regarding hypnosis in therapy is that it shows promise, especially when used in conjunction with other evidence-based psychological or medical treatments.
Under hypnosis, people can withstand higher levels of pain for longer periods of time, including the discomfort associated with dental procedures. Bikeriderlondon/Shutterstock
Myths in Mind Recovering Lost Memories
through Hypnosis Before the limitations of hypnosis were fully understood, professionals working in the fields of psychology and law regularly used this technique for uncovering lost memories. What a powerful tool this would be for a psychologist—if a patient could remember specifics about trauma or
abuse it could greatly help the individual’s recovery. Similarly, law enforcement and legal professionals could benefit by learning the details of a crime recovered through hypnosis—or so many assumed.
However, as you have read, hypnosis puts the subject into a highly
suggestible state. This condition leaves the individual vulnerable to prompts and suggestions by the hypnotist. A cooperative person could certainly comply with suggestions and create a story that, in the end, was entirely false. This has happened time and again. In reality, hypnosis
does not improve memory (Kihlstrom, 1997; Loftus & Davis, 2006). Today, responsible psychologists do not use hypnotherapy to uncover or reconstruct lost memories. Police officers have also largely given up this practice. In 2007, the Supreme Court of Canada ruled that testimony
based on hypnosis sessions alone cannot be submitted as evidence (R. v. Trochym, 2007).
Perhaps the most practical use for hypnosis is in the treatment of pain. If researchers can demonstrate its effectiveness in this application, it may be a preferred method of pain control given painkillers’ potential side effects and risk of addiction. What does the scientific evidence say about the use of hypnosis in treating pain? A review of 18 individual studies found that approximately 75% of all individuals experienced adequate pain relief with this approach beyond that
provided by traditional analgesics or no treatment (Montgomery et al., 2000). What happened to the other 25%? Perhaps the failure of the treatment in this group is attributable to the fact that some people are more readily hypnotized than others. Indeed, brain-imaging studies suggest that the strength of connections to and from the anterior cingulate gyrus differs between
hypnotizable and non-hypnotizable individuals (Cojan et al., 2015); this brain region is involved in both hypnosis and the perception of pain (see Module 4.4 ). In addition, to truly understand pain control, researchers must distinguish among different types of pain. Research has shown that hypnosis generally
works as well as drug treatments for acute pain, which is the intense, temporary pain associated with a medical or dental procedure (Patterson & Jenson, 2003). The effect of hypnosis on chronic pain is more complicated, as some conditions are due to purely physical causes whereas others are more psychological in nature. For these latter conditions, it is likely that the patient will expect to continue to feel pain regardless of the treatment, thus reducing the effectiveness of hypnosis.
Module 5.2a Quiz:
Hypnosis
Know . . . 1. suggestions specify that certain actions cannot be performed
while hypnotized.
A. Ideomotor B. Challenge C. Cognitive-perceptual D. Dissociation
Understand . . . 2. Dr. Johnson claims that hypnosis is a distinct state of consciousness
involving a disconnection between perception and executive processing.
It appears that she is endorsing the theory of hypnosis. A. social-cognitive B. psychoanalytic C. dissociation D. hypnotherapy
Analyze . . . 3. Which of the following statements best describes the scientific consensus
about recovering memories with hypnosis?
A. Memories “recovered” through hypnosis are highly unreliable and should never be used as evidence in court.
B. If the memory is recovered by a trained psychologist, then it may be used as evidence in court.
C. Recovering memories through hypnosis is a simple procedure and, therefore, the findings should be a regular part of court hearings.
D. Memories can be recovered only in individuals who are highly hypnotizable.
Mind-Wandering
During hypnosis, an individual enters an altered state of consciousness in which he or she is more suggestible than at other times. Although the idea of altered states of consciousness might seem strange to you at first, you actually experience them all the time, possibly even while reading this book. One such example is mind-wandering, an obstacle to your (and everyone else’s) ability to work and study.
What is Mind-Wandering?
Imagine sitting in a large lecture hall listening to an enthusiastic professor talk about European history. Despite the fascinating topic filled with battles and revolutions, after a few minutes, you start to think about a conversation you had with a friend the day before. Then you start to think about the witty remarks you wish you had made, and fantasize about unleashing these comments on people in an argument sometime in the future. Then, suddenly, you are back in your classroom, and see an unfamiliar slide on the screen at the front of the room. Your body was physically present in the classroom for the entire lecture, but your
mind was elsewhere. This is an example of mind-wandering , an unintentional redirection of attention from one’s current task to an unrelated train of thought (Mooneyham & Schooler, 2013).
The frequency with which we think about something unrelated to what we are doing is astonishing. This was powerfully demonstrated in an innovative study in which researchers programmed an iPhone “app” that contacted participants at
random points during the day (Killingsworth & Gilbert, 2010). Participants were asked, “Are you thinking about something other than what you’re currently doing?” The results indicated that mind-wandering occurred in 47% of the samples taken. The frequency of mind-wandering was over 30% for every activity other than sex! The challenge for psychologists is to determine whether —or how much—these lapses of attention affect our ability to work and study.
At first glance, studying the effects of mind-wandering might seem impossible—
how you do study the process of not paying attention? However, in the past decade, psychologists have conducted a number of studies examining how
mind-wandering affects attention and memory (e.g., Kam & Handy, 2014). For instance, several studies have shown that mind-wandering decreases reading comprehension. In one such study conducted at the University of Alberta, participants read either an engaging passage (an excerpt from Anne Rice’s
Interview with the Vampire) or a less interesting passage (an excerpt from William M. Thackeray’s The History of Pendennis). While reading the assigned passages, participants were occasionally asked whether they were attending to the text. Not surprisingly, the researchers found that for both types of passages, the recall of the material was better when participants were paying attention to
the text rather than mind-wandering (Dixon & Bortolussi, 2013). However, the errors caused by mind-wandering went beyond missing minor details. Participants in this and other experiments often missed major elements of the plot. One study found that mind-wandering participants couldn’t identify the villain
in a mystery story (Smallwood et al., 2008)! Given these results, it should come as no surprise that mind-wandering is associated with poorer retention of
university lecture material (Risko et al., 2012) and with poorer scores on intelligence tests (Mrazek et al., 2012).
Of course, if we spend at least 30% of our time not consciously attending to our current situation, it does make you wonder where your mind wandered off to. Recent brain-imaging studies suggest an interesting destination.
Mind-Wandering and the Brain
In the late 1990s, Marcus Raichle and his research team made a discovery that would change psychology. While looking at their brain-imaging data, Raichle noticed that a number of brain areas were active. For most scientists, finding brain activity that is consistent with your predictions is a cause for celebration, if not a trip to the campus pub. But Raichle noticed something else in his data. He
noticed that across a number of studies, the same pattern of deactivations also occurred (Raichle et al., 2001). In other words, a network of brain regions became less active when participants performed a task (see Figure 5.9 ). This network, now known as the default mode network , is a network of brain regions including the medial prefrontal cortex, posterior cingulate gyrus, and
medial and lateral regions of the parietal lobe that is most active when an individual is awake but not responding to external stimuli. In other words, the default mode network is more active when a person is paying attention to his
internal thoughts rather than to an outside stimulus or task (Raichle, 2015).
Figure 5.9 The Default Mode Network and Frontoparietal Network The default mode network (left) is involved with self-related thinking. The frontoparietal network is linked with goal-directed thought and planning. Both are involved with mind-wandering. Source: Reproduced with permission of Annual Review of Neuroscience, Volume © by Annual Reviews,
http://www.annualreviews.org.
The default mode network also appears to be related to mind-wandering; this makes sense given that mind-wandering is often associated with becoming lost in one’s own thoughts (Gruberger et al., 2011). In one fMRI study conducted at the University of British Columbia, researchers measured participants’ brain activity while they performed a simple (and boring) perceptual task. At different points in the experiment, participants were asked (1) “Where was your attention focused just before the probe [the question]?” and (2) “How aware were you of where your attention was focused?” Activity in the default mode network was more pronounced when participants were not paying attention to the perceptual task. This effect was largest when they weren’t aware that they were mind-
wandering (Christoff et al., 2009). Importantly, the default mode network wasn’t the only group of brain areas found to be active during mind-wandering. A network involving parts of the frontal and parietal lobes also showed increased
activity when mind-wandering was occurring (Fox et al., 2015). This frontoparietal network is associated with goal-directed thinking such as planning for the future, as well as the control of attention (i.e., “executive functioning”). This pattern of activity is important—the fact that a brain network involved in higher-order thought shows stronger connectivity during mind-wandering suggests that these lapses of attention might actually serve a useful purpose.
The Benefits of Mind-Wandering
Our minds don’t always wander. If you’re being chased by a bear, it’s unlikely that you’ll start daydreaming about your cute classmate. Instead, mind- wandering typically occurs during tasks that are repetitive, don’t require much thought, and/or that we’ve experienced before. If we’re not dedicating many mental resources to a given task, we will have more resources to dedicate to
mind-wandering (Risko et al., 2012).
It is at this point that the increased activity in the frontal and parietal brain areas becomes important. One function of the frontal lobes is planning future goals and
actions. As it turns out, mind-wandering is related to future thinking (Smallwood et al., 2011). In one study, participants completed a simple reaction-time task; at various points in the experiment, they were interrupted and asked what they were thinking about. The experimenters then judged whether the participants’ thoughts were focused on the past, the present, or the future. When participants were thinking about the experimental task, their thoughts were (not surprisingly)
rated as being focused on the present most of the time (see Figure 5.10 ). In contrast, when people were mind-wandering, there was a strong tendency to be thinking about the future. This future focus may allow us to think about possible plans of action before we are actually in that situation, an ability that could be
quite useful (Baird et al., 2011).
Figure 5.10 Mind-Wandering about the Future When participants are paying attention to the task (“On”), their thoughts were judged to be focused on the present situation. When they were mind-wandering (“Off,” for “off-task”), they were more likely to be thinking about the future. Source: Republished with permission of Elsevier Science, Inc., from Back to the future: Autobiographical planning and the
functionality of mind-wandering. Consciousness and Cognition 20, 1604-1611, 2011., Benjamin Baird; Jonathan Smallwood;
Jonathan W. Schooler. Permission conveyed through Copyright Clearance Center, Inc.
It is important to note that although some studies have shown benefits to mind- wandering, this area of research is still in its initial stages. Most researchers would agree that your performance on most tasks would be improved if they received your full conscious attention. Unfortunately, as you will read in the next section, this is not always possible.
Module 5.2b Quiz:
Mind-Wandering
Know . . . 1. What functions may benefit from mind-wandering?
A. Thinking about things you plan to do in the near future B. Reading comprehension C. Thinking about abstract problems D. Paying attention to other cars while you are driving
Analyze . . . 2. The default mode network is often active when people are mind-
wandering. What can you infer from the activity of this particular network? A. The individual is trying to solve problems that they may encounter
in the future.
B. The individual is thinking about problems that a friend is having. C. The individual is likely thinking about ideas or future plans related
to him- or herself.
D. The individual is paying attention to interesting external stimuli such as sounds or smells.
Disorders of Consciousness
In 1990, a Florida woman named Terri Schiavo collapsed to the ground. She had suffered a full cardiac arrest, resulting in massive brain damage due to a lack of oxygen. She would never regain consciousness. After she had been in a coma for almost three months, her diagnosis was changed to a persistent vegetative state. In 1998, her husband asked the hospital to remove her feeding tube because he was sure she wouldn’t want to live this way. Her parents fought the decision, claiming part of Terri was still conscious. The ethical and legal battles continued for seven years, and included President George W. Bush cutting his vacation short in order to return to Washington to sign a legal order keeping her
alive (Cranford, 2005). Eventually, after the U.S. Supreme Court refused to hear an appeal, her feeding tube was removed for the last time. Terri Schiavo died on March 31, 2005.
The Terri Schiavo case highlights the importance of consciousness in medical decision making. Consciousness can take many forms, all of which vary in terms
of how aware a person is of his or her environment. In patients with brain damage, the degree to which a patient is conscious of her surroundings can
influence the diagnosis that she receives (G. Lee et al., 2015). Neurologists distinguish between six types of consciousness, ranging from little-to-no brain
function up to normal levels of awareness (see Figure 5.11 ).
Figure 5.11 Disorders of Consciousness Although more nuanced diagnoses exist, this diagram depicts six key levels of consciousness used in the diagnosis of brain-damaged individuals. Source: Gawryluk, J. R., D’Arcy, R. C. N., Connolly, J. F., & Weaver, D. F. (2010). Improving the clinical assessment of
consciousness with advances in electrophysiological and neuroimaging techniques. BMC Neurology, 10, 11. Figure 1, p. 3.
The lowest level of consciousness in a person who is still technically alive is
known as brain death , a condition in which the brain, specifically including the brainstem, no longer functions (American Academy of Neurology, 1995). Individuals who are brain dead have no hope of recovery because the brainstem regions responsible for basic life functions like breathing and maintaining the
heartbeat do not function (see Figure 5.12 ).
Figure 5.12 Neuroimaging of Brain Death This positron emission tomography (PET) scan shows the amount of glucose being used by the brain. In a healthy brain, most of the image would be yellow, green, or red, indicating activity. Here, only the tissue surrounding the brain is using glucose, giving the image the appearance of being an empty skull; functionally speaking, it is one. Source: Laureys, S., Owen, A. M., & Schiff, N. D. (2004). Brain function in brain death, coma, vegetative state, and related
disorders. Lancet Neurology, 3, 537–546. Figure 3, p. 539.
In contrast to brain death, a coma is a state marked by a complete loss of consciousness. It is generally due to damage to the brainstem or to widespread damage to both hemispheres of the brain (Bateman, 2001). Patients who are in a coma have an absence of both wakefulness and awareness of themselves or
their surroundings (Gawryluk et al., 2010). Some of the patient’s brainstem reflexes will be suppressed, including pupil dilation and constriction in response to changes in brightness. Typically, patients who survive this stage begin to recover to higher levels of consciousness within 2–4 weeks, although there is no guarantee that the patient will make a full recovery.
If a patient in a coma improves slightly, the individual may enter a persistent vegetative state , a state of minimal to no consciousness in which the patient’s eyes may be open, and the individual will develop sleep–wake cycles without clear signs of consciousness. For example, vegetative state patients do not appear to focus on objects in their visual field, nor do they track movement. These patients generally do not have damage to the brainstem. Instead, they
have extensive brain damage to the grey matter and white matter of both
hemispheres, leading to impairments of most functions (Laureys et al., 2004; Owen & Coleman, 2008). The likelihood of recovery from a vegetative state is time dependent. If a patient emerges from this state within the first few months, he or she could regain some form of consciousness. In contrast, if symptoms do
not improve after three months, the patient is classified as being in a permanent vegetative state; the chances of recovery from that diagnosis decrease sharply (Wijdicks, 2006).
Thus far, we have discussed disorders of consciousness as though there were a quick-and-easy tool for diagnoses. While this is definitely true for brain death, distinguishing between other conditions is much more difficult. In fact,
misdiagnosis of these disorders is estimated to be as high as 43% (Gawryluk et al., 2010; Schnakers et al., 2009). The challenge, therefore, is to develop or adapt tools that will help neurologists more accurately diagnose these mysterious conditions.
Working the Scientific Literacy Model Assessing Consciousness in the Vegetative State
Determining a brain-damaged patient’s level of consciousness is quite challenging. It also has important implications for the patient’s treatment. If she is shown to have some degree of awareness of her situation and/or her environment, then it seems reasonable to get her opinion on matters affecting her treatment. In contrast, if she is unresponsive, then such decisions should be made entirely by the family and the medical team. Everyone wants what is best for the patient, but the tools used to assess consciousness are still a work in progress.
What do we know about the assessment of consciousness in vegetative patients?
The initial assessment of consciousness in severely brain- damaged patients is generally performed at the patient’s bedside. Doctors will perform tests of a patient’s reflexes (e.g., pupil responses, which involve the brainstem) and examine other simple responses. The most common assessment tool is the Glasgow Coma Scale (GCS), a 15-item checklist for the physician. The GCS measures eye movements—whether they can open at all, open in response to pain, open in response to speech, or open spontaneously without any reason. The next five items on this checklist assess language abilities (e.g., does she use incorrect words?). The final six items measure movement abilities such as whether the patient responds to pain and whether she can obey commands. Scores of 9 or below reflect a severe disturbance of consciousness. (For comparison, individuals suffering from a concussion tend to score between 13 and 15, which is labelled as a mild disturbance.)
Checklists such as the GCS provide a useful initial indicator of a brain-damaged patient’s abilities. However, many of the behaviours measured by this and similar assessment tools focus more on overt behaviours (i.e., movements) than on direct indications of awareness. A patient’s inability to move may imply a greater disturbance of consciousness than actually exists, thus leading to potential misdiagnoses. Improvements in brain-imaging techniques may prove to be a more sensitive tool for investigating consciousness.
How can science explain consciousness in vegetative patients? Researchers have argued for some time that some patients in a persistent vegetative state can show some signs of consciousness. For example, some patients have shown rudimentary responses to language. There have been cases of
neurological changes in response to one’s name (Staffen et al.,
2006), as well as the emotional tone of a speaker’s voice (Kotchoubey et al., 2009). However, the most stunning example of consciousness in this patient group was shown by Adrian
Owen (now at Western University) and his colleagues (Owen et al., 2006). In their study, a 23-year-old patient in a vegetative state was asked to perform two different mental imagery tasks during an fMRI scan. In one task, she was asked to imagine playing tennis, an activity involving a specific set of movements. In the other task, she was asked to imagine visiting all of the rooms in her house, starting at the front door (this required her to develop a spatial map of her house). Despite not being able to respond to any questions verbally, this patient’s brain showed clear evidence of understanding the commands. Imagining playing tennis activated brain areas related to movement; imagining walking through her house activated a spatial network including the parahippocampal gyrus and the parietal lobe. This result provided stunning evidence that the patient did, in fact, have some degree of consciousness.
Owen and his colleagues have performed several subsequent
studies with larger groups of patients (Owen, 2013). However, not all patients are able to modify their own brain activity. In a study including 54 patients, only five were able to perform the
tennis–house task (Monti et al., 2010). But, one of these patients was able to do something remarkable: He was able to learn to use the tennis–house imagery task to communicate! The experimenters asked him simple questions and told him to imagine playing tennis if he wanted to respond “yes” and to imagine walking through his house if he wanted to respond “no”
(see Figure 5.13 ). Using this technique, he was able to demonstrate that some of his cognitive abilities were preserved. Of course, we must be cautious and remember that this is only one patient among dozens who were tested. The ongoing challenge for researchers is to determine what made the five “fMRI responders” different from the 49 non-responders, and to
use that information to help identify other patients who might still retain some degree of consciousness.
Figure 5.13 Using fMRI to Communicate with a Vegetative Patient
Results of two sample communication scans obtained from Patient 23 (Panels A and C) and a healthy control subject (Panels B and D) during functional MRI are shown. In Panels A and B, the observed activity pattern (orange) was very similar to that observed in the motor-imagery localizer scan (i.e., activity in the supplementary motor area alone), indicating a “yes” response. In Panels C and D, the observed activity pattern (blue) was very similar to that observed in the spatial-imagery localizer scan (i.e., activity in both the parahippocampal gyrus and the supplementary motor area), indicating a “no” response. The names used in the questions have been changed to protect the privacy of the patient.
Source: Monti, M.M, et al. (2010). Willful modulation of brain activity in disorders of consciousness.
New England Journal of Medicine, 362(7), 587. Figure 3 (communication scans).
Can we critically evaluate this evidence? The initial neuroimaging studies of consciousness in vegetative state patients are indeed promising. However, there are some important issues that need to be dealt with. First, we mentioned above that up to 43% of patients with disorders of consciousness are misdiagnosed. Given that a small subset of the vegetative state patients were able to modify their brain activity, it is possible that they were not actually in a vegetative state, but instead had a less severe condition. Second, the researchers are equating language abilities with consciousness; yet, consciousness could take the form of responses to other, non-linguistic stimuli
(Overgaard & Overgaard, 2011). This criticism would be particularly important if a vegetative state patient had damage to brain areas related to language comprehension.
We also have to be cautious about the use of PET and fMRI scans in patients with widespread brain damage. Both types of neuroimaging measure characteristics of blood flow in the brain.
But, damage to the brain will alter how the blood flows (Rossini et al., 2004); therefore, we need to be careful when comparing patients with healthy controls. One way around this latter concern
is to use multiple methods of neuroimaging (Gawryluk et al., 2010). Increasing numbers of research groups are using EEG, which measures neural activity using electrodes attached to the
scalp, to search for brain function in vegetative patients (Cruse et al., 2011; Wijnen et al., 2007). Given that distinct brain waves have been identified for sensory detection of a stimulus, the detection of unexpected auditory stimuli, higher-level analysis of stimuli, and semantic (meaning) analysis of language, this technology could provide important insights into the inner worlds of vegetative state patients. Indeed, Canadian researchers have developed the EEG-based Halifax Consciousness Scanner for
this specific purpose (http://mindfulscientific .ca/hcs/).
Why is this relevant? Neuroimaging investigations of consciousness in vegetative state patients could literally have life-and-death implications. Currently, doctors have a very difficult time determining a patient’s level of consciousness if they cannot move or make some sort of response. However, this information influences the decision about whether to remove that patient from life support. If brain imaging could provide insight into the inner world of patients (or, in some cases, lack thereof), it would provide doctors and family members with valuable information that would help them make the right decision for the patient.
There are two other disorders of consciousness that are often diagnosed by
neurologists. One is the minimally conscious state (MCS) , a disordered state of consciousness marked by the ability to show some behaviours that suggest at least partial consciousness, even if on an inconsistent basis. A minimally conscious patient must show some awareness of himself or his environment, and be able to reproduce this behaviour. Examples of some behaviours that are tested are following simple commands, making gestures or yes/no responses to questions, and producing movements or emotional reactions in response to some person or object in their environment. When neuroimaging is used, minimally conscious patients show more activity than
vegetative patients (see Figure 5.14 ), including activity in some higher-order sensory and cognitive regions (Boly et al., 2004).
Figure 5.14 Brain Activity in Four Levels of Consciousness PET images of brain activity found in a healthy conscious brain and the brains of three patients with different types of brain damage. The highlighted red area near the back of the brain (along the midline) is the precuneus and the posterior cingulate cortex; these areas are involved in a number of different functions and use the most energy in the brain. Source: Laureys, S., Owen, A. M., & Schiff, N. D. (2004). Brain function in brain death, coma, vegetative state, and related
disorders. Lancet Neurology, 3, 537–546. Figure 7, p. 543.
The disorder of consciousness that most resembles the healthy, awake state—at
least in terms of awareness—is locked-in syndrome , a disorder in which the patient is aware and awake but, because of an inability to move his or her body, appears unconscious (Smith & Delargy, 2005). Locked-in syndrome was brought to the attention of most people by the movie The Diving Bell and the Butterfly, which depicted Jean-Dominique Bauby’s attempts to communicate to the outside world using eye movements. This disorder is caused by damage to part of the pons, the region of the brainstem that sticks out like an Adam’s apple. Most patients with locked-in syndrome remain paralyzed. Luckily, new
technology is making it easier for these patients to communicate with the outside world.
The final stage of consciousness is the healthy, conscious brain. That’s you. Be grateful.
Module 5.2c Quiz: Disorders of Consciousness
Know . . .
1. is a disorder of consciousness in which an individual may open the eyes and exhibit sleep–wake cycles but show no specific signs of consciousness.
A. A coma B. A persistent vegetative state C. Brain death D. A minimally conscious state
Understand . . .
2. What is the difference between a persistent vegetative state (PVS) and a minimally conscious state (MCS)?
A. Nothing—they are both names for the same state. B. Someone in an MCS can have conversations, unlike someone in
a PVS.
C. Someone in an MCS has sleep–wake cycles, unlike someone in a PVS.
D. People in an MCS show at least some behaviours that indicate consciousness, even if on an irregular basis.
Module 5.2 Summary
brain death
coma
default mode network
dissociation theory
hypnosis
locked-in syndrome
mind-wandering
minimally conscious state (MCS)
persistent vegetative state
social-cognitive theory
Dissociation theory states that hypnosis involves a division between a lower-level system involved with perception and movement and an “executive” system that evaluates and monitors these behaviours. In contrast, the social- cognitive theory states that a person’s beliefs and expectations about hypnosis heighten his or her willingness to follow suggestions.
Apply Activity
Hypnosis could potentially work in the following scenarios (answer true or false):
1. Temporarily increasing physical strength
Know . . . the key terminology associated with hypnosis, mind- wandering, and disorders of consciousness.
5.2a
Understand . . . the competing theories of hypnosis.5.2b
Apply . . . your knowledge of hypnosis to identify what it can and cannot do.
5.2c
2. Helping someone quit smoking 3. Remembering all of the precise details of a crime scene 4. Recovering a traumatic memory 5. Helping someone relax 6. Reducing pain sensation
Neuroimaging studies have repeatedly shown that two brain networks—the default mode network and the frontoparietal network—are more active when someone is mind-wandering. However, it is important to remember that brain-
imaging studies are correlational in nature. The activity in these networks co- occurs with mind-wandering, but we cannot say for certain if this activity causes mind-wandering.
Consciousness is difficult to detect using traditional bedside testing because many of these testing tools require movement. Using neuroimaging (specifically fMRI), it has been possible to detect conscious awareness in some patients who are in a vegetative state, as well as in patients who are in a minimally conscious state and those with locked-in syndrome. Although these studies do have some limitations (discussed earlier in this module), the results show that it is an exciting time for neuroscience research in Canada!
Analyze . . . the effectiveness of using neuroimaging to study mind- wandering.
5.2d
Analyze . . . the ability of researchers to detect consciousness in brain-damaged patients.
5.2e
Module 5.3 Drugs and Conscious Experience
Nathan Griffith/Alamy Stock Photo
Learning Objectives
Know . . . the key terminology related to different categories of drugs and their effects on the nervous system and behaviour. Understand . . . drug tolerance and dependence. Apply . . . your knowledge to better understand your own beliefs about drug use.
5.3a
5.3b 5.3c
Could taking a drug-induced trip be a way to cope with traumatic stress or a life-threatening illness? A variety of medications for reducing anxiety or alleviating depression are readily available. However, a few doctors and psychologists have suggested that perhaps a 6-hour trip on psychedelic “magic” mushrooms (called psilocybin) could be helpful to people dealing with difficult psychological and life problems. (It would also help them communicate with the sparkling trilingual dragon sighing in the bathtub.)
In the 1960s, a fringe group of psychologists insisted that psychedelic drugs were the answer to all the world’s problems. The outcast nature of this group and the ongoing “war on drugs” prompted mainstream psychologists to shelve any ideas that a psychedelic drug or something similar could be used in a therapeutic setting. However, this perception appears to be changing. Recently, Roland Griffiths from Johns Hopkins University in Maryland has been conducting studies on the possible therapeutic benefits of psilocybin mushrooms. Cancer patients who were experiencing depression volunteered to take psilocybin as a part of Dr. Griffiths’s study. Both at the end of their experience and 14 months later, they reported having personally meaningful, spiritually significant
experiences that improved their overall outlook on life (Griffiths et al., 2008). Subsequent studies have shown that psilocybin mushrooms can help reduce the symptoms of tobacco addiction (Johnson et al., 2014) and may even increase openness of one’s personality (MacLean et al., 2011). Although these findings are not likely to convince your doctor to give you a bag of magic mushrooms, they do illustrate an important point: most drugs can be used to alter brain chemistry for both medical and recreational purposes. The line between “medicine” and “drug” is a blurry one indeed.
Focus Questions
Analyze . . . the difference between spiritual and recreational drug use. Analyze . . . the short- and long-term effects of drug use.
5.3d 5.3e
1. How do we distinguish between recreationally abused drugs and therapeutic usage?
2. What other motives underlie drug use?
Every human culture uses drugs. It could even be argued that every human uses drugs, depending on your definition of the term. Many of the foods that we eat contain the same types of compounds found in mind-altering drugs. For example, nutmeg contains compounds similar to those found in some psychedelic substances, and chocolate contains small amounts of the same
compounds found in amphetamines and marijuana (Wenk, 2010). Of course, caffeine and alcohol—both of which are mainstream parts of our culture—are also drugs. The difference between a drug and a nondrug compound seems to be that drugs are taken because the user has an intended effect in mind. Regardless of why we use them, drugs influence the activity of some elements of our central nervous system, affecting us both physically and psychologically. In this module, we will discuss these physical and psychological effects of drug use. We will then examine how these processes are affected by different classes of drugs.
Physical and Psychological Effects of Drugs
Although we often think of drugs as having a simple effect such as relieving pain or “getting someone high,” the reality is actually much more complicated. To truly understand the impact of a drug on how people act and feel, we have to look at both the short-term and the long-term effects of drugs.
Short-Term Effects
Your brain contains a number of different chemical messengers called
neurotransmitters (see Module 3.2 ). These brain chemicals are released by a
neuron (the pre-synaptic neuron) into the synapse, the space between the cells. They then bind to receptors on the surface of other neurons (the post-synaptic neurons), thus making these neurons more or less likely to fire. Drugs influence the amount of activity occurring in the synapse. Thus, they can serve as an
agonist (which enhances or mimics the activity of a neurotransmitter) or an antagonist (which blocks or inhibits the activity of a neurotransmitter).
The short-term effects of drugs can be caused by a number of different brain mechanisms including (1) altering the amount of the neurotransmitter being released into the synapse, (2) preventing the reuptake (i.e., reabsorption back into the cell that released it) of the neurotransmitter once it has been released, thereby allowing it to have a longer influence on other neurons, (3) blocking the receptor that the neurotransmitter would normally bind to, or (4) binding to the receptor in place of the neurotransmitter. In all of these scenarios, the likelihood of the postsynaptic neurons firing is changed, resulting in changes to how we think, act, and feel.
Different drugs will influence different neurotransmitter systems. For instance, the “club drug” ecstasy primarily affects serotonin levels, whereas painkillers like OxyContin™ affect opioid receptors. However, the brain chemical that is most often influenced by drugs is dopamine, a neurotransmitter that is involved in
responses to rewarding, pleasurable feelings (Volkow et al., 2009). Dopamine release in two brain areas, the nucleus accumbens and the ventral tegmental area, is likely related to the “high” associated with many drugs (Koob, 1992; see Figure 5.15 ). These positive feelings serve an important, and potentially dangerous, function: They reinforce the drug-taking behaviour. In fact, the dopamine release in response to many drugs makes them more rewarding than
sex or delicious food (Bassareo & Di Chiara, 1999; Di Chiara & Imperato, 1988; Fiorino et al., 1997). This reinforcing effect is so powerful that, for someone who has experience with a particular drug, even the anticipation of taking the drug is pleasurable and involves the release of dopamine (Schultz, 2000).
Figure 5.15 Brain Regions Associated with the Effects of Drugs The nucleus accumbens and ventral tegmental area are associated with reward responses to many different drugs.
But, the drug–neurotransmitter relationship is not as simple as it would seem. This is because the effects of drugs involve biological, psychological, and social mechanisms. Think about the effects of alcohol. Drinking half a bottle of wine at a party often leads people to be more outgoing, whereas drinking half a bottle at home might cause them to fall asleep on the couch. In each case, the drug was the same: alcohol. But the effects of the drug differed because the situations in which the drug was consumed changed. The setting in which drugs are consumed can also have a more sinister effect: Overdoses of some drugs are more common when they are taken in new environments than when they are
taken in a setting that the person often uses for drug consumption (Siegel et al., 1982). When people enter an environment that is associated with drug use, their bodies prepare to metabolize drugs even before they are consumed (i.e., their bodies become braced for the drug’s effects). Similar preparations do not occur in new environments, which leads to larger, and potentially fatal, drug effects
(see Module 6.1 ). Another psychological factor that influences drug effects is the person’s experience with a drug. It takes time for people to learn to associate taking the drug with the drug’s effects on the body and brain. Therefore, a drug
might have a much more potent effect on a person the third or fourth time he took it than it did the first time, which is very common with some drugs, such as marijuana. Finally, a person’s expectations about the drug can dramatically influence its effects. If a person believes that alcohol will make him less shy, then it is likely that a few glasses of wine will have that effect.
How can we reconcile these psychological effects with the physiological effects discussed above? To do so, we have to remember that the psychological states mentioned above also influence the activity of brain areas. For instance, dealing with novel or stressful situations (e.g., being surrounded by strangers, or your parents arriving home early) often requires input from the frontal lobes; this activity might reduce the impact that drugs are having on a person’s behaviour. A similar result can occur when a person has expectations about a drug. This mental set can itself change the activity of different brain areas and can alter the effects of a drug. Thus, the effects of drugs are yet another example of how our biology and psychology interact to create our conscious experiences.
Long-Term Effects
Importantly, the effects that different drugs will have on us change as we become frequent users. Think about a drug that most of you use: caffeine (found in coffee, tea, and some soft drinks). The first time you had a cup of coffee, you were likely wired and unable to sleep. But, veteran coffee drinkers rarely experience such a large burst of energy; some can even drink coffee before
going to bed. This is an example of tolerance , when repeated use of a drug results in a need for a higher dose to get the intended effect. While tolerance might seem annoying, it is actually the brain’s attempt to keep the level of neurotransmitters at stable levels. When receptors are overstimulated by neurotransmitters, as often happens during drug use, the neurons fire at a higher rate than normal. In order to counteract this effect and return the firing rate to normal, some of the receptors move further away from the synapse so that they
are more difficult to stimulate, a process known as down-regulation.
Tolerance is not the only effect that can result from long-term use of legal or physical dependence
illegal drugs. Another is , the need to take a drug to ward off unpleasant physical withdrawal symptoms. The characteristics of dependence and withdrawal symptoms differ from drug to drug. Caffeine withdrawal can involve head and muscle aches and impaired concentration. Withdrawal from long-term alcohol abuse is much more serious. A person who is dependent on alcohol can experience extremely severe, even life-threatening, withdrawal symptoms including nausea, increased heart rate and blood pressure, and hallucinations and delirium. However, drug dependence is not
limited to physical symptoms. Psychological dependence occurs when emotional need for a drug develops without any underlying physical dependence. Many people use drugs in order to ward off negative emotions. When they no longer have this defence mechanism, they experience the negative emotions they have been avoiding, such as stress, depression, shame, or anxiety. Therefore, treatment programs for addiction often include some form of therapy that will allow users to learn to cope with these emotional symptoms while they are attempting to deal with the physical symptoms of withdrawal.
There is no single cause of drug dependence; instead, consistent with the biopsychosocial model, researchers believe that numerous factors influence whether someone will become dependent upon a drug as well as the severity of that dependence. At the biological level, researchers are attempting to identify the specific genes—or groups of genes—that make someone prone to becoming
addicted to different drugs (Foroud et al., 2010). For example, the A1 allele of the DRD2 gene, which influences the activity of dopamine receptors, is related to reward processing and to being open to new experiences (Peciña et al., 2013); it is also more common in people who are addicted to opioid drugs such as
heroin (Clarke et al., 2012). In contrast, researchers at the University of Toronto found that a protective version of the CYP2A6 gene is more common in people who do not smoke; this version of the gene is related to feelings of nausea and dizziness occurring when the person is exposed to smoking (Pianezza et al., 1998). Although we cannot go through a complete list of the genes involved with responses to different drugs, these examples show that scientists are rapidly identifying specific genes related to drug-taking behaviour.
However, genes are obviously not the only cause of drug dependence;
researchers are also examining cognitive factors affecting drug-taking behaviour. For example, dependence is influenced by the fact that drugs are often taken in the same situations, such as a cup of coffee to start your day or alcohol whenever you see particular friends. Eventually, taking the drug becomes linked in your memory to that setting or that group of people. When you next see those people or enter that environment, thoughts of the drug will often resurface, making it more likely that you will use, or at least crave, that drug.
Addiction rates are also affected by social factors, such as the culture in which a person lives. For instance, alcoholism rates are lower in religious and social groups that prohibit drinking even though these groups are genetically similar to
the rest of the population (Chentsova-Dutton & Tsai, 2007; Haber & Jacob, 2007). Family attitudes toward drugs is a factor as well, as early experiences with different drugs can shape our attitudes toward them and influence how we
consume those drugs later in life (Zucker et al., 2008). If a young person first tries wine in a family setting, it will feel much less like a “cool” part of teenage rebellion than if that person first tried the same drink at a high school house party. That initial introduction can alter how that person views alcohol for years to come.
Drug dependence is also influenced by the social support available. The importance of this factor was powerfully demonstrated in a classic (if imperfect) study by Bruce Alexander and his colleagues at Simon Fraser University in 1978. Research in the 1960s and 1970s had shown that rats housed in small cages would eagerly press a lever in order to receive drugs such as morphine; these studies made it appear as though the chemistry of the drugs made them irresistible. However, another possibility existed: perhaps the drug-seeking behaviour was due to the fact that the rats felt isolated, a feeling that mirrors how many drug addicts report feeling. To test this, the researchers gave caged rats access to morphine in a way similar to previous studies. After several weeks of drug consumption, the rats were randomly assigned to different conditions: a caged group that remained isolated or a social group that was able to interact with other rats in what became known as Rat Park. When rats from both conditions were later given the opportunity to press a lever to receive morphine, the isolated rats were much more likely to do so than the social rats. This effect
was particularly apparent in females (see Figure 5.16 ). These findings suggest that a key factor in drug dependence is a feeling of isolation.
Figure 5.16 Rat Park: The Effects of Isolation and Gender on Morphine Self- Administration In the Rat Park study, all rats self-administered morphine for several weeks. They were then randomly divided into two conditions. Rats that were able to socialize with other rats showed much less drug-seeking behaviour than rats that were housed in isolation. This effect was largest in females. Source: Republished with permission of Springer Science, from The effect of housing and gender on morphine self-
administration in rats. Bruce K. Alexander; Robert B. Coambs; Patricia F. Hadaway, 58, 1978. Permission conveyed through
Copyright Clearance Center, Inc.
Finally, all of these variables interact with a person’s personality; individuals with impulsive personality traits are more likely to become addicted to drugs
regardless of their early experiences or cultural setting (Lejuez et al., 2010; Perry & Carroll, 2008). Thus, drug dependence does not have a single, simple cause, but is instead influenced by a number of interacting factors, as would be expected by the biopsychosocial model of behaviour.
Module 5.3a Quiz:
Physical and Psychological Effects of Drugs
Know . . . 1. Physical dependence occurs when
A. an individual will die if he does not continue to use the drug. B. an individual desires a drug for its pleasant effects. C. an individual has to take the drug to prevent or stop unpleasant
withdrawal symptoms.
D. an individual requires increasingly larger amounts of a substance to experience its effects.
Understand . . . 2. Drug tolerance occurs when
A. an individual needs increasingly larger amounts of a drug to achieve the same desired effect.
B. individuals do not pass judgment on drug abusers. C. an individual experiences withdrawal symptoms. D. an individual starts taking a new drug for recreational purposes.
Apply . . . 3. Which is NOT a way in which drugs affect neurotransmitter levels?
A. Binding to receptors that would normally receive the neurotransmitters
B. Stimulating the release of excess neurotransmitters C. Preventing down-regulation from occurring D. Preventing neurotransmitters from being reabsorbed into the cell
that released them
Commonly Abused “Recreational” Drugs
Thus far, we have discussed some of the ways in which drugs can affect our brain and our behaviour. These drugs are categorized based on their effects on the nervous system. Drugs can speed up the nervous system, slow it down,
stimulate its pleasure centres, or distort how it processes the world. Table 5.3 provides an overview of some of the better-known drugs.
Table 5.3 The Major Categories of Drugs
Drugs Psychological
Effects
Chemical Effects Tolerance Likelihood of
Dependence
Stimulants:
caffeine,
cocaine,
amphetamine,
ecstasy
Euphoria,
increased
energy,
lowered
inhibitions
Increase
dopamine,
serotonin,
norepinephrine
activity
Develops
quickly
High
Marijuana Euphoria,
relaxation,
distorted
sensory
experiences,
paranoia
Stimulates
cannabinoid
receptors
Develops
slowly
Low
Hallucinogens:
LSD, psilocybin,
DMT, ketamine
Major distortion
of sensory and
perceptual
experiences.
Fear, panic,
paranoia
Increase
serotonin
activity; block
glutamate
receptors
Develops
slowly
Very low
Opiates: heroin Intense
euphoria, pain
relief
Stimulate
endorphin
receptors
Develops
quickly
Very high
Sedatives:
barbiturates,
benzodiazepines
Drowsiness,
relaxation,
sleep
Increase GABA
activity
Develops
quickly
High
Alcohol Euphoria,
relaxation,
lowered
inhibitions
Primarily
facilitates GABA
activity; also
stimulates
endorphin and
dopamine
receptors
Develops
gradually
Moderate to
high
Almost all of the drugs discussed in this chapter are known as psychoactive drugs , substances that affect thinking, behaviour, perception, and emotion. However, not all of them are legal. As you will see, the boundary between illicit recreational drugs and legal prescription drugs can be razor-thin at times. Many common prescription medications are chemically similar, albeit safer, versions of illicit drugs; additionally, many legal prescription drugs are purchased illegally and used in ways not intended by the manufacturer.
Stimulants
Stimulants are a category of drugs that speed up the activity of the nervous system, typically enhancing wakefulness and alertness. There are a number of different types of stimulant drugs, ranging from naturally occurring substances such as leaves (cocaine) and beans (coffee) to drugs produced in a laboratory (crystal meth). Additionally, each drug has its own unique effect on the nervous system, influencing the levels of specific neurotransmitters in one of the four ways discussed earlier in this module.
The most widely used—and perhaps abused—stimulant is one that is likely in
front of you as you read this: caffeine. Caffeine is not a “recreational” drug per se; however, because its neural mechanisms are similar to other stimulants, we will discuss it here. Caffeine can be found in many substances including coffee, tea, many soft drinks, and chocolate. It should come as no surprise that caffeine tends to temporarily increase energy levels and alertness. It produces these
effects by influencing the activity of a brain chemical called adenosine. When adenosine binds to its receptors in the brain, it slows down neural activity. In fact, it helps you become sleepy. Caffeine binds to adenosine receptors, but without causing a reduction in neural activity. In other words, it prevents adenosine from doing its job. At the same time, caffeine stimulates the adrenal glands to release adrenaline. This hormone accounts for the burst of energy associated with caffeine. Given that adrenaline is also associated with “fight or flight” responses, it may also explain why many people feel jittery after consuming too much caffeine.
Although no drug is harmless, the withdrawal effects associated with it are far less severe than those found for other stimulants. Depriving yourself of caffeine will typically result in headaches, fatigue, and occasionally nausea; however, these symptoms will usually disappear after two to three days. Other stimulants are not so forgiving.
Cocaine is another commonly abused stimulant. It is synthesized from coca leaves, most often grown in South American countries such as Colombia, Peru, and Bolivia. The people who harvest these plants often take the drug in its simplest form—they chew on the leaves and experience a mild increase in energy. However, by the time it reaches Canadian markets, it has been processed into powder form. It is typically snorted and absorbed into the bloodstream through the nasal passages or, if prepared as crack cocaine, smoked in a pipe. Cocaine influences the nervous system by blocking the reuptake of dopamine in reward centres of the brain, although it can also
influence serotonin and norepinephrine levels as well (see Figure 5.17 ). By preventing dopamine from being reabsorbed by the neuron that released it, cocaine increases the amount of dopamine in the synapse between the cells, thus making the postsynaptic cell more likely to fire. The result is an increase in
energy levels and a feeling of euphoria.
Figure 5.17 Stimulant Effects on the Brain Like many addictive drugs, cocaine and amphetamines stimulate the reward centres of the brain, including the nucleus accumbens and ventral tegmental area. Cocaine works by blocking reuptake of dopamine, and methamphetamine works by increasing the release of dopamine at presynaptic neurons.
Amphetamines, another group of stimulants, come in a variety of forms. Some are prescription drugs, such as methylphenidate (Ritalin) and modafinil (Provigil), which are typically prescribed for attention deficit hyperactivity disorder (ADHD) and narcolepsy, respectively. When used as prescribed, these drugs can have beneficial effects; oftentimes, however, these drugs are used recreationally. Other stimulants, such as methamphetamine, are not prescribed drugs. Methamphetamine, which stimulates the release of dopamine in presynaptic
cells (see Figure 5.17 ), may be even more potent than cocaine when it comes to addictive potential. (Crystal meth, a drug made famous by the TV program Breaking Bad, is a form of methamphetamine that has undergone additional chemical refinement to remove impurities.) Methamphetamines are
also notorious for causing significant neurological and external physical problems. For example, chronic methamphetamine abusers often experience deterioration of their facial features, teeth, and gums, owing to a combination of factors. First, methamphetamine addiction can lead to neglect of basic dietary and hygienic care. Second, the drug is often manufactured from a potent cocktail of substances including hydrochloric acid and farm fertilizer—it is probably not surprising that these components can have serious side effects on appearance and health.
Long-term use of potent stimulants like methamphetamines can actually alter the structure of the user’s brain. Compared to non-users, people who have a history of abusing methamphetamine have been shown to have structural abnormalities of cells in the frontal lobes, which reduce the brain’s ability to inhibit irrelevant
thoughts (Tobias et al., 2010). This ability can be measured through the Stroop test (Figure 5.18 ), which challenges a person’s ability to inhibit reading a word in favour of identifying its colour. Methamphetamine abusers had greater difficulty with this task than non-users, and they also had reduced activity in the
frontal lobes, likely because of the damage described previously (Salo et al., 2010).
Figure 5.18 The Stroop Task The Stroop task requires you to read aloud the colour of the letters of these sample words. The task measures your ability to inhibit a natural tendency to read the word, rather than identify the colour. Chronic methamphetamine users have greater difficulty with this task than do non-users.
It often comes as a surprise to learn that the very substances that people can become addicted to, or whose possession and use can even land them in prison today, were once ingredients in everyday products. Cocaine was once used as an inexpensive, over-the-counter pain remedy. A concoction of wine and cocaine was popular, and the drug was also added to cough syrups and drops for treating toothaches. Coca-Cola used to contain nine milligrams of cocaine per
glass; this practice ceased in 1903 (Liebowitz, 1983). Advertising Archive/Courtesy Everett Collection
Theresa Baxter was 42 when the picture on the left was taken. The photo on the right was taken 2.5 years later; the effects of methamphetamine are obvious and striking. Multnomah County Sheriff/Splash/Newscom
Changes in brain structure have also been noted in chronic users of ecstasy
(3,4-methylenedioxy-N-methylamphetamine or MDMA), a drug that is typically classified as a stimulant, but also has hallucinogenic effects (Cowan et al., 2008). MDMA was developed in 1912 by the German pharmaceutical company Merck KGaA; it was originally designed as a blood-clotting agent (Meyer, 2013). In the late 1970s, it was rediscovered by a chemist at the Dow chemical
company, who described its emotional and sensual effects (Shulgin & Nichols, 1978). In the 1980s, it was labelled a “club drug” because of its frequent appearance at nightclub and rave parties. Ecstasy exerts its influence on the brain by stimulating the release of massive amounts of the neurotransmitter serotonin; it also blocks its reuptake, thereby ensuring that neurons containing serotonin receptors will fire at levels much greater than normal. Ecstasy heightens physical sensations and is known to increase social bonding and compassion among those who are under its influence. Unfortunately, this drug has also been linked to a number of preventable deaths. Heat stroke and
dehydration are major risks associated with ecstasy use, especially when the drug is taken at a rave where there is a high level of physical exertion from dancing in an overheated environment. It can also lead to lowered mood two to five days after consumption, as it takes time for serotonin levels to return to
normal (Curran & Travill, 1997).
The long-term effects of ecstasy use are difficult to identify because most users of this drug also abuse other illegal substances. That said, recent neuroimaging studies with long-term ecstasy users have highlighted some of the effects this
drug can have on the brain (Urban et al., 2012). For instance, several studies have shown that MDMA impairs the sensitivity of many visual regions in the
occipital lobe (Oliveri & Calvo, 2003; White et al., 2013). Additionally, recent neuroimaging data show that using ecstasy can produce unique damage (independent of the effects of other drugs) in several areas of the cortex in the
left hemisphere (Cowan et al., 2003). Given that the left hemisphere is also critical for language abilities, it should come as no surprise that ecstasy users show slight impairments on language-based tests of memory (e.g., lists of words;
Laws & Kokkalis, 2007).
Hallucinogens
Hallucinogenic drugs are substances that produce perceptual distortions. Depending on the type of hallucinogen consumed, these distortions may be visual, auditory, and sometimes tactile in nature, such as the experience of crawling sensations against the skin. Hallucinogens also alter how people perceive their own thinking. For example, deep significance may be attached to what are normally mundane objects, events, or thoughts. One commonly used hallucinogen is LSD (lysergic acid diethylamide), which is a laboratory-made (synthetic) drug. A recent study examined brain activity of individuals after they
had just taken LSD (Carhart-Harris et al., 2016). These researchers found that the LSD experience involves greater activity in visual areas; this activity strongly correlated with participants’ reports of hallucinations. The researchers also noted reduced connectivity between areas in the temporal and parietal lobe; these changes were related to feelings of “losing oneself” and finding “altered meanings.” These results show the strong link between brain activity and
moment-to-moment experiences.
Hallucinogenic substances also occur in nature, such as psilocybin (a mushroom) and mescaline (derived from the peyote cactus). Hallucinogens can have very long-lasting effects—more than 12 hours for LSD, for example. These drugs may also elicit powerful emotional experiences that range from extreme euphoria to fear, panic, and paranoia. The two most common hallucinogens, LSD and psilocybin, both act on the transmission of serotonin.
Short-acting hallucinogens have become increasingly popular for recreational use. The effects of two of these hallucinogens, ketamine and DMT (dimethyltryptamine), last for about an hour. Ketamine (street names include “Special K” and “Vitamin K”) was originally developed as a surgical anesthetic to be used in cases where a gaseous anesthetic could not be applied, such as on the battlefield. It has been gaining popularity among university students as well as among people who frequent dance clubs and raves. Ketamine induces dream-like states, memory loss, dizziness, confusion, and a distorted sense of
body ownership (i.e., feeling like your body and voice don’t belong to you; Fu et al., 2005; Morgan et al., 2010). This synthetic drug blocks receptors for glutamate, which is an excitatory neurotransmitter that is important for, among other things, memory.
The short-acting hallucinogen known as DMT occurs naturally in such different places as the bark from trees native to Central and South America and on the skin surface of certain toads. DMT is even found in very small, naturally
produced amounts in the human nervous system (Fontanilla et al., 2009). The function of DMT in the brain remains unclear, although some researchers have speculated that it plays a role in sleep and dreaming, and even out-of-body
experiences (Barbanoj et al., 2008; Strassman, 2001). DMT is used in Canada primarily for recreational purposes. Users frequently report having intense “spiritual” experiences, such as feeling connected to or communicating with divine beings (as well as aliens, plant spirits, and other beings that aren’t part of most modern people’s version of reality). In fact, its ability to apparently enhance spiritual experiences has been well known in South American indigenous
cultures. DMT is the primary psychoactive ingredient in ayahuasca, which plays
a central role in shamanistic rituals involving contact with the spirit world. An
increasing number of Canadians have used another drug, salvia divinorum, for similar purposes.
Many psychedelics can have serious negative consequences on users, ranging from memory problems to unwanted “flashbacks” in which the user re- experiences the visual distortions and emotional changes associated with the
psychedelic state (Halpern & Pope, 2003). However, as you read in the introduction to this module, some psychedelics are now being used to treat a number of clinical conditions. LSD has been used to help people deal with the
anxiety associated with terminal illnesses (Gasser et al., 2015). Psilocybin (magic mushrooms), ayahuasca, and DMT have all been used to help reduce
addiction to tobacco and alcohol (Tupper et al., 2015). MDMA (ecstasy) has been used to help people suffering from post-traumatic stress disorder or PTSD
(Mithoefer et al., 2011, 2013). Obviously these drugs are generally only used when traditional treatments are ineffective. But, it does demonstrate that the line between “recreational drugs” and “medical drugs” is not as clear cut as we might think.
Marijuana
Thus far, we have discussed drugs that stimulate the central nervous system and drugs that lead to altered states of consciousness. However, not all drugs neatly
fit into these distinct categories. For instance, marijuana is a drug comprising the leaves and buds of the Cannabis plant that produces a combination of hallucinogenic, stimulant, and relaxing (narcotic) effects. These buds contain a high concentration of a compound called tetrahydrocannabinol (THC). THC
mimics anandamide, a chemical that occurs naturally in the brain and the peripheral nerves. Both anandamide and THC bind to cannabinoid receptors and induce feelings of euphoria, relaxation, reduced pain, and heightened and
sometimes distorted sensory experiences (Edwards et al., 2012; Ware et al., 2010). They also stimulate one’s appetite (Kirkham, 2009). Although “having the munchies” might seem like a funny side effect for recreational users, it is an incredibly important benefit for cancer sufferers who use medicinal marijuana to counteract the nausea and lack of appetite that occurs following chemotherapy
(Machado Rocha et al., 2008).
From the above list, it is clear that marijuana use can affect a number of different behaviours. Missing from this list, however, are the effects that this drug can have on our cognitive abilities.
Biopsychosocial Perspectives Recreational
and Spiritual Uses of Salvia Divinorum Salvia divinorum is an herb that grows in Central and South America. When smoked or chewed, salvia induces highly intense but short-lived
hallucinations. Use of this drug also leads to dissociative experiences—a detachment between self and body (Sumnall et al., 2011). An exploration of salvia reveals a great deal about how cultural views affect how drugs are perceived. A single drug could be described as recreational, addictive, and a scourge to society in one culture, yet highly valued and spiritually significant to another.
Test what you know about this drug:
True or False? 1. Sale of salvia is prohibited by the Canadian government. 2. Very few young people in Canada who use drugs have tried
salvia.
3. Salvia has profound healing properties.
Answers 1. True. The legal status of salvia changed in February 2016.
Previously, it had been listed as a natural product under the control of Health Canada; although technically illegal, regulations controlling salvia were not strictly enforced. However, it is now
listed as a Schedule IV drug under the Controlled Drugs and Substances Act. It is illegal to sell, cultivate, or transport salvia,
although possession of small amounts is still legal. Further details of the change, passed by the Conservative government in 2015,
can be found online: www.hc-sc.gc.ca/hc-ps/substancontrol/ substan/legal-salvia-statut-eng.php.
2. False. The use of salvia is on the rise among North Americans and Europeans, particularly among younger people (Nyi et al., 2010). Approximately 7.3% of Canadians aged 15–24 have tried it (Health Canada, 2010).
3. False. There is no scientific evidence that salvia has healing properties. Whether one agrees with this statement, however, depends on who is asked. Among the Mazateca people of Mexico, salvia is used in divine rituals in which an individual communicates with the spiritual world. Shamans of the Mazateca people use salvia for spiritual healing sessions. They believe the drug has profound medicinal properties.
Drugs such as salvia and ayahuasca raise important questions about the effects of drugs and our view toward them. Although a given drug usually has standard, reliable effects on brain chemistry, the subjective experience it provides, the purposes it is used for, and people’s attitudes toward the drug may vary widely depending on the cultural context.
Salvia divinorum is a type of sage plant that grows naturally in Central and South America. Users of the herb chew or smoke the leaves or
combine juices from the leaves with tea for drinking. Ted Kinsman/Photo Researchers, Inc./Science Source
Working the Scientific Literacy Model Marijuana, Memory, and Cognition
No one doubts that marijuana affects a person’s thinking and behaviour. That said, descriptions of the exact nature of these effects are often more anecdotal than scientific. The earliest
reference to marijuana is found in the ancient Hindu text Raja Nirghanta, which translates the drug as “promoter of success,” “the cause of the reeling gait,” and “the laughter moving” (see
Chopra & Chopra, 1957). Indeed. More recent descriptions have noted that marijuana’s effects on one’s ability to think are both widespread and testable.
What do we know about the effects of marijuana on memory and cognition? Studies of people under the influence of marijuana have demonstrated a number of different impairments to memory
processes (Crean et al., 2011). Several researchers have confirmed that marijuana disrupts short-term memory
(Ranganathan & D’Souza, 2006). Studies of long-term memory have indicated that marijuana use was associated with a reduced
ability to recall information (Miller et al., 1977) and a greater tendency to commit intrusion errors—adding in words that were not actually on a list of to-be-remembered items (i.e., a “false
positive”; Hooker & Jones, 1987; Pfefferbaum et al., 1977). Marijuana also affects a number of cognitive abilities. Executive functions, such as decision making and the control of attention, are critical for dealing with novel situations and for changing or
inhibiting responses to stimuli in the environment. Many executive functions are impaired by THC. For instance, marijuana impairs people’s ability to problem solve and to change their strategies
while performing a task (Bolla et al., 2002; Pope et al., 2003). It may impair creative thinking and attention as well (Hermann et al., 2007; Kowal et al., 2015).
How can science explain these effects? Neuroimaging results indicate that the memory and cognitive difficulties experienced by people who smoke marijuana are likely related to changes in the brains of marijuana smokers. A number of studies have noted that reduced performance on memory tests is related to decreases in brain activity in the right frontal lobe
(Block et al., 2002; Jager et al., 2007), an area involved with memory retrieval (Tulving et al., 1994). Interestingly, some researchers have found that even when marijuana users and healthy control participants produce the same results on a memory test, their brains generate different patterns of activity.
For instance, Kanayama and colleagues (2004) found that participants who had recently smoked marijuana (< 24 hours ago) were able to perform a spatial memory task; but doing so recruited a much more widespread network of brain regions, including several that are not typically associated with memory. This suggests that the brains of marijuana users need to work harder to reach the same level of performance, oftentimes relying
on additional brain structures to help out (Jager et al., 2006).
Problems with executive functions can also be explained, at least in part, by differing patterns of brain activity. The inability to inhibit responses on a Stroop task (which was discussed earlier in this module) was related to the fact that marijuana users had less activity than healthy controls in a number of frontal-lobe regions
(Eldreth et al., 2004; Gruber & Yurgelun-Todd, 2005). These studies also demonstrated that, similar to the memory studies, the brains of marijuana users had additional activity in areas not
typically associated with the task they were performing. In other words, these brains had to find alternative networks to allow them to compensate for the marijuana so that they could still perform
the task (Martín-Santos et al., 2010).
Can we critically evaluate this information? When we look at these data, we have to remember that fMRI activity is correlational. The orange and yellow “lights” in the brain pictures represent areas that are activated at the same time that a person is performing a task; but, it doesn’t mean that those areas are causing the person’s behaviour. More importantly, we have to think of the participants in drug studies. Many of the people involved in these studies use more than one drug (e.g., marijuana plus alcohol, tobacco, and possibly other drugs). It is
therefore difficult to isolate the effects of marijuana by itself on cognition.
One way to get around these problems is to look at which areas of the brain are involved with these different abilities and then see if marijuana targets those areas. As it turns out, a receptor sensitive to THC, the cannabinoid (CB1) receptor, is found throughout the hippocampus and in the medial part of the frontal
lobes (Pertwee & Ross, 2002; see Figure 5.19 ). Importantly, stimulating these receptors can lead to impairments in short-term
memory and higher-level thinking (Ranganathan & D’Souza, 2006). Thus, there is a cellular-level mechanism that can explain (some of) the odd behaviours that you see when people are smoking up.
Figure 5.19 CB1 Receptors in the Brain
The locations of the CB1 receptors, which bind to the active ingredient in marijuana, help explain the diverse effects users often experience. CB1 receptors are found in the frontal lobes (executive functions), hippocampus (memory), and cerebellum (coordination of movement). They are also found in the nucleus accumbens, an area related to the rewarding feeling associated with many drugs. Courtesy of National Institute of Drug Abuse
Why is this relevant? Marijuana use seems, to many people, harmless and funny. What’s so bad about spending hours getting high, watching cartoons, and eating chips? But, although occasional use hasn’t been linked to serious cognitive consequences, recent brain- imaging studies of long-term smokers showed reduced amounts of grey matter (neurons) in memory regions of the temporal lobe
(Battistella et al., 2014); there were also fewer white-matter connections involving this brain area (Zalesky et al., 2012). In other words, chronic marijuana use can influence how parts of the brain transmit and receive information. Heavy long-term use
of marijuana is also related to a four-point decline in IQ scores (a
number that isn’t huge, but is still something to think about; Fried et al., 2002). Importantly, the strains of marijuana that are currently available tend to be higher in THC content than the
strains available to previous generations of drug users (Hardwick & King, 2008). It is possible, therefore, that the small cognitive deficits found in current studies of long-term marijuana users may be magnified in young people who are just beginning to use this drug.
Marijuana and the Teenage Brain
Marijuana use often starts during the teenage years. From a neurological
perspective, early drug use is a particular cause for concern (Lubman et al., 2015). The brain develops in a step-by-step fashion, with higher-order cognitive areas—particularly the frontal lobes—developing after other areas have fully
matured (Gogtay et al., 2004). As part of this step-by-step development, the white-matter fibres connecting brain regions grow and form new connections while unnecessary synapses are pruned away. Marijuana use during the teenage years has been shown to impair both of these developmental processes
(Gruber et al., 2014). It has also been linked with thinning (i.e., fewer cells) in a number of cortical areas (Mashhoon et al., 2015; Price et al., 2015) and smaller hippocampal volumes (Ashtari et al., 2011).
These changes in the brain’s development can affect cognitive abilities. Increasing evidence indicates that the effects of marijuana on memory and executive functions are much larger in people who started taking the drug before
the age of 17 (Brook et al., 2008; Pope et al., 2003). In other words, using marijuana during an earlier stage of development can have a much larger effect on a person’s future than if the same dose were to be consumed or smoked later
in life (Squeglia et al., 2009). These data therefore suggest that prevention programs should specifically target teens to ensure that their cognitive abilities
don’t go up in smoke.
It is important to note that if you did smoke marijuana before the age of 17, your life isn’t ruined. It just means that if you continue to frequently use marijuana, you are statistically more likely to have memory and executive functioning programs later in life. It is quite possible that your brain will recover. You can help it bounce back by reducing your consumption of drugs and by engaging in behaviours that help increase the thickness of white-matter pathways in the frontal lobes (e.g.,
mindfulness training; see Modules 14.3 and 16.2 ). So, you have a lot of control over what happens to your brain.
Currently, marijuana is the most commonly used recreational drug in Canada. Indeed, survey research suggests that 22% of people aged 15–19 (469 000 Canadian teens) had used marijuana within the year prior to the survey
(Statistics Canada, 2013). This high usage rate reflects, in part, the fact that this drug is so readily available. A similar issue is emerging for another class of drugs, opiates, which includes well-known narcotics such as heroin, as well as many commonly abused prescription drugs.
Opiates
Opiates (also called narcotics) are drugs such as heroin and morphine that reduce pain and induce extremely intense feelings of euphoria. These drugs bind to endorphin receptors in the nervous system. Endorphins (“endogenous morphine”) are neurotransmitters that reduce pain and produce pleasurable sensations—effects magnified by opiates. Naturally occurring opiates are derived from certain species of poppy plants that are primarily grown in Asia and the Middle East (particularly Afghanistan). Opiate drugs are very common in medical and emergency room settings. For example, the drug fentanyl is used in emergency rooms to treat people in extreme pain. A street version of fentanyl, known as “China White,” can be more than 20 times the strength of more commonly sold doses of heroin. This drug is so dangerous that in April 2016, British Columbia declared a public health emergency after more than 200 people died from overdoses of the drug. Yet despite the well-publicized dangers, people continue to use it.
Treating opiate addiction can be incredibly challenging. Opiates produce very rapid and powerful “highs”; because the time between injecting or smoking opiates and their physical impact is so short, it is easy for people to mentally link the drug to the pleasurable feeling. This increases the addictiveness of these drugs. People who are addicted to opiates and other highly addictive drugs enter a negative cycle of having to use these drugs simply to ward off withdrawal effects, rather than to actually achieve the sense of euphoria they may have
experienced when they started using them. Methadone is an opioid (a synthetic opiate) that binds to opiate receptors but does not give the same kind of high that heroin does. A regimen of daily methadone treatment can help people who are addicted to opiates avoid painful withdrawal symptoms as they learn to cope without the drug. In recent years, newer alternatives to methadone have been found to be more effective and need to be taken only a few times per week.
Another opioid, oxycodone (OxyContin), has helped many people reduce severe pain while having relatively few side effects. Unfortunately, this drug, along with a similar product, Percocet, has very high abuse potential. It is often misused, especially by those who have obtained it through illegal means (i.e., without a prescription). Indeed, the abuse of prescription opiates is a growing problem in
Canada, particularly among high school students and the elderly (Sproule et al., 2009); this topic will be discussed in more detail later in this module.
Module 5.3b Quiz:
Commonly Abused “Recreational” Drugs
Know . . . 1. are drugs that increase central nervous system activity.
A. Hallucinogens B. Narcotics C. Psychoactive drugs D. Stimulants
2. Drugs that are best known for their ability to alter normal visual and
auditory perceptions are called . A. hallucinogens B. narcotics C. psychoactive drugs D. stimulants
Apply . . . 3. Which statement about marijuana’s effects on memory is not true?
A. Marijuana use led to poorer recall of information and a greater tendency to remember information that hadn’t been presented earlier (false alarms).
B. Marijuana leads to decreased activity in brain areas related to memory retrieval.
C. Marijuana use led to poorer recall of information and a lower tendency to remember information that hadn’t been presented earlier (false alarms).
D. Areas of the brain not typically involved with memory are active when smokers attempt to recall information.
Legal Drugs and Their Effects on Consciousness
So far we have covered drugs that are, for the most part, produced and distributed illegally. Some prescription drugs can also have profound effects on consciousness and, as a consequence, are targets for misuse.
Sedatives
Sedative drugs , sometimes referred to as “downers,” depress activity of the central nervous system. Barbiturates were an early form of medication used to treat anxiety and promote sleep. High doses of these drugs can shut down the brainstem regions that regulate breathing, so their medical use has largely been discontinued in favour of safer drugs. Barbiturates have a high potential for
abuse, typically by people who want to lower inhibitions, relax, and try to improve their sleep. (Incidentally, while these agents may knock you out, they do not really improve the quality of sleep. Barbiturates actually reduce the amount of REM sleep.)
Newer forms of sedative drugs, called benzodiazepines, include prescription drugs such as Xanax, Ativan, and Valium. These drugs increase the effects of gamma-aminobutyric acid (GABA), an inhibitory neurotransmitter that helps reduce feelings of anxiety or panic. The major advantage of benzodiazepine drugs over barbiturates is that they do not specifically target the brain regions responsible for breathing and, even at high doses, are unlikely to be fatal. However, people under the influence of any kind of sedative are at greater risk for injury or death due to accidents caused by their diminished attention, reaction time, and coordination.
Prescription Drug Abuse
Prescription drugs are commonly abused by illicit users; over 15% of Canadian high school students have reported abusing prescription drugs at some point in
their lives (Hammond et al., 2010; Figure 5.20 ). The prevalence of prescription drug abuse becomes even more extreme when these students enter university. Surveys have shown that as many as 31% of university students sampled have abused Ritalin, the stimulant commonly prescribed as a treatment
for ADHD (Bogle & Smith, 2009). A massive number of prescription drugs are available on the market, including stimulants, opiates, and sedatives. In 2011,
3.2% of Canadians (approximately 1.1 million people) used prescription drugs for nonmedical reasons within the year prior to the survey (Health Canada, 2012). Users typically opt for prescription drugs as their drugs of choice because they are legal (when used as prescribed), pure (i.e., not contaminated or diluted), and relatively easy to get. Prescription drugs are typically taken at large doses, and administered in such a way as to get a quicker, more intense effect—for
example, by crushing and snorting stimulants such as Ritalin (see Figure 5.21 ).
Figure 5.20 Frequency of Drug Use among Grade 12 Students The abuse of prescription and over-the-counter drugs is becoming increasingly common in Canada. In a 2008 nationwide survey, over 15% of Grade 12 students admitted to illegally using these drugs at least once. This figure illustrates how the prevalence of prescription drug abuse compares to that of other frequently abused substances. Source: Based on Hammond, D., Ahmed, R., Burkhalter, R., Sae Yang, W., & Leatherdale, S. (2010). Illicit substance use
among Canadian youth: Trends between 2002 and 2008. Canadian Journal of Public Health, 102, 7-12.
Some of the most commonly abused prescription drugs in Canada are painkillers such as OxyContin. When used normally, OxyContin is a pain-reliever that slowly releases an opioid over the course of approximately 12 hours, thus making it a
relatively safe product (Roth et al., 2000). However, crushing the OxyContin tablet frees its opioid component oxycodone from the slow-release mechanism; it can then be inhaled or dissolved in liquid and injected to provide a rapid “high”
(Carise et al., 2007). Almost 80% of people entering treatment programs for OxyContin abuse admitted that the drug was not prescribed to them, suggesting that there is a flourishing trade in this drug. Indeed, a recent study of drug users in Vancouver found that OxyContin is quite easy to illegally purchase in Canada
(Nosyk et al., 2012); not surprisingly, the number of people entering drug rehabilitation programs for oxycodone abuse is also increasing (Sproule et al., 2009). In order to counteract this trend, Purdue Pharma Canada, the company that makes the drug, has replaced it with a similar substance, OxyNeo, that is
more difficult to grind up into a powder. However, this action will likely have little
effect on addiction rates—in April 2013, the federal government allowed six pharmaceutical companies to begin manufacturing generic (cheaper) versions of the drug.
Figure 5.21 Ritalin and Cocaine Stimulants like methylphenidate (Ritalin) affect the same areas of the brain as cocaine, albeit with different speed and intensity. The National Institute on Drug Abuse
Curbing prescription drug abuse poses quite a challenge. Approaches to reducing this problem include efforts to develop pain medications that do not act on pleasure and reward centres of the brain. For example, pain can be reduced by the administration of compounds that stimulate cannabinoid receptors in peripheral regions of the nervous system, thereby avoiding the high associated with stimulation of receptors within the brain. Many communities offer prescription drug disposal opportunities, which helps remove unused drugs from actual or potential circulation. In addition, doctors and other health care professionals are becoming increasingly aware that some individuals seeking prescription drugs are doing so because they are addicted to them.
PSYCH@ University Parties Researchers have determined that university students drink significantly
more than their peers who do not attend university (Carter et al., 2010). However, although heavy drinking—particularly on the weekend—is often
associated with positive emotions (Howard et al., 2015), it can lead to some serious consequences for students. In one study, nearly half of the university student participants binge-drank, one-third drove under the influence, 10% to 12% sustained an injury or were assaulted while
intoxicated, and 2% were victims of date rape while drinking (Hingson et al., 2009). Alcohol abuse in our society is widespread, especially during times of celebration (Glindemann et al., 2007), so it might seem as if universities have few options at their disposal to reduce reckless drinking on campus. Psychologists Kent Glindemann, Scott Geller, and their associates, however, have conducted some interesting field studies in fraternity houses at their U.S. university. For example, in two separate studies, these researchers measured the typical blood-alcohol level at fraternity parties. They then offered monetary awards or entry into a raffle for fraternities that could keep their average blood-alcohol level below 0.05 at their next party. The interventions proved to be successful in both studies, with blood-alcohol levels being significantly reduced from the
baseline (Fournier et al., 2004; Glindemann et al., 2007).
Alcohol
Alcohol can be found in nearly every culture, although some frown on its use more than others. Alcohol use is a part of many cherished social and spiritual rituals, but is also associated with violence and accidents. It has the power to change societies, in some cases for the worse. Several decades ago, “problem drinking” was not an issue for the Carib people of Venezuela, for example. During specific yearly festivals, alcohol was brewed and consumed in limited amounts. In more recent years, the influence of Western civilization has led to the emergence of problems with alcohol abuse and alcoholism in this group of
people (Seale et al., 2002). Most societies regard alcohol as an acceptable form of drug use, though they may attempt to limit and regulate its use through legal means. Customs and social expectations also affect usage. For example, drinking—especially heavy drinking—is generally considered more socially
acceptable for men than for women.
Alcohol has a number of effects on the brain. It initially targets GABA receptors, and subsequently affects opiate and dopamine receptors. The stimulation of opiate and dopamine receptors accounts for the euphoria associated with lower doses as well its rewarding effects. The release of GABA, an inhibitory neurotransmitter, reduces the activity of the central nervous system, which helps explain the impairments in balance and coordination associated with consumption of alcohol. But if alcohol increases the release of an inhibitory brain
chemical, why do people become less inhibited when they drink? The reason for this behaviour is that alcohol inhibits the frontal lobes of the brain. One function of the frontal lobes is to inhibit behaviour and impulses, and alcohol appears to impair the frontal lobe’s ability to do so—in other words, it inhibits an inhibitor.
The lowered inhibitions associated with alcohol may help people muster the courage to perform a toast at a wedding, but many socially unacceptable consequences are also associated with alcohol use. Alcohol abuse has been linked to health problems, sexual and physical assault, automobile accidents, missing work or school, unplanned pregnancies, and contracting sexually
transmitted diseases (Griffin et al., 2010). These effects are primarily associated with heavy consumption, which can often lead to alcohol myopia (Steele & Josephs, 1990). When intoxicated, people often pay more attention to cues related to their desires and impulses (e.g., the attractive-looking person on the couch at the party) and less attention to cues related to inhibiting those desires (e.g., friends telling them to stop drinking, or the lecture about safe sex that they received in their sex-education class). This tendency to focus on short-term rewards rather than long-term consequences is particularly noticeable in underage drinkers whose frontal lobes (which help inhibit behaviour) are not fully developed. Alcohol myopia is also more likely to occur in people with low self- esteem; these individuals may focus on their fear of social rejection and respond by engaging in risky behaviours that they feel will lead to social acceptance
(MacDonald & Martineau, 2002).
Why are Some Drugs Legal and Others Illegal?
In the November 2012 U.S. election, both Colorado and Washington states voted to legalize marijuana. Colorado Governor John Hickenlooper cautioned users by noting that, “[F]ederal law still says marijuana is an illegal drug, so don’t break out the Cheetos or Goldfish [crackers] too quickly.” That caveat aside, these votes do suggest that attitudes toward certain drugs are changing in the U.S., which has traditionally been much more conservative than Canada. Indeed, Alaska, Oregon, and the District of Columbia (Washington, D.C.) legalized marijuana possession in November 2014. In Canada, the newly elected government of Justin Trudeau promised to legalize marijuana as well, although the sale of this drug will likely be controlled in a manner similar to alcohol and tobacco. These changes in the legal status of marijuana lead us to an interesting question: Why are some drugs legal and others illegal?
It is relatively easy to understand some decisions, such as making drugs with intense effects (such as opium) illegal, but allowing chemically similar drugs with weaker effects (such as OxyContin) to be legal (at least, with prescriptions). But, some distinctions are less clear. Nicotine is more addictive than THC, the active ingredient in marijuana, yet the sale of tobacco products is legal while the sale of marijuana is not legal in most parts of the world. As you read earlier in this module, alcohol can lead to violence and many risky behaviours; marijuana’s most dangerous effects are to the lungs and to short-term memory (and perhaps the waistline). Yet, it is legal to buy alcohol in Canada (and even at gas stations in the U.S.!), while marijuana users in many places risk getting criminal records every time they light up. One possible argument for the difference is that it is easier to tell if people have been drinking than smoking marijuana; for example, police can use a breathalyzer to test if people are drinking and driving, whereas no such test is available for marijuana, even though it also interferes with coordination and attention. As you can see, the decision to legalize or criminalize a drug is not a simple one.
Some countries, such as Portugal, have gone ahead and decriminalized drugs. The rationale for doing so was that the “War on Drugs” was not decreasing addiction rates but was costing billions of dollars to fight. Neighboring countries were understandably nervous—if Portugal turned into a drug haven, this activity would undoubtedly affect other Mediterranean nations. However, an examination
of drug use in Portugal, Spain, and Italy suggests that decriminalization had little effect on drug use. Between 2001 (the year Portugal decriminalized drugs) and 2007, the number of Portuguese people who reported consuming any recreational drug in the previous 12 months increased 0.3%. These results were
almost identical to drug use in Spain and were lower than the levels of drug use in Italy, even though drugs were illegal in both of those countries (Hughes & Stevens, 2010).
The purpose of this section is not to promote one drug or another, nor is it to promote any political agenda regarding decriminalization. Rather, this
information should promote critical thinking and the use of science when making decisions. Today’s young people will likely be asked to make legal decisions about a number of drugs ranging from marijuana to several often-abused prescription drugs. Using rigorously controlled experiments to test the physiological and psychological effects of different drugs—and paying attention to the effects of different drug policies in other countries—will help people make informed decisions about whether or not particular substances should be banned.
Module 5.3c Quiz:
Legal Drugs and Their Effects on Consciousness
Know . . . 1. Drugs that depress the activity of the central nervous system are known
as . A. stimulants B. sedatives C. hallucinogens D. GABAs
Apply . . . 2. Research shows that one effective way to decrease problem drinking on
a college or university campus is to
A. hold informative lectures that illustrate the neural effects of
drinking.
B. give up—there is little hope for reducing drinking on campus. C. provide monetary incentives for student groups to maintain a low
average blood-alcohol level.
D. threaten student groups with fines if they are caught drinking.
Analyze . . . 3. Why are benzodiazepines believed to be safer than barbiturates?
A. Barbiturates can inhibit the brain’s control of breathing. B. Benzodiazepines can be prescribed legally, but barbiturates
cannot.
C. No one misuses benzodiazepines. D. Both benzodiazepines and barbiturates are viewed as equally
dangerous.
Module 5.3 Summary
ecstasy (MDMA)
hallucinogenic drugs
marijuana
opiates
physical dependence
psychoactive drugs
psychological dependence
sedative drugs
stimulants
tolerance
Know . . . The key terminology related to different categories of drugs and their effects on the nervous system and behaviour.
5.3a
Tolerance is a physiological process in which repeated exposure to a drug leads to a need for increasingly larger dosages to experience the intended effect. Physical dependence occurs when the user takes a drug to avoid withdrawal symptoms. Psychological dependence occurs when people feel addicted to a drug despite the absence of physical withdrawal symptoms; this form of dependence is often related to a person’s emotional reasons for using a drug (e.g., dealing with stress or negative emotions).
One tool that might help you in this regard is the scale in Table 5.4 .
Table 5.4 What Are Your Beliefs About Drug Use?
Strongly
Disagree
Disagree Neutral Agree Strongly
Agree
Marijuana should be
legalized.
1 2 3 4 5
Marijuana use among
teachers can be just
healthy experimentation.
1 2 3 4 5
Personal use of drugs
should be legal in the
confines of one’s own
home.
1 2 3 4 5
Daily use of one
marijuana cigarette is not
necessarily harmful.
1 2 3 4 5
Understand . . . drug tolerance and dependence.5.3b
Apply . . . your knowledge to better understand your own beliefs about drug use.
5.3c
Tobacco smoking should
be allowed in high
schools.
1 2 3 4 5
It can be normal for a
teenager to experiment
with drugs.
1 2 3 4 5
Persons convicted for the
sale of illicit drugs should
not be eligible for parole.
5 4 3 2 1
Lifelong abstinence is a
necessary goal in the
treatment of alcoholism.
5 4 3 2 1
Once a person becomes
drug-free through
treatment he can never
become a social user.
5 4 3 2 1
Parents should teach their
children how to use
alcohol.
5 4 3 2 1
Total
Note: This scale measures permissive attitudes toward substance use and abuse.
Higher scores indicate more permissive attitudes.
Source: Reproduced with the permission of Alcohol Research Documentation, Inc. publisher of the Journal of Studies
on Alcohol (now the Journal of Studies on Alcohol and Drugs [www.jsad.com]).
Apply Activity
For each item on the left of Table 5.4 , circle the number in the column that represents your level of agreement. After you have circled an answer for each item, add up all the circled numbers to find your final score.
The difference, such as in the case of salvia, is dependent upon cultural factors, the setting in which the drug is used, and the expectations of the user.
Review Table 5.3 for a summary of short-term effects of the major drug categories. Long-term effects of drug use include tolerance, physical dependence, and psychological dependence. Additionally, long-term use of a number of drugs can change the structure of the brain, leading to permanent deficits in a number of different cognitive and physical abilities.
Analyze . . . the difference between spiritual and recreational drug use.
5.3d
Analyze . . . the short- and long-term effects of drug use.5.3e
Chapter 6 Learning
6.1 Classical Conditioning: Learning by Association Pavlov’s Dogs: Classical Conditioning of Salivation 229
Module 6.1a Quiz 232
Processes of Classical Conditioning 233
Module 6.1b Quiz 235
Applications of Classical Conditioning 235 Working the Scientific Literacy Model: Conditioning and Negative Political Advertising 239
Module 6.1c Quiz 242
Module 6.1 Summary 242
6.2 Operant Conditioning: Learning Through Consequences Basic Principles of Operant Conditioning 245
Module 6.2a Quiz 249
Processes of Operant Conditioning 249
Module 6.2b Quiz 252
Reinforcement Schedules and Operant Conditioning 252 Working the Scientific Literacy Model: Reinforcement and Superstition 255
Module 6.2c Quiz 257
Module 6.2 Summary 258
6.3 Cognitive and Observational Learning Cognitive Perspectives on Learning 261
Module 6.3a Quiz 262
Observational Learning 262 Working the Scientific Literacy Model: Linking Media Exposure to Behaviour 265
Module 6.3b Quiz 269
Module 6.3 Summary 269
Module 6.1 Classical Conditioning: Learning by Association
Brenda Carson/Fotolia
Learning Objectives
Know . . . the key terminology involved in classical conditioning. Understand . . . how responses learned through classical conditioning can be acquired and lost.
6.1a 6.1b
What do you think of when you smell freshly baked cookies? Chances are you associate the smell of cookies with your mother or grandmother, and immediately experience a flood of memories associated with them. These associations form naturally. It is quite unlikely that your grandmother shoved a chocolate chip cookie under your nose and screamed, “Remember me!” Instead, you linked these two stimuli together in your mind; now, the smell of cookies is associated with the idea of grandmother. This ability to associate stimuli provides important evolutionary advantages: It means that you can use one stimulus to predict the appearance of another, and that your body can initiate its response to the second stimulus before it even appears. Although the link between your grandmother and the smell of cookies is not vital to your survival, similar associations such as the smell of a food that made you sick and a feeling of revulsion just might. Interestingly, we are not the only species with this ability—even the simplest animals (such as the earthworm) can learn by association, suggesting that these associations are in fact critical for survival. In this module, we will explore the different processes that influence how these associations form.
Focus Questions
1. Which types of behaviours can be learned? 2. Do all instances of classical conditioning go undetected by the
individual?
Understand . . . the role of biological and evolutionary factors in classical conditioning. Apply . . . the concepts and terms of classical conditioning to new examples. Analyze . . . the use of negative political advertising to condition emotional responses to candidates.
6.1c
6.1d
6.1e
Learning is a process by which behaviour or knowledge changes as a result of experience. To many people, the term “learning” signifies the activities that students do—reading, listening, and taking tests in order to acquire new
information. This process, which is known as cognitive learning, is just one type of learning, however. Another way that we learn is by associative learning, which is the focus of this module.
Pavlov’s Dogs: Classical Conditioning of Salivation
Research on associative learning has a long history in psychology, dating back to Ivan Pavlov (1849–1936), a Russian physiologist and the 1904 Nobel laureate
in medicine (for work on digestion, not his now-famous conditioning research). Pavlov studied digestion, using dogs as a model species for his experiments. As a part of his normal research procedure, he collected saliva and other gastric secretions from the dogs when they were presented with meat powder. Pavlov and his assistants noticed that as they prepared dogs for procedures, even before any meat powder was presented, the dogs would start salivating. This curious observation led Pavlov to consider the possibility that digestive
responses were more than just simple reflexes elicited by food. If dogs salivate in anticipation of food, then perhaps the salivary response can also be learned (Pavlov’s lab assistants referred to them as “psychic secretions”). Pavlov began conducting experiments in which he first presented a sound from a metronome, a device that produces ticking sounds at set intervals, and then presented meat powder to the dogs. After pairing the sound with the food several times, Pavlov
discovered that the metronome could elicit salivation by itself (see Figure 6.1 ).
Figure 6.1 Associative Learning Although much information may pass through the dog’s brain, in Pavlov’s experiments on classical conditioning an association was made between the clicking sound of a metronome and the food. (Pavlov used a metronome as well as other devices for presenting sounds.)
Pavlov’s discovery began a long tradition of inquiry into what is now called classical conditioning or Pavlovian conditioning —a form of associative learning in which an organism learns to associate a neutral stimulus (e.g., a sound) with a biologically relevant stimulus (e.g., food), which results in a change in the response to the previously neutral stimulus (e.g., salivation). You can think
about classical conditioning in mechanical terms—that is, one event causes
another. A stimulus is an external event or cue that elicits a perceptual response; this occurs regardless of whether the event is important or not. Some stimuli— such as food, water, pain, or sexual contact—elicit responses instinctively (i.e., without any learning being required). Each of these is an example of an unconditioned stimulus (US) , a stimulus that elicits a reflexive response without learning. An unconditioned response (UR) , on the other hand, is a reflexive, unlearned reaction to an unconditioned stimulus. URs could include hunger, drooling, expressions of pain, and sexual responses. Again, you do not need to learn these; they occur fairly automatically. In Pavlov’s experiment, meat
powder elicited unconditioned salivation in his dogs (see the top panel of Figure 6.2 ). The link between the US and the UR is, by definition, unlearned. The dog’s parents did not have to teach it to salivate when food appeared; this response occurs naturally.
Figure 6.2 Pavlov’s Salivary Conditioning Experiment Food elicits the unconditioned response of salivation. Before conditioning, the sound of the metronome elicits no response by the dog. During conditioning, the
metronome’s clicking repeatedly precedes the food. After conditioning, the sound of the metronome alone elicits salivation. Interestingly, the term “conditioning” was actually a translation error. Pavlov initially used the term “conditional” stimulus to describe stimuli that were previously unimportant (or neutral) but that later acquired greater significance due to their ability to signal the upcoming occurrence (or, in some cases, nonoccurrence) of a biologically important stimulus. These stimuli can be contrasted with stimuli such as food, which are relevant to an animal’s survival and therefore trigger an almost automatic—or “unconditional”—response such as salivating. These terms were mistranslated into English as “conditioned” and “unconditioned.”
A defining characteristic of classical conditioning is that a neutral stimulus comes to elicit a response. It does so because the neutral stimulus is paired with, and therefore predicts, an unconditioned stimulus. In Pavlov’s experiment, the sound
of the metronome was originally a neutral stimulus because it did not elicit a response, least of all salivation (see Figure 6.2 ); however, over time, it began to influence the dogs’ responses because of its association with food. In this
case, the metronome became a conditioned stimulus (CS) , a once-neutral stimulus that later elicits a conditioned response because it has a history of being paired with an unconditioned stimulus. A conditioned response (CR) is the learned response that occurs to the conditioned stimulus. In other words, after being repeatedly paired with the US, the once-neutral metronome clicking in Pavlov’s experiment became a conditioned stimulus (CS) because it elicited the conditioned response of salivation. To establish that conditioning has taken
place, the metronome’s sound (CS) must elicit salivation in the absence of food (US; see the bottom panel of Figure 6.2 ).
A common point of confusion is the difference between a conditioned response and an unconditioned response—in Pavlov’s experiment, they are both salivation. What distinguishes the UR from the CR is the stimulus that elicits them. Salivation is a UR if it occurs in response to a US (food). Salivation is a CR if it occurs in response to a CS (the clicking of the metronome). A CS can have
this effect only if it becomes associated with a US. In other words, a UR is a naturally occurring response whereas a CR must be learned.
Evolutionary Function of the CR
In Pavlov’s original experiments, the response to the signal (after pairings) and to food were exactly the same: salivation. It is important to note that the UR and CR
do not have to be identical. In Pavlov’s study, it made good evolutionary sense to salivate just prior to receiving food. Saliva moisturizes the mouth and is a critical first step in the digestive process. An animal with the ability to prepare in this way would process food more efficiently. Therefore, the CR of salivation served a useful function. Following this line of thinking, what do you think would happen if the US was unpleasant, painful, and potentially life threatening? The answer from an evolutionary perspective is pretty obvious: avoid death and minimize physical damage.
Many animals have an instinct to “freeze” when they are scared. You see this when deer are caught in headlights. They remain motionless—why? The reason is that many of their predators, such as the wolf, have perceptual systems that are quite sensitive to detecting movement; so remaining still has an evolutionary survival advantage. (Highways weren’t part of the evolution of deer.) However, if the wolf were to begin to stalk the deer, it should immediately stop freezing and run. So, there are two different defensive responses associated with fear: freezing and fleeing.
Psychologists have spent decades trying to study these defensive responses in the lab (although these experiments used rodents rather than the potentially more dramatic combination of deer and wolves). For instance, many conditioning experiments have studied the ability of rats to associate a cue (e.g., a tone) with a painful electric shock to their feet. Some of the URs to shock include flinching, jumping, and pain. However, once the rat has learned to associate the tone with the shock, the rat’s primary learned response to the tone is to “freeze” (the CR). The freezing CR has served many species well for millions of years, so it is the natural response to a fear-inducing signal in the laboratory. The lesson from this experimental situation is that UR and the CR are often quite different responses. The CR has been selected by evolution to be a helpful response.
The UR and CR sometimes differ. CRs are often evolutionarily useful behaviours such as the “freezing” response. SCS Studio/Corbis/Getty Images
This example isn’t meant to confuse you! Rather, it is to show you that classical conditioning has a dramatic effect on an organism’s survival. In other words,
conditioning has an evolutionary function, and so the CR and the UR are not necessarily the same response.
Classical Conditioning and the Brain
Classical conditioning can occur in extremely simple organisms such as Aplysia, a type of sea slug (Hawkins, 1984; Pinsker et al., 1970). Of course, the number
of possible conditioned responses is more limited in the sea slug than in humans. But, the fact that both of these species can be classically conditioned suggests that at its heart, classical conditioning is a simple biological process. The connections between specific groups of neurons (or specific axon terminals and receptor sites on neurons) become strengthened during each instance of
classical conditioning (Murphy & Glanzman, 1997).
According to the Hebb Rule (named after Canadian neurologist Donald Hebb;
see Module 7.1 ), when a weak connection between neurons is stimulated at the same time as a strong connection, the weak connection becomes strengthened. So, before conditioning, there may be a strong connection between perceiving a puff of air and a blinking response and a weak connection between a sound (e.g., a metronome) and the blinking response. But, if both networks are stimulated at the same time, the link between the sound and the blinking response would be strengthened. Over repeated conditioning trials, this connection would become strong enough that the sound itself would trigger an
eyeblink (see Figure 6.3 ).
Figure 6.3 Conditioning and Synapses During conditioning, weak synapses fire at the same time as related strong synapses. The simultaneous activity strengthens the connections in the weaker
synapse. Source: Carlson, Neil R., Psychology Of Behavior, 11th ed., Copyright © 2013, pp. 29, 72. Reprinted and electronically
reproduced by permission of Pearson Education, Inc., Upper Saddle River, New Jersey.
When reading these examples, it’s quite easy to think of conditioning as something unrelated to your life. Not many of us undergo eyeblink conditioning. But these principles still apply to your everyday existence. For instance, most of you have received a needle at the doctor’s office. In this situation, the needle caused a response of pain. The doctor’s office itself did not harm you in any way. But, over time, you may start to feel scared whenever you enter the doctor’s office because it has been repeatedly paired with pain. What do you think the US, UR, CS, and CR would be in this situation? In this case, the needle (US) causes pain (UR). The office is the neutral stimulus (NS). Over time, the sights and sounds of the doctor’s office could be the CS, because it would trigger the CR (fear). Importantly, as you will read in the next section, the strength of these networks—and thus of the conditioning—will vary depending upon how often and how consistently the CS and the US appear together.
Module 6.1a Quiz:
Pavlov’s Dogs: Classical Conditioning of Salivation
Know . . . 1. The learned response to the conditioned stimulus is known as the
. A. unconditioned stimulus B. conditioned stimulus C. conditioned response D. unconditioned response
2. A once-neutral stimulus that elicits a conditioned response because it has a history of being paired with an unconditioned stimulus is known as a(n)
. A. unconditioned stimulus
B. conditioned stimulus C. conditioned response D. unconditioned response
Apply . . . 3. A dental drill can become an unpleasant stimulus, especially for people
who may have experienced pain while one was used on their teeth. In
this case, the pain elicited by the drill is a(n) . A. conditioned response B. unconditioned stimulus C. conditioned stimulus D. unconditioned response
Processes of Classical Conditioning
Although classically conditioned responses typically involve reflexive actions, there is still a great deal of flexibility in how long they will last and how specific they will be. Conditioned responses may be very strong and reliable, which is likely if the CS and the US have a long history of being paired together. Conditioned responding may diminish over time, or it may occur with new stimuli with which the response has never been paired. We now turn to some processes that account for the flexibility of classically conditioned responses.
Acquisition, Extinction, and Spontaneous
Recovery
Learning involves a change in behaviour due to experience, which can include
acquiring a new response. Acquisition is the initial phase of learning in which a response is established; thus, in classical conditioning, acquisition is the phase in which a neutral stimulus is repeatedly paired with the US. In Pavlov’s
experiment, the conditioned salivary response was acquired with numerous metronome–food pairings (see Figure 6.4 ). A critical part of acquisition is the predictability with which the CS and the US occur together. In Pavlov’s
experiment, conditioning either would not occur or would be very weak if food was delivered only sometimes (i.e., inconsistently) when the metronome sound occurred.
Figure 6.4 Acquisition, Extinction, and Spontaneous Recovery Acquisition of a conditioned response occurs over repeated pairings of the CS and the US. If the US no longer occurs, conditioned responding diminishes—a
process called extinction. Often, following a time interval in which the CS does not occur, conditioned responding rebounds when the CS is presented again—a
phenomenon called spontaneous recovery.
Of course, even if a conditioned response is fully acquired, there is no guarantee
it will persist forever. Extinction is the loss or weakening of a conditioned response when a conditioned stimulus and unconditioned stimulus no longer occur together. For the dogs in Pavlov’s experiment, if the sound of the metronome clicking is presented repeatedly and no food follows, then salivation
should occur less and less, until eventually it may not occur at all (Figure 6.4 ). This trend probably makes sense from a biological perspective: If the sound of the metronome is no longer a reliable predictor of food, then salivation becomes unnecessary. At the neural level, the rate of firing in brain areas related
to the learned association decreases over the course of extinction (Robleto et al., 2004). However, even after extinction occurs, a previously established conditioned response can return.
A number of studies have shown that classically conditioned behaviours that had disappeared due to extinction could quickly reappear if the CS was paired with the US again. This tendency suggests that the networks of brain areas related to
conditioning were preserved in some form (Schreurs, 1993; Schreurs et al., 1998). Additionally, some animals (and humans) show spontaneous recovery , or the reoccurrence of a previously extinguished conditioned response, typically after some time has passed since extinction. Pavlov and his assistants noticed that salivation would reappear when the dogs were later returned to the experimental testing room where acquisition and extinction trials had been conducted. The dogs would also salivate again in response to a
metronome clicking, albeit less so than at the end of acquisition (Figure 6.4 ). Why would salivation spontaneously return after the response had supposedly extinguished? One possibility is that extinction also involves learning something
new (Bouton, 1994). In this case, Pavlov’s dogs would be learning that the clicking of a metronome indicates that food will not appear. It is possible that spontaneous recovery is a case of the animal not being able to retrieve the memory of extinction and thus reverting back to the original memory, the
classically conditioned response (Bouton, 2002; Brooks et al., 1999).
Extinction and spontaneous recovery are evidence that classically conditioned responses can change once they are acquired. Further evidence of flexibility of conditioned responding can be seen in some other processes of classical conditioning, including generalization and discrimination.
Stimulus Generalization and Discrimination
Stimulus generalization is a process in which a response that originally occurred for a specific stimulus also occurs for different, though similar, stimuli. In Pavlov’s experiment, dogs salivated not just to the original sound (CS), but
also to very similar sounds (see Figure 6.5 ). At the cellular level, generalization may be explained, at least in part, by the Hebb rule discussed
above. When we perceive a stimulus, it activates not only our brain’s representation of that item, but also our representations of related items. Some of these additional representations (e.g., a sound that has a slightly higher or lower pitch than the conditioned stimulus) may become activated at the same time as the synapses involved in conditioned responses. If this did occur, according to the Hebb rule, the additional synapse would become strengthened and would therefore be more likely to fire along with the other cells in the future.
Figure 6.5 Stimulus Generalization and Discrimination A conditioned response may generalize to other similar stimuli. In this case, salivation occurs not just for the 1200-Hz tone used during conditioning, but for other tones as well. Discrimination learning has occurred when responding is elicited by the original training stimulus, but much less so, if at all, for other stimuli.
Generalization allows for flexibility in learned behaviours, although it is certainly
possible for behaviour to be too flexible. Salivating in response to any sound would be wasteful because not every sound correctly predicts food. Thus
Pavlov’s dogs also showed discrimination , which occurs when an organism learns to respond to one original stimulus but not to new stimuli that may be similar to the original stimulus. In salivary conditioning, the CS might be a 1200- hertz tone, which is the only sound that is paired with food. The experimenter might produce tones of 1100 or 1300 hertz as well, but not pair these with food.
This point is critical: If stimuli that are similar to the CS are presented without a US, then it becomes less likely that these stimuli will lead to stimulus generalization. Instead, these other tones would have their own memory
representation in the brain—in which they did not receive food. So, stimulus discrimination would occur if salivation was triggered by the target 1200-hertz tone, but was not triggered (or was triggered less) in response to the other tones
(Figure 6.5 ).
Module 6.1b Quiz:
Processes of Classical Conditioning
Know . . . 1. What is the reoccurrence of a previously extinguished conditioned
response, typically after some time has passed since extinction?
A. Extinction B. Spontaneous recovery C. Acquisition D. Discrimination
Understand . . . 2. In classical conditioning, the process during which a neutral stimulus
becomes a conditioned stimulus is known as . A. extinction B. spontaneous recovery C. acquisition D. discrimination
Apply . . . 3. Your dog barks every time a stranger’s car pulls into the driveway, but
not when you come home. Reacting to your car differently is a sign of
. A. discrimination B. generalization
C. spontaneous recovery D. acquisition
Applications of Classical Conditioning
Now that you are familiar with the basic processes of classical conditioning, we can begin to explore its many applications. Classical conditioning is a common phenomenon that applies to many different situations, including emotional learning, aversions to certain foods, advertising, and responses to drugs.
Conditioned Emotional Responses
Psychologists dating back to John Watson in the 1920s recognized that our
emotional responses could be influenced by classical conditioning (Paul & Blumenthal, 1989; Watson & Rayner, 1920). These conditioned emotional responses consist of emotional and physiological responses that develop to a specific object or situation. In one of the most diabolical studies in the history of psychology, Watson and Rayner conditioned an 11-month-old child known as Albert B. (also referred to as “Little Albert”) to fear white rats. When they first presented Albert with a white rat, he showed no fear, and even reached out for the animal. Later, while Albert was again in the vicinity of the rat, they startled him by striking a steel bar with a hammer. Watson and Rayner reported that Albert quickly associated the rat with the startling sound; the child soon showed a conditioned emotional response to the rat. In this situation, the US would be the loud noise. The UR would be the feeling of fear elicited by the loud noise. With repeated pairings of the loud noise and the white rat, the white rat—which preceded the onset of the loud noise—would start to trigger fear. In this case, the white rat became the CS and the fear it elicited became the CR. Little Albert not only developed a fear of rats; the emotional conditioning generalized to other white furry objects including a rabbit and a Santa Claus mask.
It should be pointed out that ethical standards in modern-day psychological research would not allow this type of experiment to take place. To make matters
worse, it appears that Watson and Rayner did not keep in touch with Little Albert to see if there were any lasting effects from the study. In fact, the fate of Little Albert has been shrouded in mystery for almost a century. One group of researchers examined hospital records and reported that Little Albert passed away as a result of a brain illness (i.e., for reasons unrelated to this study) at the
age of 5 (Beck et al., 2009; Fridlund et al., 2012). However, researchers at Grant MacEwan University in Edmonton found evidence suggesting that Little Albert actually lived a long and relatively happy life, although he was not
comfortable around furry animals such as dogs (Digdon et al., 2014). More detective work is necessary to address these competing claims. Ironically, in
1928, Watson published a book entitled Psychological Care of Infant and Child.
The Watson and Rayner procedure may seem artificial because it took place in a laboratory, but here is a more naturalistic example. Consider a boy who sees his neighbour’s cat. Not having a cat of his own, the child is very eager to pet the animal—perhaps a little too eager, because the cat reacts defensively and scratches his hand. The cat may become a CS for the boy, which elicits a fear response. Further, if generalization occurs, the boy might become afraid of all cats. Conditioned emotional responses like these offer a possible explanation for many phobias, which are intense, irrational fears of specific objects or situations
(discussed in detail in Module 15.2 ).
During the past two decades, researchers have made great strides in identifying the brain regions responsible for such conditioned emotional responses. When an organism learns a fear-related association such as a tone predicting the onset of a startling noise, activity occurs in the amygdala, a brain area related to fear
(LeDoux, 1995; Maren, 2001). If an organism learns to fear a particular location, such as learning that a certain cage is associated with an electrical shock, then context-related activity in the hippocampus will interact with fear-related activity
in the amygdala to produce contextual fear conditioning (Kim & Fanselow, 1992; Phillips & LeDoux, 1992). Importantly, the neural connections related to conditioned fear remain intact, even after extinction has occurred. Instead, other neurons suppress the activity of the brain areas related to the fear responses
(Marek et al., 2013). If the CS is paired with the US again, this suppression will be removed and the fear-conditioned response will quickly reappear.
Watson and Rayner generalized Albert’s fear of white rats to other furry, white objects. Shown here, Watson tests Albert’s reaction to a Santa Claus mask. Archives of the History of American Psychology, The Center for the History of Psychology—The University of Akron
Neuroimaging has been used to study the brain’s responses to fear conditioning in both clinical populations and in healthy control participants. For example, scientists have conducted some fascinating experiments on people diagnosed with psychopathy (the diagnosis of “psychopathy” is very similar to antisocial
personality disorder; see Module 15.2 ). People with this disorder are notorious for disregarding the feelings of others. In one study, a sample of people diagnosed with psychopathy looked at brief presentations of human faces (neutral stimuli) followed by a painful stimulus (the US). The painful stimulus
would obviously elicit a pain response (the UR). What should have happened is that over repeated pairings, participants would acquire a negative emotional reaction (the CR) to the faces (which are now the CS); but, this particular sample did not react this way. Instead, these individuals showed very little physiological arousal, their emotional brain centres remained quiet, and overall they did not seem to mind looking at pictures of faces that had been paired with pain (see Figure 6.6 ; Birbaumer et al., 2005). In contrast, people who showed no signs of psychopathy did not enjoy this experience. In fact, following several
pairings between CS and US, the control group showed increased physiological arousal and activity of the emotion centres of the brain, and understandably reported disliking the experience of the experiment.
Figure 6.6 Fear Conditioning and the Brain During fear conditioning, a neutral stimulus (NS) such as a tone or a picture of a human face is briefly presented, followed by an unconditioned stimulus (US), such as a mild electric shock. The result is a conditioned fear response to the CS. A procedure like this has been used to compare fear responses in people diagnosed with psychopathy with control participants. The brain images show that those with psychopathy (right image) showed very little response in their emotional brain circuitry when presented with the CS. In contrast, control participants showed strong activation in their emotional brain centres (left image)
(Birbaumer et al., 2005). Source: Courtesy of Dr. Herta Flor
Evolutionary Role for Fear Conditioning
A healthy fear response is important for survival, but not all situations or objects are equally dangerous. Snakes and heights probably elicit more fear and caution than butterflies or flowers. In fact, fearing snakes is very common, which makes
it tempting to conclude that we have an instinct to fear them. In reality, young primates (both human children and young monkeys, for example) tend to be quite curious about, or at least indifferent to, snakes, so this fear is most likely the product of learning rather than instinct.
Psychologists have conducted some ingenious experi ments to address how learning is involved in snake fear. For instance, photographs of snakes (the CS) were paired with a mild electric shock (the US). One unconditioned response that a shock elicits is increased palm sweat—known as the skin conductance response. This reaction, part of the fight-or-flight response generated by the
autonomic nervous system (Module 3.3 ), occurs when our bodies are aroused by a threatening or uncomfortable stimulus. Following several pairings between snake photos and shock in an experimental setting, the snake photos alone (the CS) elicited a strong increase in skin conductance response (the CR). For comparison, participants were also shown nonthreatening pictures of flowers, paired with the shock. Much less intense conditioned responding developed in response to pictures of flowers, even though the pictures had been
paired with the shock just as many times as the snake pictures had been paired
with the shock (Figure 6.7 ; Öhman & Mineka, 2001). Thus, it appears we are predisposed to acquire a fear of snakes, but not flowers.
Figure 6.7 Biologically Prepared Fear Physiological measures of fear are highest in response to photos of snakes after the photos are paired with an electric shock—even higher than the responses to photos of guns. Flowers—something that humans generally do not need to fear in nature—are least effective when it comes to conditioning fear responses.
This finding may not be too surprising, but what about other potentially dangerous objects such as guns? In modern times, guns are far more often associated with death or injury than snakes, and certainly flowers. When the researchers paired pictures of guns (the CS) with the shock (US), they found that conditioned arousal to guns among participants was less than that to snake photos, and comparable to that of harmless flowers. In addition, the conditioned arousal to snake photos proved longer lasting and slower to extinguish than the
conditioned responding to pictures of guns or flowers (Öhman & Mineka, 2001). However, before completely accepting this finding, it is important to point out that the participants in this study were from Sweden, a country that has relatively little gun violence. It is unclear whether similar results would be found in participants
who lived in a location where gun violence was more prevalent.
This caveat aside, given that guns and snakes both have the potential to be dangerous, why is it so much easier to learn a fear of snakes than a fear of guns? One possibility is that over time, humans have evolved a strong predisposition to fear an animal that has a long history of causing severe injury
or death (Cook et al., 1986; Öhman & Mineka, 2001). The survival advantage has gone to those who quickly learned to avoid animals such as snakes. The same is not true for flowers (which do not attack humans) or guns (which are relatively new in our species’ history). This evolutionary explanation is known as preparedness , the biological predisposition to rapidly learn a response to a particular class of stimuli (Seligman, 1971).
Conditioned Taste Aversions
Another example of an evolutionarily useful conditioned fear response comes from food aversions. Chances are there is a food that you cannot stand to even look at because it once made you ill. This new aversion isn’t due to chance; rather, your brain and body have linked the taste, sight, and smell of that food to the feeling of nausea. In this situation, the taste (and often the sight and smell) of the food or fluid serves as the CS. The US is whatever substance in the food or environment happened to make you sick (e.g., some sort of bacteria); this, in turn, leads to the actual sickness (the UR). Aversion is not simply a case of “feeling gross.” Instead, it involves both a feeling (and in some species, a facial
expression) of disgust and a withdrawal or avoidance response. When the CS and US are linked, the taste of the food or fluid soon produces aversion
responses (the CR), even in the absence of physical illness (see Figure 6.8 ). This acquired dislike or disgust for a food or drink because it was paired with illness is known as conditioned taste aversion (Garcia et al., 1966).
Figure 6.8 Conditioned Taste Aversions Classical conditioning can account for the development of taste aversions. Falling ill after eating a particular food can result in conditioned feelings of disgust as well as withdrawal responses when you are later re-exposed to the taste, smell, or texture of the food. Conditioned taste aversions are another example of conditioning occurring even though the UR and the CR are not identical responses.
Conditioned taste aversions may develop in a variety of ways, such as through illness associated with food poisoning, the flu, medical procedures, or excessive intoxication. Importantly, these conditioned aversions only occur for the flavour of a particular food rather than to other stimuli that may have been present when you became ill. For example, if you were listening to a particular song while you got sick from eating tainted spinach or a two-week-old tuna sandwich, your aversion would develop to the taste of spinach, but not to the song that was playing. Thus, humans (and many other animals) are biologically prepared to
associate food, but not sound, with illness (Garcia et al., 1966).
Neuroimaging studies provide us with additional insights into conditioned taste aversions. These studies show responses in brain areas related to disgust and
emotional arousal (Yamamoto, 2007) as well as in brainstem regions related to vomiting (Reilly & Bornovalova, 2005; Yamamoto & Fujimoto, 1991). Additionally, neurons in reward centres in the brain show altered patterns of
activity to the food associated with illness (Yamamoto et al., 1989). These different brain responses suggest that illness triggers a strong emotional response that causes the reward centres to update their representation of the illness-causing food, thus making that food less rewarding.
Although these studies may explain how some aspects of conditioned taste aversions are maintained, there are still some riddles associated with this phenomenon. For instance, the onset of symptoms from food poisoning may not occur until several hours have passed after the tainted food or beverage was consumed. As a consequence, the interval between tasting the food (CS) and feeling sick (UR) may be a matter of hours, whereas most conditioning happens only if the CS, US, and the UR occur very closely to each other in time. Another peculiarity is that taste aversions are learned very quickly—a single CS–US pairing leading to illness is typically sufficient. These special characteristics of taste aversions are extremely important for survival. The flexibility offered by a long window of time separating food (CS) and the illness (UR), as well as the requirement for only a single exposure, raises the chances of acquiring an important aversion to the offending substance.
One potential explanation for these characteristics involves the food stimuli themselves. Usually, a conditioned taste aversion develops to something we have ingested that has an unfamiliar flavour. Such flavours stick out when they are experienced for the first time and are therefore much easier to remember, even after considerable time has passed. In contrast, if you have eaten the same ham and Swiss cheese sandwich at lunch for years, and you become ill one afternoon after eating it, you will be less prone to develop a conditioned taste
aversion. This scenario can be explained by latent inhibition, which occurs
when frequent experience with a stimulus before it is paired with a US makes it less likely that conditioning will occur after a single episode of illness (Lubow & Moore, 1959).
Conditioned taste aversions are a naturally occurring experience. However, conditioned emotional responses are also being created by advertisers to influence our responses. As you will read in the next section, food is not the only stimulus that can make you feel sick.
Working the Scientific Literacy Model Conditioning and Negative Political Advertising
Some politicians have charisma; you want to like them and believe what they say. Barack Obama (2009–2017) was treated like a rock star when he travelled internationally. Justin Trudeau (2016–) also seems rather well liked. But not everyone has natural charisma. In these cases, politicians need to use advertising and carefully constructed “photo ops” to create emotional responses that can influence voting behaviours. In an ideal world, these advertisements would focus on issues and would highlight the candidates’ positive qualities. Unfortunately, the last few decades have seen a dramatic upsurge in a different form of advertising: negative attack ads. In a three-month period during the 2008 U.S. presidential election, Republican John McCain and Democrat Barack Obama combined for 150,000
negative ads in “battleground states” (Nielsen Research, 2008). This type of advertisement relies on the principles of classical conditioning and, in the process, treats you, the voter, like one of Pavlov’s dogs.
What do we know about classical conditioning in negative political advertising? Negative political advertisements routinely include unflattering
images. In the next federal or provincial election, pay attention to the commercials that are sponsored by each party and you will notice a few tricks. First, many images of opponents will be black and white and of poor quality (grainy). This trick is designed to make viewers feel mildly frustrated when viewing the unclear photographs. Second, the images of the attacked politicians will include them expressing a negative emotion. In some, they will be yelling (angry faces trigger a physiological response in people). Others may show facial expressions that appear smug or that suggest the candidate feels contempt toward the person
they’re looking at (which, in this case, would appear to be you). The assumption underlying these attack ads is that if you pair a party leader with imagery that generates unpleasant emotions, then viewers will associate that leader with negative feelings and be less likely to vote for that party.
In this case, the CS would be the attacked politician. The US would be the negative imagery. The UR would be the negative emotional response to the imagery (or unflattering photograph). Eventually, the individuals who constructed the ad hope that simply seeing the attacked person will produce a negative emotional response (CR) along with the thought, “I will not vote for him or her.” The question is, “Does this work?”
How can science help explain the role of classical conditioning in negative political advertising? An attempt to use negative emotions to alter people’s opinions of political candidates is similar to a psychology research technique
known as evaluative conditioning. In an evaluative conditioning study, experimenters pair a stimulus (e.g., a shape) with either
positive or negative stimuli (e.g., an angry face; Murphy & Zajonc, 1993). The repeated association of a stimulus with an emotion leads participants to develop a positive or negative feeling toward that stimulus (depending on the emotional pairing;
see Figure 6.9 ). This is precisely what political strategists are
attempting to do when they show unpleasant pictures of an opponent and pair it with angry narrators and emotional labels.
Figure 6.9 Evaluative Conditioning
In evaluative conditioning, researchers pair an emotional image (e.g., an emotional face) with a previously neutral target image such as a Japanese symbol. The association that (sometimes) forms between the two images can influence participants’ later judgments of the target image, leading them to like (if paired with a happy face) or dislike (if paired with angry face) them more than if no conditioning had occurred. Political advertising sometimes uses similar, if less subtle, techniques.
REUTERS/Alamy Stock Photo
In the laboratory, evaluative conditioning works. This phenomenon has been found with visual, auditory, olfactory (smell), taste, and tactile (touch) stimuli. It has been used to alter
feelings toward objects ranging from snack foods (Lebens et al., 2011), to consumer brands (Walther & Grigoriadis, 2004), to novel shapes (Olson & Fazio, 2001). A number of studies have specifically attempted to use conditioning to create negative
attitudes toward products or behaviours (Moore et al., 1982; Zanna et al., 1970), a goal similar to the attack ads you see each election. For instance, Stuart and colleagues (1990) found that
associating a new brand of toothpaste with negative pictures decreased evaluations of that product. In all of these cases, the advertisers and sponsoring politicians are assuming that the viewer will associate the negative emotions (UR) with the ad’s target (CS) and that this will make the viewer more likely to select an alternative (i.e., the candidate sponsoring the attack ad). In the case of politics, this assumption makes sense—attack ads tend to be effective and are recalled better than other types of political
information (Fernandes, 2013).
Can we critically evaluate this information? A major question that arises from this research is whether producing a negative opinion of one option (be it a brand of toothpaste or a political candidate) automatically means that you also produce a positive opinion of the other option. Oftentimes, we can’t tell if the results are due to liking one option or disliking the other option. This question isn’t really an issue for U.S.-based studies, as there are only two parties in that country (for now). However, with five political parties running in the next federal election in Canada, there is a danger that attack ads might produce negative opinions of the target, but still not boost opinions of the party running the ads.
Recent research has examined who is actually influenced by these attack ads. In one U.S.-based study (none have been conducted in Canada), researchers found that negative ads had no effect on donations to political parties. They did, however,
increase voter turnout among partisans, people who already agreed with the views expressed in the ads (Barton et al., 2016). In other words, although the primary goal of attack ads might be to make undecided voters associate negative emotions with the target of the ads, the actual effect of the ads is to motivate people
who already had negative emotions to act on those emotions (i.e., to vote).
Of course, politicians also need to be careful not to overstep certain boundaries and inadvertently create sympathy for the target of the negative ads. In October 1993, the Progressive Conservative Party broadcast two television commercials that highlighted the partial facial paralysis of Liberal leader (and future Prime Minister) Jean Chrétien. One ad asked, “Is this a Prime Minister?” Another had a female narrator stating, “I personally would be embarrassed if he were to become the Prime Minister of Canada.” The goal of the commercials was not to attack Chrétien’s political credentials or experience, which far surpassed those of the other, less experienced, party leaders. Instead, the ads were designed to link the negative emotion associated with physical deformities, and any stigma associated with them, to the Liberal party so that people would feel uneasy about voting Liberal. It didn’t work: The public outcry in response to the commercials caused the Conservatives to withdraw the ads after only one day. Indeed, people who saw the ads were inclined to sympathize with Chrétien and feel anger toward Conservative
leader Kim Campbell (Haddock & Zanna, 1997). The Liberals won the election handily, with the Conservatives being reduced to two seats in the House of Commons.
Negative ads can backfire if the public views them as overly
personal or insensitive. Mocking Jean Chrétien’s facial paralysis led to a disastrous outcome for the Progressive Conservative party in the 1993 election. Allstar Picture Library/Alamy Stock Photo
Why is this relevant? Dozens of studies indicate that people are prone to a third-person effect whereby they assume that other people are more affected by advertising and mass media messages than they themselves
are (Cheng & Riffe, 2008; Perloff, 2002). Thus, there appears to be a disconnect between the power of negative advertising and people’s awareness of its effects. It is important to realize that conditioning often occurs without our conscious awareness. Our brains are designed to make associations; it’s how we learn. So, by becoming aware of how marketing companies and politicians are using classical conditioning to influence how you vote, you can try to reduce the effect of their manipulation. That way, when you cast your vote, it will hopefully be because of issues you care about and not because of conditioned emotional responses.
Incidentally, the type of evaluative conditioning that occurs with negative political advertising may also work with positive information if it is powerful enough. At the beginning of the 2015 federal election campaign, the Liberal Party was concerned that the much wealthier Conservatives would buy up all of the advertising time during sporting events. To prevent this, they booked some commercial time with sports networks just in case
the Blue Jays made the playoffs (Thibedeau, 2015). They did— and although they ended up losing in the second round, their dramatic first-round victory over the Texas Rangers brought the nation together. Millions of excited Jays fans (jumping up and down after José Bautista’s bat flip) got to see frequent commercials featuring Justin Trudeau.
Drug Tolerance and Conditioning
In addition to influencing overt behaviours such as salivating and emotional behaviours such as phobias, classical conditioning can influence how the body regulates its own responses to different stimuli. For example, classical conditioning can help explain some drug-related phenomena, such as cravings and tolerance. Cues that accompany drug use can become conditioned stimuli
that elicit cravings (Sinha, 2009). For example, a cigarette lighter, the smell of tobacco smoke, or the presence of another smoker can elicit cravings in people who smoke.
Conditioning can also influence drug tolerance, or a decreased reaction that
occurs with repeated use of the drug (Siegel et al., 2000). When a person takes a drug, his or her body attempts to metabolize that substance. Over time, the setting and paraphernalia associated with the drug-taking begin to serve as cues (a CS) that a drug (US) will soon be processed by the body (UR). As a result of this association, the physiological processes involved with metabolizing the drug will begin with the appearance of the CS rather than when the drug is actually consumed. In other words, because of conditioning, the body is already braced for the drug before the drug has been snorted, smoked, or injected. This response means that, over time, more of the drug will be needed to override these preparatory responses so that the desired effect can be obtained; this
change is referred to as conditioned drug tolerance.
This phenomenon can have fatal consequences for drug abusers. Shepard
Siegel (1984), a psychologist at McMaster University, conducted interviews with patients who were hospitalized for overdosing on heroin. Over the course of his interviews, a pattern among the patients emerged. Several individuals reported that they were in situations unlike those that typically preceded their heroin injections—for example, in a different environment or even using an injection site (i.e., part of the body) that differed from the usual ritual. As a result of these differences, there were fewer CSs present to trigger the CR, the body’s
metabolizing activity that braced (or prepared) the drug taker’s body for the arrival of the drug. Without this conditioned preparatory response, delivery of
even a normal dose of the drug can be lethal. This finding has been confirmed in animal studies: Siegel and his associates (1982) found that conditioned drug tolerance and overdosing can also occur with rats. When rats received heroin in an environment different from where they experienced the drug previously, mortality rates were double that of control rats that received the same dose of heroin in their normal surroundings (64% versus 32%).
The examples discussed in this module are only a few of the applications of
classical conditioning (Domjan et al., 2004). But, the fact that behaviours ranging from phobias, to voting preferences, to drug tolerance can be explained by classical conditioning shows us that Pavlov’s observations of his salivating dogs were really just a drop in the bucket.
Module 6.1c Quiz:
Applications of Classical Conditioning
Know . . . 1. Conditioning a response can take longer if the subject experiences the
conditioned stimulus repeatedly before it is actually paired with a US.
This phenomenon is known as . A. preparedness B. extinction C. latent inhibition D. acquisition
2. When a heroin user develops a routine, the needle can become the , whereas the body’s preparation for the drug in response to the presence of the needle is the .
A. CS; CR B. US; UR C. US; CR D. CS; US
Understand . . . 3. Why are humans biologically prepared to fear snakes and not guns?
A. Guns kill fewer people than do snakes. B. Guns are a more recent addition to our evolutionary history. C. Snakes are more predictable than guns. D. Guns are not a natural phenomenon, whereas snakes do occur in
nature.
Apply . . . 4. A television advertisement for beer shows young people at the beach
drinking and having fun. Based on classical conditioning principles, the advertisers are hoping you will buy their beer because the commercial elicits
A. a conditioned emotional response of pleasure. B. a conditioned emotional response of fear. C. humans’ natural preparedness toward alcohol consumption. D. a taste aversion to other companies’ beers.
Module 6.1 Summary
acquisition
classical conditioning (Pavlovian conditioning)
conditioned emotional response
conditioned response (CR)
conditioned stimulus (CS)
conditioned taste aversion
discrimination
extinction
Know . . . the key terminology involved in classical conditioning.6.1a
generalization
latent inhibition
learning
preparedness
spontaneous recovery
unconditioned response (UR)
unconditioned stimulus (US)
Acquisition of a conditioned response occurs with repeated pairings of the CS and the US. Once a response is acquired, it can be extinguished if the CS and the US no longer occur together. During extinction, the CR diminishes, although it may reappear under some circumstances. For example, if enough time passes following extinction, the CR may spontaneously recover when the organism encounters the CS again.
Not all stimuli have the same potential to become a strong CS. Responses to biologically relevant stimuli, such as snakes, are more easily conditioned than are responses to stimuli such as flowers or guns, for example. Similarly, avoidance of potentially harmful foods is critical to survival, so organisms can develop a conditioned taste aversion quickly (in a single trial) and even when ingestion and illness are separated by a relatively long time interval.
Apply Activity
Understand . . . how responses learned through classical conditioning can be acquired and lost.
6.1b
Understand . . . the role of biological and evolutionary factors in classical conditioning.
6.1c
Apply . . . the concepts and terms of classical conditioning to new examples.
6.1d
Read the three scenarios that follow and identify the conditioned stimulus (CS), the unconditioned stimulus (US), the conditioned response (CR), and the
unconditioned response (UR) in each case. (Hint: When you apply the terms CS, US, CR, and UR, a good strategy is to identify whether something is a stimulus (something that elicits) or a response (a behaviour). Next, identify whether the stimulus automatically elicits a response (the US) or does so only after being paired with a US (a CS). Finally, identify whether the response occurs in response to the US alone (the UR) or the CS alone (the CR).)
1. Cameron and Tia went to the prom together. During their last slow dance, the DJ played the theme song for the event. During the song, the couple kissed. Now, several years later, whenever Cameron and Tia hear the song, they feel a rush of excitement.
2. Harry has visited his eye doctor several times due to problems with his vision. One test involves blowing a puff of air into his eye. After repeated visits to the eye doctor, Harry starts blinking as soon as the doctor begins to prepare the instrument.
3. Sarah went to a new restaurant and experienced the most delicious meal she had ever tasted. The restaurant began advertising on the radio, and now every time an ad comes on, Sarah finds herself craving the meal she enjoyed so much.
Negative political advertising often uses a form of conditioning known as evaluative conditioning. Negative images, sounds, and/or statements are paired with images of the targeted candidate. The goal is to have viewers link negative emotions with the target. Research has found that this technique can be successful. But, if the images used are deemed cruel or inappropriate, it is possible that viewers will feel negative emotions toward the sponsor of the ad instead.
Analyze . . . the use of negative political advertising to condition emotional responses to candidates.
6.1e
Module 6.2 Operant Conditioning: Learning through Consequences
Mike Mergen/Bloomberg via Getty Images
Learning Objectives
Know . . . the key terminology associated with operant conditioning. Understand . . . the role that consequences play in increasing or decreasing behaviour. Understand . . . how schedules of reinforcement affect behaviour.
6.2a 6.2b
6.2c
Gambling is a multibillion-dollar industry in Canada. According to Statistics Canada, the net revenue from lotteries, video-lottery terminals (VLTs), and casinos was $13.74 billion in 2011. That’s an average of $515 per person. Given these huge sums, it is clear that some individuals are spending more than they should on this habit. Psychologists and government officials have invested a considerable amount of time into the development of prevention and treatment programs for gambling addictions. Although these programs have led to addiction rates levelling off in recent years, compulsive gambling is still a problem in Canada. So, what compels people to keep pulling the lever on a slot machine or pressing buttons on a VLT screen when logic would tell them to stop and go home?
Although the answer to this question is complicated (Hodgins et al., 2011), it is clear that reinforcement plays a role in these behaviours. As you will read in this module, rewarding a behaviour—which happens when someone wins money after pressing the button on a VLT—makes that behaviour more likely to occur again in the future. The effect is larger when the reward doesn’t happen every time and isn’t predictable— qualities that perfectly describe gambling. The machines aren’t the only ones having their buttons pushed.
Focus Questions
1. How do the consequences of our actions—such as winning or losing a bet—affect subsequent behaviour?
2. Many behaviours, including gambling, are reinforced only part of the time. How do the odds of being reinforced affect how often a behaviour occurs?
Apply . . . your knowledge of operant conditioning to examples. Analyze . . . the effectiveness of punishment on changing behaviour.
6.2d 6.2e
Very few of our behaviours are random. Instead, people tend to repeat actions that previously led to positive or rewarding outcomes. If you go to a new restaurant and like it, you will eat there again. Conversely, if a behaviour previously led to a negative outcome, people are less likely to perform that action again. If you go to a new restaurant and don’t enjoy the meal, then you will likely not eat there again. These types of stimulus-response relationships are known
as operant conditioning , a type of learning in which behaviour is influenced by consequences. The term operant is used because the individual operates on the environment before consequences can occur. In contrast to classical
conditioning, which typically affects reflexive responses, operant conditioning involves voluntary actions such as speaking or listening, starting and stopping an activity, and moving toward or away from something. Whether and when we engage in these types of behaviours depend on how our unique collection of previous experiences has influenced what we do and do not find rewarding.
Initially, the difference between classical and operant conditioning may seem unclear. One useful way of telling the difference is that in classical conditioning a
response is not required for a reward (or unconditioned stimulus) to be presented; to return to Pavlov’s dogs, meat powder was presented regardless of whether salivation occurred. In classical conditioning, learning has taken place if a conditioned response develops following pairings of the conditioned stimulus and the unconditioned stimulus. In other words, the dogs learned the association between the sound of a metronome and food (as shown by their salivation), but
they didn’t have to actually do anything. In operant conditioning, a response and a consequence are required for learning to take place. Without a response of
some kind, there can be no consequence. See Table 6.1 for a summary of differences between operant and classical conditioning.
Table 6.1 Major Differences between Classical and Operant Conditioning
Classical Conditioning Operant Conditioning
Target response is . . . Automatic Voluntary
Reinforcement is . . . Present regardless of whether a
response occurs
A consequence of the
behaviour
Behaviour mostly
depends on . . .
Reflexive and physiological
responses
Skeletal muscles
Basic Principles of Operant Conditioning
The concept of contingency is important to understanding operant conditioning; it simply means that a consequence depends upon an action. Earning good grades is generally contingent upon studying effectively. Excelling at athletics is contingent upon training and practice. The consequences of a particular
behaviour can be either reinforcing or punishing (see Figure 6.10 ).
Figure 6.10 Reinforcement and Punishment The key distinction between reinforcement and punishment is that reinforcers, no matter what they are, increase behaviour. Punishment involves a decrease in behaviour, regardless of what the specific punisher may be. Thus both reinforcement and punishment are defined based on their effects on behaviour.
Reinforcement and Punishment
Reinforcement is a process in which an event or reward that follows a response increases the likelihood of that response occurring again. We can trace the scientific study of reinforcement’s effects on behaviour back to Edward Thorndike, who conducted experiments in which he measured the time it took
cats to learn how to escape from puzzle boxes (see Figure 6.11 ). Thorndike (1905) observed that over repeated trials, cats were able to escape more rapidly because they learned which responses worked (such as pressing a pedal on the
floor of the box). From his experiments, Thorndike proposed the law of effect —the idea that responses followed by satisfaction will occur again in the same situation whereas those that are not followed by satisfaction become less likely. In this definition, “satisfaction” implies either that the animal’s desired goal was achieved (e.g., escaping the puzzle box) or it received some form of reward for the behaviour (e.g., food).
Figure 6.11 Thorndike’s Puzzle Box and the Law of Effect (a) Thorndike conducted experiments in which cats learned an operant response that was reinforced with escape from the box and access to a food reward. (b) Over repeated trials, the cats took progressively less time to escape, as shown in this learning curve.
Within a few decades of the publication of Thorndike’s work, the famous behaviourist B. F. Skinner began conducting his own studies on the systematic relationship between reinforcement and behaviour. Although operant conditioning can explain many human behaviours, most of its basic principles stem from laboratory studies conducted on nonhuman species such as pigeons
or rats, which were placed in an apparatus such as the one pictured in Figure 6.12 . These operant chambers, sometimes referred to as Skinner boxes, include a lever or key that the subject can manipulate. Pushing the lever may result in the delivery of a reinforcer such as food. In operant conditioning terms, a reinforcer is a stimulus that is contingent upon a response and that increases the probability of that response occurring again. (So, a reinforcer would be a stimulus like food, whereas reinforcement would be the changes in the frequency
of a behaviour like lever-pressing that occur as a result of the food reward.) Researchers use machinery such as operant chambers to help them control and quantify learning. Specifically, researchers record an animal’s rate of responding over time (a measure of learning), and typically set a criterion for the number of responses that must be made before a reinforcer becomes available. As you will read later in this module, animals and humans are quite sensitive to how many responses they must make, or how long they must wait, in order to receive a reward.
Figure 6.12 An Operant Chamber The operant chamber is a standard laboratory apparatus for studying operant conditioning. The rat can press the lever to receive a reinforcer such as food or water. The lights can be used to indicate when lever pressing will be rewarded. The recording device measures cumulative responses (lever presses) over time.
Source: Lilienfeld, Scott O.; Lynn, Steven J; Namy, Laura L.; Woolf, Nancy J., Psychology: From Inquiry to Understanding,
2nd Ed., © 2011. Reprinted and electronically reproduced by permission of Pearson Education, Inc., New York, NY.
The discussion thus far has focused on how reinforcement can lead to increased responding; but, decreased responding is also a possible outcome of an
encounter with a stimulus. Punishment is a process that decreases the future probability of a response. Thus, a punisher is a stimulus that is contingent upon a response, and that results in a decrease in behaviour. Like reinforcers, punishers are defined not based on the stimuli themselves, but rather on their effects on behaviour. In all cases, a punisher—be it yelling, losing money, or going to jail—will make it less likely that a particular response will occur again.
Positive and Negative Reinforcement and
Punishment
Thus far, we have differentiated between reinforcement (when a response increases the likelihood that a behaviour will occur again) and punishment (when a response decreases the likelihood that a behaviour will occur again). In both of these cases, it is natural to think of the responses as something that is added to the situation. For instance, a behaviour could be reinforced by giving the animal food. Or, it could be punished by shocking the animal. But, both reinforcement
and punishment can be accomplished by removing a stimulus as well. In the descriptions that follow, try to remember the following four terms as they are used in operant conditioning:
Reinforcement: this increases the chances of a behaviour occurring again Punishment: this decreases the chances of a behaviour occurring again Positive: this means that a stimulus is added to a situation; positive can refer to reinforcement or punishment
Negative: this means that a stimulus is removed from a situation; negative can refer to reinforcement or punishment
These terms can be combined to produce four different subtypes of operant
conditioning. For instance, a response can be strengthened because it brings a
reward. This form of reinforcement, positive reinforcement , is the strengthening of behaviour after potential reinforcers such as praise, money, or nourishment follow that behaviour (see Table 6.2 ). For example, if you laugh at your professor’s jokes, the praise will serve as a reward; this will increase the likelihood that your professor will tell more jokes. (Remember: the “positive” in
positive reinforcement indicates the addition of a reward.) Positive reinforcement can be a highly effective method of rewarding desired behaviours among humans and other species.
Table 6.2 Distinguishing Types of Reinforcement and Punishment
Consequence Effect on
Behaviour
Example
Positive
reinforcement
Stimulus is
added or
increased.
Increases
the
response
A child gets an allowance for making
her bed, so she is likely to do it again
in the future.
Negative
reinforcement
Stimulus is
removed or
decreased.
Increases
the
response
The rain no longer falls on you after
opening your umbrella, so you are
likely to do it again in the future.
Positive
punishment
Stimulus is
added or
increased.
Decreases
the
response
A pet owner scolds his dog for
jumping up on a house guest, and
now the dog is less likely to do it
again.
Negative
punishment
Stimulus is
removed or
decreased.
Decreases
the
response
A parent takes away TV privileges to
stop the children from fighting.
Behaviour can also be reinforced by the removal of something that is unpleasant.
This form of reinforcement, negative reinforcement , involves the
strengthening of a behaviour because it removes or diminishes a stimulus (Table 6.2 ). For instance, taking aspirin is negatively reinforced because doing so removes a painful headache. Similarly, studying in order to prevent nagging from parents is also a form of reinforcement as the behaviour, studying, will increase.
Negative reinforcement is a concept that students frequently find confusing because it seems unusual that something aversive could be involved in the context of reinforcement. Recall that reinforcement (whether positive or negative) always involves an increase in the strength or frequency of responding. Also remember that the term “positive” in this context simply means that a stimulus is introduced or increased, whereas the term “negative” means that a stimulus has been reduced or avoided.
But, not all types of negative reinforcement are the same; in fact, negative
reinforcement can be further classified into two subcategories. Avoidance learning is a specific type of negative reinforcement that removes the possibility that a stimulus will occur. Examples of avoidance learning include leaving a sporting event early to avoid crowds and traffic congestion, and paying bills on time to avoid late fees. In these cases, negative situations are avoided. Escape learning , on the other hand, occurs if a response removes a stimulus that is already present. Covering your ears upon hearing overwhelmingly loud music is one example. You cannot avoid the music, because it is already present, so you perform a specific behaviour (covering your ears) to escape the aversive stimulus instead. The responses of paying bills on time to avoid late fees and covering your ears to escape loud music both increase in frequency because they have effectively prevented or removed the aversive stimuli.
In the laboratory, operant chambers such as the one pictured in Figure 6.12 often come equipped with a grid metal floor that can be used to deliver a mild electric shock; responses that remove (escape learning) or prevent (avoidance learning) the shock are negatively reinforced. This highly controlled environment allows researchers to carefully monitor all aspects of an animal’s environment while investigating the different contingencies that will cause a behaviour to increase or decrease in frequency.
As with reinforcement, various types of punishment are possible. Positive punishment is a process in which a behaviour decreases in frequency because it was followed by a particular, usually unpleasant, stimulus (Table 6.2 ). For example, some cat owners use a spray bottle to squirt water when the cat hops on the kitchen counter or scratches the furniture. Remember that the term “positive” simply means that a stimulus is added to the situation (i.e., no one is claiming that spraying a cat with water is an emotionally positive experience). In these cases, the stimuli are punishers because they decrease the frequency of a behaviour.
Finally, negative punishment occurs when a behaviour decreases because it removes or diminishes a particular stimulus (Table 6.2 ). Withholding someone’s privileges as a result of an undesirable behaviour is an example of negative punishment. A parent who “grounds” a child does so because this action removes something of value to the child. If effective, the outcome of the grounding will be to decrease the behaviour that got the child into trouble.
Shaping
Although these different forms of reinforcement and punishment make sense in theory, researchers (and parents) have an additional challenge: How do you get animals (or children) to perform the behaviour that you want to reinforce? Rats placed in operant chambers do not automatically go straight for the lever and begin pressing it to obtain food rewards. Instead, they must first learn that lever pressing accomplishes something. Getting a rat to press a lever can be done by
reinforcing behaviours that approximate (or lead up to) lever pressing, such as standing up, facing the lever, standing while facing the lever, placing paws upon
the lever, and pressing downward. This process of reinforcing successive approximations of a specific operant response is known as shaping . Shaping is done in a step-by-step fashion until the desired response—in this case, lever pressing—is learned. These techniques can also be used to help people develop
specific skill sets (e.g., toilet training). A similar process, chaining, involves linking together two or more shaped behaviours into a more complex action or sequence of actions. When you see an animal “acting” in a movie, its behaviours were almost certainly learned through lengthy shaping and chaining procedures.
Applications of shaping. Reinforcement can be used to shape complex chains of behaviour in animals and humans. (Later attempts to teach the cat to use a bidet were less successful.) Bork/Shutterstock
Applying Operant Conditioning
It is important to remember that although most studies of operant learning have involved animals, the principles derived from these studies apply to humans as well. In fact, they are found in many different areas of our lives ranging from work and school to interpersonal relationships. For example, the operant conditioning principles that we’ve reviewed thus far serve as the basis for an educational
method called applied behaviour analysis (ABA), which involves using close
observation, prompting, and reinforcement to teach behaviours, often to people who experience difficulties and challenges owing to a developmental condition such as autism (Granpeesheh et al., 2009). People with autism are typically nonresponsive to normal social cues from a very early age. This impairment can lead to a deficit in developing many skills, ranging from basic, everyday ones to complex skills such as language. For example, explaining how to clear dishes from the dinner table to a child with autism could prove difficult. Psychologists who specialize in ABA often shape the desired behaviour using prompts (such as asking the child to stand up, gather silverware, stack plates, and so on) and verbal rewards as each step is completed. These and more elaborate ABA techniques can be used to shape a remarkable variety of behaviours to improve the independence and quality of life for people with autism.
Module 6.2a Quiz:
Principles of Operant Conditioning
Know . . . 1. removes the immediate effects of an aversive stimulus, whereas
removes the possibility of an aversive stimulus from occurring in the first place.
A. Avoidance learning; escape learning B. Positive reinforcement; positive punishment C. Negative reinforcement; negative punishment D. Escape learning; avoidance learning
Understand . . . 2. When children misbehave, they are sometimes told to go to their room.
As a result, they no longer get to play with their friends or siblings. How does this consequence affect children’s behaviour?
A. It adds a stimulus in order to decrease bad behaviour. B. It takes away a stimulus in order to decrease bad behaviour. C. It adds a stimulus in order to increase bad behaviour. D. It takes away a stimulus in order to increase bad behaviour.
Apply . . . 3. Lucy hands all of her homework in to her psychology professor on time
because she does not want to lose points for late work. This is an
example of . A. negative reinforcement B. positive reinforcement C. negative punishment D. positive punishment
Processes of Operant Conditioning
In the previous section, you read about how the frequency of a behaviour can be increased (reinforcement) or decreased (punishment) by a number of different stimuli or responses. The obvious question, then, is why do some stimuli affect behaviour while others have no influence whatsoever? Is there a biological explanation for this difference?
Primary and Secondary Reinforcers
Reinforcers can come in two main forms. Primary reinforcers consist of reinforcing stimuli that satisfy basic motivational needs—needs that affect an individual’s ability to survive (and, if possible, reproduce). Examples of these inherently reinforcing stimuli include food, water, shelter, and sexual contact. In
contrast, secondary reinforcers consist of stimuli that acquire their reinforcing effects only after we learn that they have value. Money and Facebook “likes” are both examples of secondary reinforcers. They are more abstract and
do not directly influence survival-related behaviours.
Both primary and secondary reinforcers satisfy our drives, but what underlies the motivation to seek out these reinforcers? The answer is complex, but research
points to a specific brain circuit including a structure called the nucleus accumbens (see Figure 6.13 ). The nucleus accumbens becomes activated during the processing of all kinds of rewards, including primary ones such as
eating and having sex, as well as “artificial” rewards such as using cocaine and smoking a cigarette. Variations in this area might also account for why individuals differ so much in their drive for reinforcers. For example, scientists have discovered that people who are prone to risky behaviours such as gambling and alcohol abuse are more likely to have inherited particular copies of genes that code for dopamine and other reward-based chemicals in the brain
(Comings & Blum, 2000). Researchers have also found that individuals who are impulsive, and therefore vulnerable to gambling and drug abuse, release more dopamine in brain areas related to reward, and have trouble removing dopamine
from the synapses in these areas (Buckholtz et al., 2010).
Figure 6.13 Reward Processing in the Brain The nucleus accumbens is one of the brain’s primary reward centres.
Animals pressing levers in operant chambers to receive rewards may seem artificial. However, if you look around you will see that our environment is full of devices that influence our operant responses. Top: RisingStar/Alamy Stock Photo; bottom: Richard Goldberg/Shutterstock
Secondary reinforcers also trigger the release of dopamine in reward areas of the brain. A number of neuroimaging experiments have shown that monetary
rewards cause dopamine to be released in parts of the basal ganglia (Elliott et al., 2000) as well as in the medial regions of the frontal lobes (Knutson et al.,
2003). Some of these areas directly overlap with those involved with primary reinforcers (Valentin & O’Doherty, 2009).
How can dopamine be related to operant conditioning? When a behaviour is
rewarded for the first time, dopamine is released (Schultz & Dickinson, 2000); this reinforces these new, reward-producing behaviours so that they will be
performed again (Morris et al., 2006; Schultz, 1998). These dopamine- releasing neurons in the nucleus accumbens and surrounding areas help maintain a record of which behaviours are, and are not, associated with a reward. Interestingly, these neurons alter their rate of firing when you have to update your understanding of which actions lead to rewards; so, they are
involved with learning new behaviour–reward associations as well as with reinforcement itself.
Discrimination and Generalization
Once a response has been learned, the individual may soon learn that reinforcement or punishment will occur under only certain conditions and circumstances. A pigeon in an operant chamber may learn that pecking is reinforced only when the chamber’s light is switched on, so there is no need to continue pecking when the light is turned off. This illustrates the concept of a discriminative stimulus —a cue or event that indicates that a response, if made, will be reinforced. Our lives are filled with discriminative stimuli. Before we pour a cup of coffee, we might check whether the light on the coffee maker is on —a discriminative stimulus that tells us the beverage will be hot and, presumably, reinforcing. There are also numerous social examples of discriminative stimuli. For instance, you might only ask to borrow your parents’ car when they show signs of being in a good mood. In this case, your parents’ mood (smiling, laughing, etc.) will dictate whether you perform a behaviour (asking to borrow the car). Discriminative stimuli demonstrate that we (and animal subjects) can use cues from our environment to help us decide whether to perform a conditioned behaviour.
The idea of a discriminative stimulus should not be confused with the concept of
discrimination. Discrimination occurs when an organism learns to respond to
one original stimulus but not to new stimuli that may be similar to the original stimulus. For example, a pigeon may learn that he will receive a reward if he pecks at a key after a 1000-Hz tone, but not if he performs the same action following a 2000-Hz tone. As a result, he won’t peck at the key after a 2000-Hz tone. Or, to extend our earlier example, you may quickly learn that your father will lend you the car whereas your mother will not. In this case, the process of discrimination would lead you to perform a behaviour (asking to borrow the car) when you are with your father but not when you are with your mother.
In contrast to discrimination, generalization takes place when an operant response occurs in response to a new stimulus that is similar to the stimulus present during original learning. In this case, a pigeon who learned to peck a key after hearing a 1000-Hz tone may attempt to peck the key whenever any tone is presented. If petting a neighbour’s border collie (a type of dog) led to a child laughing and playing with the animal, then he might be more likely to pet other dogs or even other furry animals. In this instance, a specific reinforcement
related to an action (petting a specific dog) led to a similar behaviour (petting) occurring in other instances (petting other dogs).
If you’ve noticed similarities between discrimination and generalization in operant
conditioning and the same processes in classical conditioning (see Module 6.1 ), you are not mistaken. The same general logic underlies these concepts in both types of conditioning. However, while discrimination and generalization in classical conditioning were due to the strengthening of synapses as a result of simultaneous firing, in operant conditioning, the mechanism appears to be dopamine-secreting neurons.
Delayed Reinforcement and Extinction
The focus of this module thus far has been on behavioural and biological responses to reinforcement and punishment. In most studies exploring these responses, the reward or punishment occurred immediately following the
behaviour. This allows individuals to predict when a reward will occur (Schultz & Dickinson, 2000). But, you know from your own life that rewards are not always immediate. What happens if the reward is delayed, or doesn’t occur at all? As
early as 1911, Thorndike (the cat imprisoner) noted that reinforcement was more effective if there was very little time between the action and the consequence. Indeed, in a study with pigeons, researchers found that the frequency of responses (pecking a button) decreased as the amount of time between the
pecking and the reward (a food pellet) increased (Chung & Herrnstein, 1967). Interestingly, neuroscientists have found that neural activity decreases during this time as well. In fact, delays of as little as half a second decrease the amount
of neural activity in dopamine-releasing neurons (Hollerman & Schultz, 1996).
This effect of delayed reinforcement influences a number of human behaviours as well. For instance, drugs that have their effect (i.e., produce their rewarding feeling) soon after they are taken are generally more addictive than drugs whose effects occur several minutes or hours after being taken. This difference is due, in part, to the ease with which one can mentally associate the action of taking the drug with reinforcement from the drug (the consequence).
Sometimes, however, a reinforcer is not just delayed; it doesn’t occur at all. A pigeon may find that pressing a key in its operant chamber no longer leads to a food reward. You may find that your parents no longer let you borrow the car no matter how nicely you ask. Although both you and the pigeon may persist in your behaviour for a while, eventually you’ll stop. This change is known as extinction , the weakening of an operant response when reinforcement is no longer available. If you lose your Internet connection, for example, you will probably stop trying to refresh your web browser because there is no reinforcement for doing so—the behaviour will no longer be performed. Extinction, like most of the observable behaviours you’ve read about in this module, is related to dopamine. If you expect a reward for your behaviour and
none comes, the amount of dopamine being released decreases (Schultz, 1998). Dopamine release will increase again when there is a new behaviour– reward relationship to learn.
Injecting drugs allows them to enter the bloodstream and therefore the brain more quickly than if they are taken orally. This is one reason why injected drugs are often more addictive than pills. Victoria M/Fotolia
Table 6.3 differentiates among the processes of extinction, generalization, and discrimination in classical and operant conditioning.
Table 6.3 Comparing Discrimination, Generalization, and Extinction in Classical and Operant Conditioning
Process Classical Conditioning Operant Conditioning
Discrimination A CR does not occur in
response to a different CS
that resembles the original
CS.
There is no response to a stimulus
that resembles the original
discriminative stimulus used during
learning.
Generalization A different CS that
resembles the original CS
used during acquisition
elicits a CR.
Responding occurs to a stimulus that
resembles the original discriminative
stimulus used during learning.
Extinction A CS is presented without a
US until the CR no longer
occurs.
Responding gradually ceases if
reinforcement is no longer available.
Reward Devaluation
In all of these examples of operant conditioning, the value of the reinforcement remained the same. But, if you think about your own life it quickly becomes apparent that this is not always the case. Food is incredibly rewarding when you are hungry but becomes less so after you have eaten a large meal. Similarly, $100 may seem like a lot of money to a starving student, but would seem less important to a doctor with a high income. If a behaviour is more likely to occur because of reward, what happens when the reward becomes less rewarding?
Scientists have found that behaviours do change when the reinforcer loses some
of its appeal (Colwill & Rescorla, 1985, 1990). In a typical experiment, rats are trained to press two different levers, each associated with a different reward (e.g., two different rewarding tastes). If the experimenters pre-feed the animal with one of these two tastes, they will crave it less than the other; in other words, its reward will be devalued compared to the other taste. Researchers consistently find a decrease in the response rate for the “devalued” reward, whereas the other reward remains largely unaffected.
Reward devaluation can also occur by making one of the rewards less appealing. In this version of reward devaluation, one of the reinforcing tastes is paired with a toxin that made the rats feel ill; this obviously reduces its value! (Ideally, this pairing would occur outside of the operant chamber so that the toxin didn’t serve as a positive punishment.) The rats would then have the choice of two levers to press, one associated with a rewarding taste and the other associated with the taste that is now less rewarding than before. When these rats were later given the opportunity to choose between the two operant learning tasks, they showed a strong preference for the task whose reward had not been
devalued (Colwill & Rescorla, 1985, 1990).
Module 6.2b Quiz:
Processes of Operant Conditioning
Know . . . 1. A basic need such as food may be used as a reinforcer,
whereas a stimulus whose value must be learned is a reinforcer.
A. primary; continuous B. secondary; shaping C. primary; secondary D. continuous; secondary
Understand . . . 2. The difference between a discriminative stimuli and discrimination (as it
applies to operant conditioning) is that
A. discrimination tells you when behaviours could be reinforced whereas discriminative stimuli involve an animal responding to some stimuli but not others.
B. discriminative stimuli are used only in animal research (which involve simple cues) where discrimination occurs in psychological studies involving human participants.
C. discriminative stimuli can only affect behaviour after the process of discrimination has taken place.
D. a discriminative stimulus tells you when behaviours could be reinforced whereas discrimination involves responding to some stimuli but not others.
Apply . . . 3. Jack’s mother rewarded him for cleaning his messy room by baking him
cookies. As a result, Jack cleaned his room every week. However, after few months, Jack’s mother stopped rewarding his cleaning behaviour. As a result, Jack didn’t clean his room very often. This is an example of
.
A. extinction B. reward devaluation C. discrimination D. Skinner’s paradox
4. Jennifer used to love both tequila and vodka (although not mixed together). One night, she drank so much tequila that she felt sick. At a house party the next week, she avoided tequila and drank vodka instead.
This is an example of . A. extinction B. reward devaluation C. discrimination D. positive reinforcement
Reinforcement Schedules and Operant Conditioning
Think about the last time you did something nice for a friend. How did he or she respond? You may have received a hug. She may have said “Thanks!” and smiled. Regardless, you likely received some positive feedback that made you feel like your behaviour was worth repeating. Now think about the last time you played a sport or a video game. Not every shot would have hit the target, so your
behaviour wasn’t reinforced each time. But, it was likely reinforced some of the time. These real-world examples show you that some behaviours are reinforced more consistently than others. The question that interested psychologists was “How do these different patterns of reinforcement affect learning?
Schedules of Reinforcement
Operant conditioning occurs, intentionally or unintentionally, in many different areas of our lives. However, the exact timing of the action and reinforcement (or punishment) differs across situations. Typically, a given behaviour is rewarded
according to some kind of schedule. These schedules of reinforcement —rules that determine when reinforcement is available—can have a dramatic effect on both the learning and unlearning of responses (Ferster & Skinner, 1957). Reinforcement may be available at highly predictable or very irregular times. Also, reinforcement may be based on how often someone engages in a behaviour, or on the passage of time.
During continuous reinforcement , every response made results in reinforcement. As a result, learning initially occurs rapidly. For example, vending machines (should) deliver a snack every time the correct amount of money is deposited. In other situations, not every action will lead to reinforcement; we also encounter situations where reinforcement is available only some of the time. For example, phoning a friend may not always get you an actual person on the other
end of the call. In this kind of partial (intermittent) reinforcement , only a certain number of responses are rewarded, or a certain amount of time must pass before reinforcement is available. Four types of partial reinforcement schedules are possible (see Figure 6.14 ). These schedules have different effects on rates of responding.
Figure 6.14 Schedules of Reinforcement (a) Four types of reinforcement schedule are shown here: fixed ratio, variable ratio, fixed interval, and variable interval. Notice how each schedule differs based on when reinforcement is available (interval schedules) and on how many responses are required for reinforcement (ratio schedules). (b) These schedules of reinforcement affect responding in different ways. For example, notice the vigorous responding that is characteristic of the variable ratio schedule, as indicated by the steep upward trajectory of responding. (c) Real-world examples of the four types of reinforcement schedules. Photos: bottom left: Li jianbin/Imaginechina/AP Images; bottom centre left: Lightreign/Alamy Stock Photo; bottom centre right:
Andresr/ Shutterstock; bottom right: Bill Fehr/Shutterstock
Source: Lilienfeld, Scott O.; Lynn, Steven J; Namy, Laura L.; Woolf, Nancy J., Psychology: From Inquiry to Understanding,
2nd Ed., © 2011. Reprinted and electronically reproduced by permission of Pearson Education, Inc., New York, NY.
In the descriptions that follow, try to remember the following four terms as they are used in operant conditioning:
Ratio schedule: This means that the reinforcements are based on the amount of responding. Interval schedule: This means that the reinforcements are based on the amount of time between reinforcements, not the number of responses an animal (or human) makes.
Fixed schedule: This means that the schedule of reinforcement remains the same over time.
Variable schedule: This means that the schedule of reinforcement, although linked to an average (e.g., 10 lever presses or 10 seconds), varies from reinforcement to reinforcement.
Keeping these distinctions in mind should help you make sense of the four different reinforcement schedules discussed below.
In a fixed-ratio schedule , reinforcement is delivered after a specific number of responses have been completed. For example, a rat may be required to press
a lever 10 times to receive food. Similarly, a worker in a factory may get paid based on how many items she worked on (e.g., receiving $1 for every five items produced). In both cases, a certain number of responses is required before a reward is given.
In a variable-ratio schedule , the number of responses required to receive reinforcement varies according to an average. A VR5 (variable ratio with an average of five trials between reinforcements) could include trials that require seven lever presses for a reward to occur, followed by four, then six, then three, and so on. But, the average number of responses required to receive reinforcement would be five. Slot machines at casinos operate on variable-ratio reinforcement schedules. The odds are that the slot machine will not give anything back, but sometimes a player will win a small amount of money. Of course, hitting the jackpot is very infrequent. The variable nature of the reward structure for playing slot machines helps explain why responding on this schedule can be vigorous and persistent. Slot machines and other games of
chance hold out the possibility that at some point players will be rewarded, but it is unclear how many responses will be required before the reward occurs. The
fact that the reinforcement is due to the number of times a player responds promotes strong response levels (i.e., more button presses or lever pulls on a slot machine). In animal studies, variable-ratio schedules lead to the highest rate of responding of the four types of reinforcement schedules.
PSYCH@ Never Use Multiline Slot Machines When casinos first became popular in the middle of the 20th century, people who used slot machines would pull a lever. Wheels with different images or numbers would spin around; if the correct combination of numbers appeared, the player would win a reward (often paired with loud noises and hundreds of coins being dispensed). In modern casinos, the slot machines are computerized. This technology has allowed game designers to add a sinister trick to slot machines: It is now possible for players to bet on several lines (rows) of numbers rather than on just one.
These multiline slot machines therefore allow the player to make multiple bets on each “spin.” On the surface, this doesn’t seem alarming. But,
these machines are using operant conditioning against players. For each line that a player bets on, he or she has to insert money into the machine. So, if a player is betting on nine lines, he would put $9 into the machine. Then the machine “spins” so that the numbers and symbols on each line change. On many of these spins, the player will win, a result that is paired with rewarding celebratory sound effects as well as money. However, the “win” will be for less money than the original total bet (e.g.,
winning $5 after putting $9 into the machine). In other words, it is a loss that is disguised as a win (Dixon et al., 2010). In an interview, one game designer wrote, “[W]e give them a sense of winning but also continue to
accrue [their] credits” (Dow Schull, 2012, p. 121). Indeed, gambling researchers at the University of Waterloo have worked out the mathematics for these slot machines and found that players will double their bets only 20% of the time and will win 10x their initial bet (viewed as
a “big win” by gamblers) less than 1% of the time (Harrigan et al., 2014). And yet, due to the little rewards on each trial—the losses disguised as wins—gamblers continue to press the buttons. The house always wins in the long run.
Multiline video slot machines allow a player to bet on more than one line of numbers and symbols at a time. However, the small “wins” that players experience are often smaller than their overall losses.
frans lemmens/Alamy Stock Photo
In contrast to ratio schedules, interval schedules are based on the passage of
time, not the number of responses. A fixed-interval schedule reinforces the first response occurring after a set amount of time passes. If your psychology professor gives you an exam every four weeks, your reinforcement for studying
is on a fixed-interval schedule. In Figure 6.14 , notice how the fixed-interval schedule shows that responding drops off after each reinforcement is delivered (as indicated by the tick marks). However, responding increases because reinforcement is soon available again. This schedule may reflect how you devote time to studying for your next exam—studying time tends to decrease after an exam, and then builds up again as another test looms.
The final reinforcement schedule is the variable-interval schedule , in which the first response is reinforced following a variable amount of time. The time interval varies around an average. For example, if you were watching the nighttime sky during a meteor shower, you would be rewarded for looking upward at irregular times. A meteor may fall on average every 5 minutes, but there will be times of inactivity for a minute, 10 minutes, 8 minutes, and so on.
As you can see from Figure 6.14 , ratio schedules tend to generate relatively high rates of responding. This outcome makes sense in light of the fact that in ratio schedules, reinforcement is based on how often you engage in the behaviour (something you have some control over) versus how much time has passed (something you do not control). For example, looking up with greater
frequency does not cause more meteor activity because a variable-interval schedule is in effect. In contrast, a salesperson is on a variable-ratio schedule because approaching more customers increases the chances of making a sale.
One general characteristic of schedules of reinforcement is that partially reinforced responses tend to be very persistent. For example, although people are only intermittently reinforced for putting money into a slot machine, a high rate of responding is maintained and may not decrease until after a great many
losses in a row (or the individual runs out of money). The effect of partial
reinforcement on responding is especially evident during extinction. The partial reinforcement effect refers to a phenomenon in which organisms that have been conditioned under partial reinforcement resist extinction longer than those conditioned under continuous reinforcement. This effect is likely due to the fact that the individual is accustomed to not receiving reinforcement for every response; therefore, a lack of reinforcement is not surprising and does not alter the motivation to produce the response, even if reinforcement is no longer available. We see this effect in many situations ranging from gambling, to cheesy pick-up lines in bars, to the numerous superstitions developed by professional and amateur athletes.
Working the Scientific Literacy Model Reinforcement and Superstition
It is clear that reinforcement can appear in multiple forms and according to various schedules. What all forms have in common is the notion that the behaviour that brought about the reinforcement will be strengthened. But what happens if the organism is mistaken about what caused the reinforcement to occur—will it experience reinforcement anyway? This raises the topic of superstition.
What do we know about superstition and reinforcement? Reinforcement is often systematic and predictable. If it is not, then behaviour is eventually extinguished. In some cases, however, it is not perfectly clear what brings about the reinforcement. Imagine a baseball player who tries to be consistent in how he pitches. After a short losing streak, the pitcher suddenly wins a big game. If he is playing the same way, then what happened to change the outcome of the game? Did an alteration in his pre-game ritual lead to the victory? Humans the world over are prone to believing that some ritual or lucky charm
will somehow improve their chances of success or survival. Psychologists believe these superstitions can be explained by operant conditioning.
How can science explain superstition?
Decades ago, B. F. Skinner (1948) attempted to create superstitious behaviour in pigeons. Food was delivered every 15 seconds, regardless of what the pigeons were doing. Over time, the birds started engaging in “superstitious” behaviours. The pigeons repeated the behaviour occurring just before reinforcement, even if the behaviour was scratching, head- bobbing, or standing on one foot. A pigeon that happened to be turning in a counterclockwise direction when reinforcement was delivered repeated this seemingly senseless behaviour.
Humans are similarly superstitious. For example, in one laboratory study, psychologists constructed a doll that could spit
marbles (Wagner & Morris, 1987). Children were told that the doll would sometimes spit marbles at them and that these marbles could be collected and traded for toys. The marbles were ejected at random intervals, leading several of the children to develop superstitious behaviours such as sucking their thumbs or kissing the doll on the nose.
Psychologists have conducted controlled studies to see whether superstitious behaviours have any effect on performance outcomes. In one investigation, college students, 80% of whom believed in the idea of “good luck,” were asked to participate in a golf putting contest in which members of one group were told they were playing with “the lucky ball,” and others were told they would be using “the ball everyone has used so far.” Those who were told they were using the lucky ball performed significantly better than those who used the ball that was not blessed with
good luck (Damisch et al., 2010). These effects also occurred in other tasks, such as memory and anagram games, and
participants also showed better performance at tasks if allowed to bring a good luck charm.
Can we critically evaluate these findings? Superstitious beliefs, though irrational on the surface, may enhance individuals’ belief that they can perform successfully at a task. Sometimes these beliefs can even enhance performance, as the golf putting experiment revealed. These findings, however, are best applied to situations where the participant has some control over an outcome, such as taking an exam or playing a sport. People who spend a lot of time and money gambling are known to be quite superstitious, but it is important to distinguish between games of chance versus skill in this setting. “Success” at most gambling games is due entirely, or predominantly, to chance. Thus, the outcomes are immune to the superstitious beliefs of the players.
Superstitions are also prone to the confirmation bias—the tendency to seek out evidence in favour of your existing views and ignore inconsistent information—and the partial reinforcement effect discussed above. If an athlete believes that a superstitious behaviour leads to success, then he or she will
notice when the behaviour does lead to success. However, given that losing is generally part of being an athlete, there will be times when the behaviour is not reinforced. Given what you’ve read about the partial reinforcement effect, it is easy to see how a superstitious behaviour could be difficult to change. For instance, former NHL goaltender Patrick Roy was as famous for his many superstitions as he was for his playoff heroics. During every game he would (1) skate backwards toward his net before spinning around at the last minute (which made it appear smaller), (2) talk to his goalposts, (3) thank his goalposts when the puck hit one of them, and (4) avoid touching the blue line and red line when skating off the ice. Roy has the second-highest total of wins for NHL goalies and the most playoff wins in history
(151). He won the Stanley Cup four times and was the playoffs’s Most Valuable Player three times (an NHL record). But, in addition to his 702 reinforcers, he also lost over 400 games in his impressive career.
Why is this relevant? Between Skinner’s original work with pigeons, and more contemporary experiments with people, it appears that operant conditioning plays a role in the development of some superstitions. Perhaps you have a good luck charm or a ritual you must complete before a game or even before taking a test. Think about what brings you luck, and then try to identify why you believe in this relationship. Can you identify a specific instance when you were first reinforced for this behaviour? Then remember that the superstition is a form of reinforcement, a
linking of a behaviour and a response that is formed in your mind. Whether a superstition affects your performance is based on whether or not you allow it to.
Applying Punishment
People tend to be more sensitive to the unpleasantness of punishment than they are to the pleasures of reward. Psychologists have demonstrated this asymmetry in laboratory studies with university students who play a computerized game in which they can choose a response that can bring either a monetary reward or a monetary loss. It turns out that the participants found losing money to be about three times as punishing as being rewarded with money was pleasurable. In other words, losing $100 is three times more punishing than gaining $100 is
reinforcing (Rasmussen & Newland, 2008).
The use of punishment raises some ethical concerns—especially when it comes to physical means. A major issue that is debated all over the world is whether
corporal punishment (e.g., spanking) is acceptable to use with children. In fact, more than 20 countries, including Sweden, Austria, Finland, Denmark, and Israel, have banned the practice. It is technically legal to spank a child aged 2– 12 in Canada; in a contentious decision, the Supreme Court of Canada (in a 6–3
vote) upheld Section 43 of the Criminal Code allowing spanking (Supreme Court of Canada, 2004). Some parents use this tactic because it works: Spanking is generally a very effective punisher when it is used for immediately
stopping a behaviour (Gershoff, 2002). However, one reason so few psychologists advocate spanking is because it is associated with some major
side effects (Gershoff, 2002; Gershoff & Bitensky, 2007). In a recent review of this research published in the Canadian Medical Association Journal, investigators at the University of Manitoba noted that spanking has been associated with poorer parent–child relationships, poorer mental health for both adults and children, delinquency in children, and increased chances of children
becoming victims or perpetrators of physical abuse in adulthood (Durrant & Ensom, 2012).
It is also important to note that, while punishment may suppress an unwanted behaviour temporarily, by itself it does not teach which behaviours are appropriate. As a general rule, punishment of any kind is most effective when
combined with reinforcement of an alternative, suitable response. Table 6.4 offers some general guidelines for maximizing the effects of punishment and minimizing negative side effects.
Table 6.4 Punishment Tends to Be Most Effective When Certain Principles Are Followed
Principle Description and Explanation
Severity Should be proportional to offence. A small fine is suitable for parking
illegally or littering, but inappropriate for someone who commits assault.
Initial
punishment
level
The initial level of punishment needs to be sufficiently strong to reduce
the likelihood of the offence occurring again.
Contiguity Punishment is most effective when it occurs immediately after the
behaviour. Many convicted criminals are not sentenced until many
months after they have committed an offence. Children are given
detention that may not begin until hours later. Long delays in
punishment are known to reduce its effectiveness.
Consistency Punishment should be administered consistently. A parent who only
occasionally punishes a teenager for breaking her curfew will probably
have less success in curbing the behaviour than a parent who uses
punishment consistently.
Show
alternatives
Punishment is more successful, and side effects are reduced, if the
individual is clear on how reinforcement can be obtained by engaging in
appropriate behaviours.
Are Classical and Operant Learning Distinct
Events?
It is tempting to think of behaviour as being due to either classical conditioning or operant conditioning. However, it is possible, even likely, that a complex behaviour is influenced by both types of learning, each influencing behaviour in slightly different ways. Consider gambling with video lottery terminals (VLTs), the topic of the opening story in this module. As discussed above, slot machines and VLTs use a variable-ratio schedule of reinforcement, a type of operant conditioning that leads to a high response rate. But, the flashy lights, the dinging sounds coming from the machine, and even the chair all serve as conditioned stimuli for the unconditioned response of excitement associated with gambling
(Dixon et al., 2014). So, classical conditioning produces an emotional response and operant conditioning maintains the behaviour. Given these forces, should we really be surprised that VLTs are so alluring to people, particular those prone to
problem gambling (Clarke et al., 2012; Nicki et al., 2007)?
Module 6.2c Quiz:
Reinforcement Schedules and Operant Conditioning
Know . . . 1. In a , the first response occurring after a set amount of time leads
to a reward.
A. fixed-ratio schedule B. variable-ratio schedule C. fixed-interval schedule D. variable-interval schedule
Understand . . . 2. Pete cannot seem to stop checking the change slots of vending
machines. Although he usually does not find any money, occasionally he finds a quarter. Despite the low levels of reinforcement, this behaviour is
likely to persist due to . A. escape learning B. the partial reinforcement effect C. positive punishment D. generalization
Apply . . . 3. Frederick trained his parrot to open the door to his cage by pecking at a
lever three times. Based on this description, which schedule of reinforcement would he most likely have used?
A. variable-interval B. variable-ratio C. fixed-interval D. fixed-ratio
Analyze . . . 4. Jeremy regularly spanks his children to decrease their misbehaviour.
Which statement is most accurate in regard to this type of corporal punishment?
A. Spanking is an effective method of punishment and should always be used.
B. Spanking can be an effective method of punishment but carries risks of additional negative outcomes.
C. Spanking is not an effective method of punishment, so it should never be used.
D. The effects of spanking have not been well researched, so it should not be used.
Module 6.2 Summary
applied behaviour analysis
avoidance learning
chaining
continuous reinforcement
discrimination
discriminative stimulus
escape learning
extinction
fixed-interval schedule
fixed-ratio schedule
generalization
law of effect
negative punishment
negative reinforcement
operant conditioning
Know . . . the key terminology associated with operant conditioning.6.2a
partial (intermittent) reinforcement
partial reinforcement effect
positive punishment
positive reinforcement
primary reinforcer
punisher
punishment
reinforcement
reinforcer
schedules of reinforcement
secondary reinforcer
shaping
variable-interval schedule
variable-ratio schedule
Positive and negative reinforcement increase the likelihood of a behaviour, whereas positive and negative punishment decrease the likelihood of a behaviour. Positive reinforcement and positive punishment involve adding a stimulus to the situation, whereas negative reinforcement and negative punishment involve removal of a stimulus.
Schedules of reinforcement can be fixed or variable, and can be based on
intervals (time) or ratios (the number of responses). As can be seen in Figure
Understand . . . the role that consequences play in increasing or decreasing behaviour.
6.2b
Understand . . . how schedules of reinforcement affect behaviour.6.2c
6.14 , variable-ratio schedules produce the most robust learning; reinforcement is linked to the animal’s (or human’s) response rather than to an amount of time, but the animal never knows how many responses will be necessary for a reward to occur. Variable-interval schedules lead to the slowest rate of learning.
The concepts of positive and negative reinforcement and punishment are often the most challenging when it comes to this material.
Apply Activity Read the following scenarios and determine whether positive reinforcement, negative reinforcement, positive punishment, or negative punishment explains the change in behaviour.
1. Bill is caught for cheating on multiple examinations. As a consequence, the school principal suspends him for a three-day period. Bill likes being at school and, when he returns from his suspension, he no longer cheats on exams. Which process explains the change in Bill’s behaviour? Why?
2. Ericka earns As in all of her math classes. Throughout her schooling, she finds that the personal and social rewards for excelling at math continue to motivate her. She eventually completes a graduate degree and teaches math. Which process explains her passion for math? Why?
3. Automobile makers install sound equipment that produces annoying sounds when a door is not shut properly, lights are left on, or a seat belt is not fastened. The purpose is to increase proper door shutting, turning off of lights, and seat belt fastening behaviour. Which process explains the behavioural changes these sounds are attempting to make?
4. Hernan bites his fingernails and cuticles to the point of bleeding and discomfort. To reduce this behaviour, he applies a terrible-tasting topical lotion to his fingertips and the behaviour stops. Which process explains Hernan’s behavioural change?
Apply . . . your knowledge of operant conditioning to examples.6.2d
Analyze . . . the effectiveness of punishment on changing6.2e
Many psychologists recommend that people rely on reinforcement to teach new or appropriate behaviours. The issue here is not that punishment does not work, but rather that there are some notable drawbacks to using punishment as a means to change behaviour. For example, punishment may teach individuals to engage in avoidance or aggression, rather than developing an appropriate alternative behaviour that can be reinforced.
behaviour.
Module 6.3 Cognitive and Observational Learning
Courtesy of Victoria Horner and the Chimpanzee Sanctuary and Wildlife Conservation Trust, Ngamba Island, Uganda
Learning Objectives
Know . . . the key terminology associated with cognitive and observational learning. Understand . . . the concept of latent learning and its relevance to cognitive aspects of learning. Apply . . . principles of observational learning outside of the laboratory. Analyze . . . the claim that viewing violent media increases violent behaviour.
6.3a
6.3b
6.3c 6.3d
Are you smarter than a chimpanzee? For years psychologists have asked this question, but in a more nuanced way. More specifically, they have tested the problem-solving and imitative abilities of chimpanzees and humans to help us better understand what sets us apart from, and what makes us similar to, other animals. Chimps and humans both acquire many behaviours from observing others, but imagine if you pitted a typical human preschooler against a chimpanzee. Who do you think would be the best at learning a new skill just by watching someone else perform it? Researchers Victoria Horner and Andrew Whiten asked this question by showing 3- and 4-year-old children how to retrieve a treat by opening a puzzle box, and then they demonstrated the task to chimpanzees as well. But there was one trick thrown in: As they demonstrated the process, the researchers added in some steps that were unnecessary to opening the box. The children and chimps both figured out how to open it, but the children imitated all the steps—even the unnecessary ones—while the chimps skipped the useless steps and
went straight for the treat (Horner & Whiten, 2005).
What can we conclude from these results? Maybe it is true that both humans and chimps are excellent imitators, although it appears the children imitated a little too well, while the chimps imitated in a smarter manner. Clearly, we both share a motivation to imitate—which is a complex cognitive ability and one of the keys to learning new skills.
Focus Questions
1. What role do cognitive factors play in learning? 2. Which processes are required for imitation to occur?
The first two modules of this chapter focused on relatively basic ways of learning.
Classical conditioning occurs through the formation of associations (Module 6.1 ), and operant conditioning involves changes in behaviour due to
rewarding or punishing consequences (Module 6.2 ). Both types of learning emphasize relationships between stimuli and responses and avoid making
reference to the thinking part of the learning process. However, since the 1950s, psychologists have recognized that cognitive processes such as thinking and remembering are useful to theories and explanations of how we learn.
Cognitive Perspectives on Learning
Cognitive psychologists have contributed a great deal to psychology’s understanding of learning. In some cases, they have presented a very different view from behaviourism by addressing unobservable mental phenomena. In other cases, their work has simply complemented behaviourism by integrating cognitive accounts into even the seemingly simplest of learned behaviours, such as classical and operant conditioning.
Latent Learning
Much of human learning involves absorbing information and then demonstrating what we have learned by performing a task, such as taking a quiz or exam. Learning, and reinforcement for learning, may not be expressed until there is an opportunity to do so. In other words, learning may be occurring even if there is no behavioural evidence of it taking place.
Psychologist Edward Tolman proposed that humans, and even rats, express latent learning —learning that is not immediately expressed by a response until the organism is reinforced for doing so. Tolman and Honzik (1930) demonstrated latent learning in rats running a maze (see Figure 6.15 ). The first group of rats could obtain food if they navigated the correct route through the maze. They were given 10 trials to figure out an efficient route to the end of the maze, where food was always waiting. A second group was allowed to explore the maze, but did not have food available at the other end until the 11th trial. A third group (a control) never received food while in the maze. It might seem that only the first group—the one that was reinforced on all trials—would learn how to
best shuttle from the start of the maze to the end. After all, it was the only group that was consistently reinforced. This is, in fact, what happened—at least for the first 10 trials. Tolman and Honzik discovered that rats that were finally rewarded on the 11th trial quickly performed as well as the rats that were rewarded on
every trial (see Figure 6.15 ). It appears that this second group of rats was learning after all, but only demonstrated their knowledge when they received reinforcement worthy of quickly running through the maze.
Figure 6.15 Learning without Reinforcement Tolman and Honzik (1930) placed rats in the start box and measured the number of errors they made in getting to the end box. Rats that were reinforced during the first 10 days of the experiment made fewer errors. Rats that were reinforced on day 11 immediately made far fewer errors, which indicated that they had learned some spatial details of the maze even though food reinforcement was not available during the first 10 trials for this group. Source: Ciccarelli, Saundra K.; White, J. Noland, Psychology: An Exploration, 1st ed., © 2010, p. 79, 81, 141. Reprinted and
Electronically reproduced by permission of Pearson Education, Inc., New York, NY.
Source: Adapted from “Degrees of Hunger, Reward and Non-Reward and Maze Learning in Rats” by E. C. Tolman & C. H.
Honzik, (1930), University of California Publications in Psychology, 4241–4256.
If you put yourself in the rat’s shoes—or perhaps paws would be more appropriate—you will realize that humans experience latent learning as well. Consider the layout of a university campus. In the first months of school, new students might wander around the campus to find different classrooms and perhaps the cafeteria, but they would probably leave entire buildings unexplored. Yet, if they were suddenly asked to meet someone in a specific building, they would likely be able to find that location without much problem (i.e., they would not wander aimlessly from building to building in a trial-and-error fashion as though investigating a new environment for the first time). The reason is that they would have formed an understanding of the general area, even though that knowledge wasn’t rewarded at the time. Tolman and Honzik assumed that this process held true for their rats, and they further hypothesized that rats possess a
cognitive map of their environment, much like our own cognitive map of our surroundings. Their classic study is important because it illustrates that humans (and rats) acquire information in the absence of immediate reinforcement and that we can use that information when circumstances allow.
It is important to point out that latent learning did not disprove the operant
learning research that highlighted the importance of reinforcement (Module 6.2 ). Instead, most of the controversy centred on the idea of cognitive maps and the statement that no reinforcement had occurred during the first 10 trials. Later research suggested that the rats may have been learning where different
parts of the maze were located in relation to each other rather than forming a complete map of the environment (Whishaw, 1991). Additionally, there is no guarantee that the rats didn’t find exploring the maze on the first 10 trials to be rewarding in some way, as rats are naturally curious about their environment. Because it is experimentally difficult, if not impossible, to answer some of these questions, much of the debate about the mechanisms underlying latent learning
remains unresolved (Jensen, 2006).
S-O-R Theory of Learning
Latent learning suggests that individuals engage in more “thinking” than is shown by operant conditioning studies. Instead, cognitive theories of learning suggest that an individual actively processes and analyzes information; this activity influences observable behaviours as well as our internal mental lives. Because of the essential role played by the individual, this early view of cognitive learning
was referred to as the S-O-R theory (stimulus-organism-response theory; Woodworth, 1929).
Stimulus–response (S–R) and S–O–R theorists both agreed that thinking took place; however, they disagreed about the content and causes of the thoughts. S–R psychologists (such as Thorndike) assumed that thoughts were based on the S–R contingencies that an organism had learned throughout its life; in other words, thinking was a form of behaviour. Individual differences in responding would therefore be explained by the different learning histories of the individuals. S–O–R psychologists, on the other hand, assumed that individual differences
were based on people’s (or animals’) cognitive interpretation of that situation—in other words, what that stimulus meant to them. In this view, the same stimulus in the same situation could theoretically produce different responses based on a variety of factors including an individual’s mood, fatigue, the presence of other organisms, and so on. For example, the same comment to two coworkers might lead to an angry response from one person and laughter from another. The
explanation for these differences is the O in the S–O–R theory; each person or organism will think about or interpret a situation in a slightly different way.
Module 6.3a Quiz:
Cognitive Perspectives on Learning
Know . . . 1. A theory of learning that highlights the role played by an individual’s
interpretation of a situation is (the)
A. classical conditioning theory. B. operant conditioning theory. C. stimulus-organism-response theory. D. individualist theory.
Understand . . . 2. Contrary to some early behaviourist views, suggests that
learning can occur without any immediate behavioural evidence.
A. latent learning B. operant conditioning C. classical conditioning D. desirable difficulties
Observational Learning
The first two modules in this chapter focused on aspects of learning that require direct experience. Pavlov’s dogs experienced the clicking sound of the metronome and the food one right after the other, and learning occurred. Rats in an operant chamber experienced the reinforcing consequences of pressing a lever, and learning occurred. However, not all learning requires direct experience, and this is a good thing. Can you imagine if surgeons had to learn by trial and error? Who on earth would volunteer to be the first patient?
Luckily, many species, including humans, are able to learn new skills and new
associations without directly experiencing them. Observational learning
involves changes in behaviour and knowledge that result from watching others. Humans have elaborate cultural customs and rituals that spread through observation. The cultural differences we find in dietary preferences, clothing
styles, athletic events, holiday rituals, music tastes, and so many other customs exist because of observational learning. Indeed, it is the primary way that adaptive behaviour spreads so rapidly within a population, even in nonhuman
species (Heyes & Galef, 1996). For example, cats that observe others being trained to leap over a hurdle to avoid a foot shock learn the same trick faster
than cats who did not observe this training (John et al., 1968). A less shocking example involves rats’ foraging behaviour. Before setting off in search of food, rats smell the breath of other rats. They will then search preferentially for food that matches the odour of their fellow rats’ breath. To humans, this practice may not seem very appealing—but for rats, using breath as a source of information about food may help them survive. By definition, a breathing rat is a living rat, so clearly the food the animal ate did not kill it. Living rats are worth copying. Human children are also very sensitive to social cues about what they should avoid. Curious as they may be, even young children will avoid food if they
witness their parents reacting with disgust toward it (Stevenson et al., 2010). However, for observational learning to occur, some key processes need to be in place if the behaviour is to be successfully transmitted from one person to the next.
Even rats have a special way of socially transmitting information. Without directly observing what other rats have eaten, rats will smell the food on the breath of other rats and then preferentially search for this food. Cathy Keifer/Shutterstock
Processes Supporting Observational Learning
Albert Bandura (Bandura, 1973; Bandura & Walters, 1963) identified four processes involved in observational learning: attention to the act or behaviour, memory for it, the ability to reproduce it, and the motivation to do so (see Figure 6.16 ). Without any one of these processes, observational learning would be unlikely—or at least would result in a poor rendition of the behaviour.
Figure 6.16 Processes Involved in Observational Learning For observational learning to occur, several processes are required: attention, memory, the ability to reproduce the behaviour, and the motivation to do so.
First, consider the importance of attention. Seeing someone react with a classically conditioned fear to snakes or spiders can result in acquiring a similar fear—even in the absence of any direct experience with snakes or spiders
(LoBue et al., 2010). As an example, are you afraid of sharks? It is likely that many of you have this fear, even if you live thousands of kilometres away from shark-infested waters. The fear you see on the faces of people in horror movies
and in “Shark Week” documentaries is enough for you to learn this experience. Observational learning can extend to operant conditioning as well. Observing someone being rewarded for certain behaviours facilitates imitation of the same behaviours that bring about rewards.
Second, memory is an important facet of observational learning. When we learn a new behaviour, there is often a delay before the opportunity to perform it arises. If you tuned in to a cooking show, for example, you would need to recreate the steps and processes required to prepare the dish at a later time. Interestingly, memory for how to reproduce a behaviour or skill can be found at a
very early age (Huang, 2012). Infants just nine months of age can reproduce a new behaviour (admittedly, a much simpler one than cooking), even if there is up to a one-week delay between observing the act and having the opportunity to
reproduce it (Meltzoff, 1988).
Third, observational learning requires that the observer can actually reproduce the behaviour. This can be very challenging, depending on the task. Unless an individual has a physical impairment, learning an everyday task—such as operating a can opener—is not difficult. By comparison, hitting a baseball thrown by a Toronto Blue Jays pitcher requires a very specialized skill set. Research indicates that observational learning is most effective when we first observe, practise immediately, and continue practising and observing soon after acquiring the response. For example, one study found that the optimal way to develop and maintain motor (movement) skills is by repeated observation before and during
the initial stages of practising (Weeks & Anderson, 2000). It appears that watching someone else helps us practise effectively, and allows us to see how errors are made. When we see a model making a mistake, we know to examine
our own behaviour for similar mistakes (Blandin & Proteau, 2000; Hodges et al., 2007).
Myths in Mind Is Teaching Uniquely Human? Teaching is a significant component of human culture and a primary means by which information is learned in classrooms, at home, and in many other settings. But are humans the only species with the ability to
teach others? Some intriguing examples of teaching-like behaviour have
been observed in nonhuman species (Thornton & Raihani, 2010). Prepare to be humbled.
Teaching behaviour was recently discovered in ants (Franks & Richardson, 2006)—probably the last species we might suspect would demonstrate this complex ability. For example, a “teacher” ant gives a “pupil” ant feedback on how to locate a source of food.
Field researchers studying primates discovered the rapid spread of
potato-washing behaviour in Japanese macaque monkeys (Kawai, 1965). Imo—perhaps one of the more ingenious monkeys of the troop— discovered that potatoes could be washed in salt water, which also may have given them a more appealing taste. Potato-washing behaviour subsequently spread through the population, especially among the monkeys that observed the behaviour in Imo and her followers.
Primate researchers have documented the spread of potato washing in Japanese macaque monkeys across multiple generations. Monkeys appear to learn how to do this by observing experienced monkeys from their troop. Miles Barton/Nature Picture Library
Transmission of new and unique behaviours typically occurs between
mothers and their young (Huffman, 1996). Chimpanzee mothers, for example, actively demonstrate to their young the special skills required to
crack nuts open (Boesch, 1991). Also, mother killer whales appear to show their offspring how to beach themselves (Rendell & Whitehead, 2001), a behaviour that is needed for the type of killer whale that feeds on seals that congregate along the shoreline.
In each of these examples, it is possible that the observer animals are imitating the individual who is demonstrating a behaviour. These observations raise the possibility that teaching may not be a uniquely human endeavour.
Is this killer whale teaching her offspring to hunt for seals? Researchers have found evidence of teaching in killer whales and a variety of other nonhuman species. Danita Delimont Creative/ Alamy Stock Photo
Finally, motivation is clearly an important component of observational learning. On the one hand, being hungry or thirsty will motivate an individual to find out where others are going to find food and drink. On the other hand, a child who has no aspirations to ever play the piano will be less motivated to observe his teacher during lessons. He will also be less likely to practise the observed behaviour that he is trying to learn.
Observational punishment is also possible, but appears to be less effective at changing behaviour than reinforcement. Witnessing others experience negative consequences may decrease your chances of copying someone else’s behaviour. Even so, we are sometimes surprisingly bad at learning from observational punishment. Seeing the consequences of smoking, drug abuse, and other risky behaviours does not seem to prevent many people from engaging in the same activities.
Imitation and Mirror Neurons
One of the primary mechanisms that allows observational learning to take place
is imitation —recreating someone else’s motor behaviour or expression, often to accomplish a specific goal. From a very young age, infants imitate the facial expressions of adults (Meltzoff & Moore, 1977). Later, as they mature physically, children readily imitate motor acts produced by a model, such as a parent, teacher, or friend. This ability seems to be something very common among humans. However, it is currently unclear what imitation actually is, although a number of theories exist. Some researchers suggest that children receive positive reinforcement when they properly imitate the behaviour of an
adult and that imitation is a form of operant learning (Horne & Erjavec, 2007). Others suggest that imitation allows children to gain a better understanding of
their own body parts versus the “observed” body parts of others (Mitchell, 1987). Finally, imitation might involve a more cognitive representation of one’s own
actions as well as the observed actions of someone else (Whiten, 2000). It is likely that all three processes are involved with imitation at different points in
human (and some animal) development (Zentall, 2012).
Neuroscientists have provided additional insight into the functions of imitation. In the 1990s, Italian researchers discovered that groups of neurons in parts of the frontal lobes associated with planning movements became active both when a
monkey performed an action and when it observed another monkey performing an action (di Pellegrino et al., 1992). These cells, now known as mirror neurons, are also found in several areas in the human brain and have been linked to many different functions ranging from understanding other people’s
emotional states to observational learning (Rizzolatti et al., 1996; Rizzolatti & Craighero, 2004). Additionally, groups of neurons appear to be sensitive to the context of an action. In one study, participants viewed a scene of a table covered
in a plate of cookies, a teapot, and a cup (see Figure 6.17 ). In one photo of these items, the setting is untouched. In this case, reaching for the cup of tea would indicate that the person intended to have a sip. In another photo, many of the cookies are gone and the milk container has been knocked over. In this case, reaching for the cup of tea—the identical action as in the previous photo—would indicate that the person was cleaning up the mess. Incredibly, different groups of mirror neurons fired in response to the two images, despite the fact that the
identical movement was being viewed (Iacoboni et al., 2005). These results suggest that the mirror neuron system—a key part of our ability to imitate—is sensitive to the purpose or goal of the imitated action.
Figure 6.17 Grasping Intentions of Mirror Neurons Watching the same physical action—grabbing the teacup— in these two scenarios will lead to activity in different groups of neurons in the mirror neuron system. This suggests that the mirror neuron system is influenced by the goals of the actions, not just the physical action itself. Source: From Iacoboni, M., Molnar-Szakacs, I., Gallese, V., Buccino, G., Mazziotta, J. C., and Rizzolatti, G. PLoS Biol, 2005,
3, e79. http://dx.doi.org/10.1371/journal.pbio.0030079.g001. Reprinted under open access license.
Working the Scientific Literacy Model Linking Media Exposure to Behaviour
Imitating behaviours such as opening contraptions with sticks or picking up teacups is fairly harmless. However, not all of the behaviours children see are this innocent. Children (and adults) are exposed to dozens of violent actions in the media, on the Internet, and in computer games every day. If kids are imitating the behaviours they see in other contexts, does this mean that the media are creating a generation of potentially violent people?
What do we know about media effects on behaviour? In some cases, learning from the media involves direct imitation; in other cases, what we observe shapes what we view as normal or acceptable behaviour. Either way, the actions people observe in the media can raise concerns, especially when children are watching. Given that North American children now spend an average of five hours per day interacting with electronic media, it is no wonder that one of the most discussed and researched topics in observational learning is the role of media violence in developing aggressive behaviours and desensitizing individuals
to the effects of violence (Anderson et al., 2003; Huesmann, 2007). So how have researchers tackled the issue?
How can science explain the effect of media exposure on children’s behaviour? One of the first experimental attempts to test whether exposure to violence begets violent behaviour in children was made by Albert
Bandura and colleagues (1961, 1963). In a series of studies, groups of children watched an adult or cartoon character attack a “Bobo” doll, while another group of children watched adults who
did not attack the doll. Children who watched adults attack the doll did likewise when given the opportunity, in some cases even imitating the specific attack methods used by the adults. The other children did not attack the doll. This provided initial evidence that viewing aggression makes children at least temporarily more prone to committing aggressive acts toward an inanimate object.
Decades of research has since confirmed that viewing aggression is associated with increased aggression and
desensitization to violence (Bushman & Anderson, 2007). In one Canadian study, Wendy Josephson (1987) had children aged 7–9 view a violent or nonviolent film before playing a game of floor hockey. Not surprisingly, children who viewed the violent film were more likely to act aggressively (i.e., to commit an act that would be penalized in a real hockey game). As an added twist, in some of the floor hockey games, a referee carried a walkie-talkie that had appeared in the violent film and thus served as a reminder of the violence. This movie-associated cue stimulated more violence, particularly in children who the teachers had indicated were prone to aggression.
Visual images are not the only source of media violence,
however. Music, particularly hip hop and rap music (Herd, 2009), has become increasingly graphic in its depictions of violence over the last few decades. Psychologists have found that songs with violent lyrics can lead to an increase in aggressive and hostile
thoughts in a manner similar to violent movies (Anderson et al., 2003). In one study, German researchers asked male and female participants to listen to songs with sexually aggressive lyrics that were degrading to women. After listening to this music, the participants were asked to help out with a (staged) taste- preference study by pouring hot chili sauce into a plastic cup for another participant (who was actually a confederate of the experimenters). The researchers found that after listening to
aggressive music that degraded women, males poured more hot sauce for a female than for a male confederate; this difference did not occur after listening to neutral music. Female participants did not show this effect. Male participants also recalled more negative and aggressive thoughts. Interestingly, when women listened to lyrics that were demeaning to men, they too recalled
more negative and hostile information (Fischer & Greitmeyer, 2006). Thus, the effects of media violence are not limited to the visual domain and can affect both males and females.
Can we critically evaluate this research? Exposure to violent media and aggressive behaviour and thinking are certainly related to each other. However, at least two very important questions remain. First, does exposure to violence
cause violent behaviour or desensitization to violence? Second, does early exposure to violence turn children into violent adolescents or adults? Unfortunately, there are no simple answers to either question, due in large part to investigators’ reliance on correlational designs, which are typically used for studying long-term effects. Recall that correlational studies can establish only that variables are related, but cannot determine that one variable (media) causes another one (violent behaviour). What is very clear from decades of research is that a positive correlation exists between exposure to violent media and aggressive behaviour in individuals, and that this correlation is stronger than those between aggression and peer influence,
abusive parenting, or intelligence (Bushman & Anderson, 2007).
Another concern with these studies is that they aren’t really
examining why people respond aggressively when they see violent imagery. Although there is clearly a role for observational learning, a number of researchers have also suggested that people become desensitized to the violence and thus less likely to inhibit their own violent impulses. Recent brain-imaging studies
support this view. In one study, activity in parts of the frontal and parietal lobes showed reductions in activity as people became
less sensitive to aggression shown in videos (Strenziok et al., 2011). In another experiment, participants with a low history of exposure to media violence showed more activity in frontal-lobe regions related to inhibiting responses than did participants who had more exposure to media violence and who had a history of aggressive behaviour. These differences were particularly strong when participants had to inhibit responses related to aggression- related words (Kalnin et al., 2011). Although these studies don’t definitively explain why media violence affects behaviour, they do point to at least one potential cause.
Why is this relevant? Clearly then, media violence is a significant risk factor for future aggressiveness. Many organizations have stepped in to help parents make decisions about which type of media their children will be exposed to. The Motion Picture Association of America has been rating movies, with violence as a criterion, since 1968. (Canada does not have a national ratings system; individual provinces each rate movies.) Violence on television was being monitored and debated even before the film industry took this step. Since the 1980s, parental advisory stickers have been appearing on music with lyrics that are sexually explicit, reference drug use, or depict violence. Of course, as you know, these precautions have little effect on what children watch and listen to. Kids will always find a way to access this type of material. But, providing parents with more information about how these depictions of violence can affect children will hopefully highlight some of the dangers of these images and lyrics, and may inspire
them to talk to their kids about how violence can be real. Doing so might teach children and adolescents to be better at examining how media violence could be affecting their own behaviour.
In Albert Bandura’s experiment, children who watched adults behave violently toward the Bobo doll were aggressive toward the same doll when given the chance—often imitating specific acts that they viewed. Albert Bandura
Biopsychosocial Perspectives Violence, Video
Games, and Culture Can pixilated, fictional characters controlled by your own hands make you more aggressive or even violent? Adolescents, university students, and even adults in their thirties and forties play hours of video games each day, many of which are very violent. Also, because video games are becoming so widespread, questions have been raised about whether the correlations between media violence and aggression are found across different cultures. What do you think: Do these games increase aggression and violent acts by players? First, test your knowledge and assumptions and then see what research tells us.
True or False? 1. Playing violent video games reduces a person’s sensitivity to
others’ suffering and need for help.
2. Gamers who play violent video games are less likely to behave aggressively if they are able to personalize their own character.
3. Gamers from Eastern cultures, who play violent video games as much as Westerners, are less prone to video game–induced aggression.
4. Physiological arousal is not affected by violent video games. 5. Male gamers are more likely to become aggressive by playing
video games than female gamers.
Answers
Source: These data are from Anderson et al., 2010; Carnagey et al., 2007; and Fischer et al., 2010.
Research examining the effects of violent movies, television shows, and music lyrics paints a disturbing picture of the effects of media on aggressive behaviour. Recently, due to a drastic upsurge in their popularity and sophistication, video games have also been labelled with parental advisory stickers. Some violent games, such as Call of Duty (which has sold over 140 million copies worldwide), involve shooting and blowing up the enemy. Other games, such as Grand Theft
1. True. People who play violent video games often become less sensitive to the feelings and well-being of others. 2. False. Personalizing a character seems to increase aggressive behaviour. 3. False. Gamers from both Eastern and Western cultures show the same effects. 4. False. Players of violent video games show increased physiological arousal during play. However, it is important to remember that this does not mean that playing these games will necessarily cause someone to become violent. 5. False. There are no overall gender differences in aggression displayed by gamers.
Auto, allow the player to commit illegal and violent acts. An obvious question is: Are video games related to aggressive behaviour (i.e., observational learning) in the same way that movies are?
Of course, the most important question is whether a regular pattern of playing
violent video games causes violent behaviour. In 2015, the American Psychological Association issued a report stating that research has shown a consistent link between violent video games and violent behaviour. However, a number of academics disagreed with the methods used to come to these conclusions. Critics also pointed out that violent crime is decreasing in most countries despite the prevalence of video games. The general consensus is that violent video games can lead to aggressive thoughts and behaviours in some people. Whether these games have a long-term effect on behaviour is still unclear.
These data don’t mean that you should never watch a violent movie or play violent video games. And, you don’t need to delete your gangsta rap songs and replace them with a steady diet of Taylor Swift. Rather, these data show you that
the media can influence your behaviour. It’s up to you to become aware of how media violence can lead to (unintentional) observational learning. Doing so will help ensure that your actions are, in fact, your own.
Module 6.3b Quiz:
Observational Learning
Know . . . 1. Observational learning
A. is the same thing as teaching. B. involves a change in behaviour as a result of watching others. C. is limited to humans. D. is not effective for long-term retention.
2. is the replication of a motor behaviour or expression, often to
accomplish a specific goal.
A. Observational learning B. Latent learning C. Imitation D. Cognitive mapping
Apply . . . 3. Nancy is trying to learn a new yoga pose. To obtain the optimal results,
research indicates she should
A. observe, practise immediately, and continue to practice and to observe others.
B. observe and practise one time. C. just closely observe the behaviour. D. observe the behaviour just one time and then practise on her
own.
Analyze . . . 4. Which is the most accurate conclusion from the large body of research
that exists on the effects of viewing media violence?
A. Exposure to violent media directly causes increased aggression and desensitization to violence.
B. There is a positive correlation between exposure to media violence and aggressive behaviour.
C. Researchers cannot establish a link between exposure to violent media and either aggression levels or desensitization to violence without first conducting brain-imaging studies.
D. Viewing aggression is not related to increased aggression and desensitization to violence.
Module 6.3 Summary
imitation
Know . . . the key terminology associated with cognitive and observational learning.
6.3a
latent learning
observational learning
Without being able to observe learning directly, it might seem as if no learning occurs. However, Tolman and Honzik showed that rats can form cognitive maps of their environment. They found that even when no immediate reward was available, rats still learned about their environment.
Apply Activity Based on what you read about in this module, how would you use observational learning in each of these settings?
1. Teaching children how to kick a soccer ball 2. Improving efficiency in a busy office 3. Improving environmental sustainability at a university
Are you simply letting people observe your behaviour, or does your plan involve elements learned in other modules in this chapter (e.g., shaping)?
Psychologists agree that observational learning occurs and that media can influence behaviour. Many studies show a correlational (noncausal) relationship between violent media exposure and aggressive behaviour. Also, experimental studies, going all the way back to Albert Bandura’s work in the 1960s, indicate that exposure to violent media can at least temporarily increase aggressive behaviour.
Understand . . . the concept of latent learning and its relevance to cognitive aspects of learning.
6.3b
Apply . . . principles of observational learning outside of the laboratory.
6.3c
Analyze . . . the claim that viewing violent media increases violent behaviour.
6.3d
Chapter 7 Memory
7.1 Memory Systems The Atkinson-Shiffrin Model 272
Working the Scientific Literacy Model: Distinguishing Short-Term from Long-Term Memory Stores 276
Module 7.1a Quiz 278
The Working Memory Model: An Active STM System 279
Module 7.1b Quiz 281
Long-Term Memory Systems: Declarative and Nondeclarative Memories 282
Module 7.1c Quiz 283
The Cognitive Neuroscience of Memory 283
Module 7.1d Quiz 286
Module 7.1 Summary 287
7.2 Encoding and Retrieving Memories Encoding and Retrieval 289
Working the Scientific Literacy Model: Context-Dependent Memory 291
Module 7.2a Quiz 295
Emotional Memories 295
Module 7.2b Quiz 297
Forgetting and Remembering 298
Module 7.2c Quiz 300
Module 7.2 Summary 301
7.3 Constructing and Reconstructing Memories How Memories Are Organized and Constructed 303
Working the Scientific Literacy Model: How Schemas Influence Memory 303
Module 7.3a Quiz 305
Memory Reconstruction 306
Module 7.3b Quiz 311
Module 7.3 Summary 312
Module 7.1 Memory Systems
Jsemeniuk/E+/Getty Images
Learning Objectives
In October 1981, an Ontario man lost control of his motorcycle and flew off an exit ramp west of Toronto. He suffered a severe head injury and required immediate brain surgery in order to treat the swelling caused by the impact. Brain scans conducted after the accident showed extensive
Know . . . the key terminology of memory systems. Understand . . . which structures of the brain are associated with specific memory tasks and how the brain changes as new memories form. Apply . . . your knowledge of the brain basis of memory to predict what types of damage or disease would result in which types of memory loss. Analyze . . . the claim that humans have multiple memory systems.
7.1a 7.1b
7.1c
7.1d
damage to the temporal lobes (including the hippocampus) as well as to both frontal lobes and the left occipital lobe. When the man, now known as patient K.C., recovered consciousness, doctors quickly noted that he had severe memory impairments. However, when psychologists from the University of Toronto dug deeper into K.C.’s condition, it became clear that he had retained some memory for general knowledge, but had lost
his episodic memory, the memory of his specific experiences (Tulving et al., 1988). Strikingly, K.C. could recall the facts about his life (e.g., where he lived) but could not recall his personal experiences or feelings relating to those facts (e.g., sitting on the steps with friends).
K.C.’s devastating experience helped researchers prove that we have several different types of memory, each involving different networks of
brain areas (Rosenbaum et al., 2005). His case also hearkens back to a philosophical question posed by William James (1890/1950) over a century ago: If an individual were to awaken one day with his or her personal memories erased, would he or she still be the same person?
Focus Questions
1. How is it possible to remember just long enough to have normal conversations and activities but then to forget them almost immediately?
2. How would damage to different brain areas affect different types of memory?
You have probably heard people talk about memory as if it were a single ability:
I have a terrible memory! Isn’t there some way I could improve my memory?
But have you ever heard people talk about memory as if it were several abilities?
One of my memories works well, but the other is not so hot.
Probably not. However, as you will learn in this module, memory is actually a collection of several systems that store information in different forms for differing
amounts of time (Atkinson & Shiffrin, 1968). One influential model for understanding these different systems, and the different types of memories they
involve, can be seen in Figure 7.1 .
Figure 7.1 The Atkinson-Shiffrin Model Memory is a multistage process. Information flows through a brief sensory memory store into short-term memory, where rehearsal encodes it into long-term memory for permanent storage. Memories are retrieved from long-term memory and brought into short-term storage for further processing.
Source: Based on “Human Memory: A Proposed System and Its Control Processes” by in The Psychology of Learning and
Motivation: Advances in Research and Theory, Vol 2 (pp. 89–195).
The Atkinson-Shiffrin Model
In the 1960s, Richard Atkinson and Richard Shiffrin reviewed what psychologists knew about memory at that time and constructed the memory model that bears
their name (see Figure 7.1 ). The first thing to notice about the Atkinson- Shiffrin model is that it includes three memory stores (Atkinson & Shiffrin, 1968). Stores retain information in memory without using it for any specific purpose; they essentially serve the same purpose as hard drives serve for a computer. The three stores include sensory memory, short-term memory (STM), and long-term memory (LTM), which we will investigate in more detail later. In
addition, control processes shift information from one memory store to another. These are represented by the arrows in the model in Figure 7.1 .
An important point illustrated in Figure 7.1 is that our memory systems, although stunningly powerful, are not perfect. We lose, or forget, information at each step of this model. Information enters the sensory memory store through all of the senses (e.g., vision, hearing, etc.), and the control process we call attention selects which information will be passed on to STM. This is highly functional: the attention process selects some elements of our environment that will receive further processing and add to our experience and understanding of the world. However, this functionality comes at a cost, because a vast amount of sensory information is quickly forgotten, almost immediately replaced by new input. We selectively narrow the information we receive in STM even further
through encoding , the process of storing information in the LTM system. We retain only some information and lose the rest. Retrieval brings information from LTM back into STM; this happens when you become aware of existing memories, such as remembering the movie you saw last week. Of course, this process is not perfect—we are sometimes unable to retrieve information when we want to. But, overall, our ability to retrieve information is astonishing. This interplay between remembering and forgetting is a theme that extends across all
of the modules in this chapter. In this module, we are primarily concerned with the various types of memory stores, so we will examine each one in detail.
Sensory Memory
“What did I just say to you?” This sentence rarely leads to good things. It is generally spoken when one person in a conversation (e.g., a relationship partner) is apparently not paying attention to what another person (e.g., the other relationship partner) is saying. Individuals on the receiving end of this sentence often experience anxiety, if not a sense of doom. Luckily, we have a memory store that can sometimes come to the rescue.
Sensory memory is a memory store that accurately holds perceptual information for a very brief amount of time—how brief depends on which sensory system we talk about. Iconic memory , the visual form of sensory memory, is held for about one-half to one second. Echoic memory , the auditory form of sensory memory, is held for considerably longer, but still only for about 5–10 seconds (Cowan et al., 1990). It is this form of sensory memory that will allow you to repeat back the words you just heard, even though you may have been thinking about something else.
How much information can be held in sensory memory? This important question has proven very difficult to answer, because sensory memories—particularly
visual memories—disappear faster than an individual can report them. George Sperling (1960) devised a brilliant method for testing the storage capacity of iconic memory. In his experiment, researchers flashed a grid of letters on a
screen for a fraction of a second (Figure 7.2 a), and participants were asked to report what they saw. In the whole report condition, participants attempted to recall as many of the letters as possible—the whole screen. Participants were generally able to report only three or four of the letters, and these would usually be in the same line. But does this mean that the iconic sensory memory system can only store three or four bits of information at a time? Sperling thought that it likely had a larger capacity, but hypothe-sized that the memory of the letters actually faded faster than participants could report them. To test this, in the
partial report condition, participants were again flashed a set of letters on the screen, but the display was followed immediately by a tone that was randomly
chosen to be low, medium, or high (Figure 7.2 b). After hearing the tone, participants were to report the corresponding line of letters—bottom, middle, or top. Under these conditions, participants still reported only three or four of the letters, but they reported them from the row indicated by the tone. Because the tone came after the screen went blank, the only way the participants could get the letters right is if all of the letters were (temporarily) stored in sensory memory. Thus Sperling argued that iconic memory could hold all 12 letters as a mental image, but that they would only remain in sensory memory long enough for a few letters to be reported.
Figure 7.2 A Test of Iconic Sensory Memory Sperling’s participants viewed a grid of letters flashed on a screen for a split second, then attempted to recall as many of the letters as possible. In the whole
report condition (a), they averaged approximately four items, usually from a single row. However, in the partial report condition (b), participants could usually
name any row of four items, depending on the row they were cued to recite. This indicated that participants’ iconic memory system could store far more than the mere four items they were able to report.
But if information in our sensory memory disappears after half a second, then how can we have any continuous perceptions? How can you stare meaningfully into someone’s eyes without that person fading away from memory half a second after you look away, just like the letters in Sperling’s experiment? The answer is attention. Attention allows us to move a small amount of the information from our sensory memory into STM for further processing. This information is often
referred to as being within the “spotlight of attention” (Pashler, 1998). Information that is outside of this spotlight of attention is not transferred into STM and is unlikely to be remembered.
The relationship between sensory memory and attention is beautifully illustrated
by a phenomenon known as change blindness (Rensink et al., 1997, 2000; Simons & Levin, 1997). In a typical change blindness experiment, participants view two nearly identical versions of a photograph (or some other stimulus); these stimuli will have only one difference between them (e.g., a car is different colours in the two photographs). The goal on each trial of the experiment is to
locate the difference (see Figure 7.3 ). However, the way in which the images are displayed presents quite a challenge. The two versions of the photograph are alternately presented for 240 ms each, with a blank screen in between them. So, a participant would see Photograph 1, blank screen, Photograph 2, blank screen, Photograph 1, blank screen, and so on. If the item that differs between the two photographs (e.g., the car) is not the focus of attention, people generally fail to
notice the change (hence the term change blindness). This is likely because the appearance of the blank screen in between the two photographs occupies sensory memory, thus making the memory of the previous photograph less accessible. However, if the participant is paying attention to that changing element (i.e., the “spotlight” of attention is focused on that part of the image), the image of the first version of that item will be transferred into STM when the
second, changed version appears on the screen. The difference between the two photographs then becomes apparent.
Figure 7.3 Change Blindness, Attention, and Sensory Memory In change blindness, the sensory memory of photograph A disappears before the onset of photograph B, making it difficult to identify the difference between the two pictures. However, if a person is paying attention to the area that differs between the two photographs, then the representation of that part of the first photograph will still be in short-term memory when the second photograph appears, thus making it relatively easy to spot the change. In this example, part of a tree branch disappears in photograph B. Source: Based on Rensink, R. A., O’Regan, J. K., & Clark, J. J. (1997). To see or not to see: The need for attention to
perceive changes in scenes. Psychological Science, 8, 368–373. (Figure 1, p. 369).
An obvious question that arises is: Why don’t people quickly move their spotlight of attention around so that they can transfer all of their sensory memory into short-term memory? Unfortunately, there is a limit to how much information can
be transferred at once (Marois & Ivanoff, 2005).
Short-Term Memory and the Magical Number 7
Although transferring information from sensory memory into short-term memory increases the chances that this information will be remembered later, it is not
guaranteed. This is because short-term memory (STM) is a memory store with limited capacity and duration (approximately 30 seconds). The capacity of STM was summed up by one psychologist as The Magical Number Seven, Plus or Minus Two (Miller, 1956). In his review, Miller found study after study in which participants were able to remember seven units of information, give or take a couple. One researcher made the analogy between STM and a juggler who can keep seven balls in the air before dropping any of them. Similarly, STM can rehearse only seven units of information at once before forgetting something
(Nairne, 1996).
This point leads to an important question: What, exactly, is “a unit of information”? The answer is not as straightforward as one might expect. It turns
out that, whenever possible, we expand our memory capacity with chunking , organizing smaller units of information into larger, more meaningful units. These larger units are referred to as chunks. Consider these examples:
1. O B T N C H C V N T C N S N C 2. C B C H B O C T V T S N C N N
If we randomly assigned one group of volunteers to remember the first list, and another group to remember the second list, how would you expect the two groups to compare? Look carefully at both lists. List 2 is easier to remember than list 1. Volunteers reading list 2 have the advantage of being able to apply patterns that fit their background knowledge; specifically, they can chunk these letters into five groups based on popular television networks:
1. CBC HBO CTV TSN CNN
In this case, chunking reduces 15 bits of information to a mere five. We do the same thing with phone numbers. We turn the area code (236) into one chunk, the first three numbers (555) into another chunk, and then the final four numbers into one or two chunks depending upon the numbers (e.g., 1867 might be one
chunk because it can be remembered as the year Canada became a country, while 8776 could be remembered as two chunks representing the jersey numbers for hockey players Sidney Crosby and P. K. Subban or, if you’re not a hockey fan, some other meaningful pattern).
The ability to chunk material varies from situation to situation. If you had never watched television, then the five chunks of information in the example above wouldn’t be very meaningful to you. This suggests that experience or expertise plays a role in our ability to chunk large amounts of information so that it fits into our STM. Studies of chess experts have confirmed that this is the case. Whereas most people would memorize the positions of chess pieces on a board individually, chess masters perceive it as a single unit, like a photograph of a
scene (Chase & Simon, 1973; Gobet & Simon, 1998). Therefore, they are able to remember the positions of significantly more chess pieces than novices can. Of course, chunking only works when the chess pieces are aligned in meaningful chess positions; when they are randomly placed on the board, the experts’
memory advantage disappears (see Figure 7.4 ). Chunking also allows the chess masters to envision what the board will look like after future moves, again providing them with an edge over novices.
Figure 7.4 Chunking in Chess Experts Chess experts have superior STM for the locations of pieces on a chess board due to their ability to create STM chunks. This advantage only occurs when the pieces are placed in a meaningful way, as they would appear in a game. (a) A depiction of a board with the pieces placed as they would appear in a game (left) and pieces placed in random locations (right). (b) The difference in STM for meaningful vs. randomly placed pieces increased as a function of the test subject’s chess experience. Source: Based on Gobet, F., Lane, P. C. R., Croker, S., Cheng, P. C. H., Jones, G., Oliver, I., and Pine, J. M. (2001).
Chunking mechanisms in human learning. TRENDS in Cognitive Sciences, 5(6), 236–243. (Figure 1, p. 237).
Importantly, this expertise is not necessarily based on some innate talent; it can be learned through intensive practice. The most stunning confirmation of this
view comes from the Polgár sisters of Budapest, Hungary (Flora, 2005). Their father, Lázló Polgár, decided before they were born that he was going to raise them to become chess grandmasters. Doing so would confirm his belief that anyone could be trained to become a world-class expert in any field if he or she worked hard enough (he was not a grandmaster himself). Polgár trained his daughters in the basics of chess, and had them memorize games so that they could visualize each move on the board. After thousands of hours of what amounts to “chunking training,” the girls (who, luckily, enjoyed chess) rose to the top of the chess world. The eldest daughter, Susan, became the first female to earn the title of Grandmaster through tournament play. The youngest daughter, Sofia, is an International Master. The middle daughter, Judit, is generally thought of as the best female chess player in history.
Long-Term Memory
Not all of the information that enters STM is retained. A large proportion of it is lost forever. This isn’t necessarily a bad thing, however. Imagine if every piece of information you thought about remained accessible in your memory. Your mind would be filled with phone numbers, details from text messages, images from billboards and ads on buses, as well as an incredible amount of trivial information from other people (e.g., overhearing the coffee order of the person in front of you). Instead, only a small amount of information from STM is encoded or transformed into a more permanent representation that we can intentionally access later on. Encoding allows information to enter the final memory store in
the Atkinson-Shiffrin model. This store, long-term memory (LTM) , holds information for extended periods of time, if not permanently. Unlike short-term memory, long-term memory has no capacity limitations (that we are aware of). All of the information that undergoes encoding will be entered into LTM.
Once entered into LTM, the information needs to be organized. Researchers have identified at least two ways in which this organization occurs. One way is
based on the semantic categories that the items belong to (Collins & Loftus, 1975). The mental representation of cat would be connected to and stored near the mental representation of other animals such as dog and mouse. This model is consistent with the results from an interesting experiment from the 1950s.
Participants were asked to remember a list of 60 words that were drawn from four different categories. Although the words were randomly presented, participants recalled them in semantically related groups (e.g., lion, tiger, cheetah . . . guitar, violin, cello, etc.). This research suggests that semantically
related items are stored near each other in LTM (see Module 8.1 ). A second way that LTM is organized is based on the sounds of the word and on how the
word looks. This explains part of the tip-of-the-tongue (TOT) phenomenon , when you are able to retrieve similar sounding words or words that start with the same letter but can’t quite retrieve the word you actually want (Brown & McNeil, 1966). What appears to be happening in these situations is that nearby items, or nodes, in your neural network are activated.
Of course, having the information in LTM doesn’t necessarily mean that you can access it when you want to. If that were the case, then you would never forget where you put your keys, and no one would be impressed by your knowledge of pop culture trivia. Instead, the likelihood that a given piece of information will undergo retrieval—the process of accessing memorized information and returning it to short-term memory—is influenced by a number of different factors including the quality of the original encoding and the strategies used to retrieve the information. These important processes are described in depth later in this chapter.
Working the Scientific Literacy Model Distinguishing Short-Term from Long-Term Memory Stores
The Atkinson-Shiffrin model of memory is very neat and tidy, with different memory stores contained in separate boxes. The problem is that the real world rarely involves 30-second blocks of time filled with 7 ± 2 pieces of information followed by a short break to encode them. Instead, we are often required to use both STM and LTM at the same time. Without this ability, we wouldn’t
be able to have conversations, nor would we be able to understand paragraphs of text like this one. So, if both STM and LTM are constantly working together, how do we isolate the functions of each memory store?
What do we know about short-term and long-term memory stores? As you’ll recall (thanks to your LTM), STM lasts for approximately 30 seconds and usually contains 7 ± 2 units of information; LTM has no fixed time limits or capacity. The distinction between STM and LTM can be revealed with a simple experiment. Imagine a group of people studied a list of 15 words and then immediately tried to recall the words in the list. The serial position curve—the
U-shaped graph in Figure 7.5 —shows what the results would look like according to the serial position effect : In general, most people will recall the first few items from a list and the last few items, but only an item or two from the middle (Ebbinghaus, 1885/1913). This finding holds true for many types of information, ranging from simple strings of letters to the ads you might recall
after watching the Super Bowl (Laming, 2010; Li, 2010).
Figure 7.5 The Serial Position Effect
Memory for the order of events is often superior for original items (the primacy effect) and later items (the recency effect). The serial position effect provides evidence of distinct short-term and
long-term memory stores.
The first few items are remembered relatively easily (known as
the primacy effect) because they have begun the process of entering LTM. The last few items are also remembered well
(known as the recency effect); however, this is because those items are still within our STM (Deese & Kaufman, 1957). The fate of the items in the middle of the test is more difficult to determine, as they would be in the process of being encoded into LTM. As you have already read, some information is lost during this process.
How can science explain the difference between STM and LTM stores?
The shape of the serial position effect (see Figure 7.5 ) suggests that there are two different processes at work. But, how do we explain the dip in the middle of the curve? Memory researchers suggest that this dip in performance is caused by two different mechanisms. First, the items that were at the beginning
of the list produce proactive interference , a process in which the first information learned (e.g., in a list of words) occupies memory, leaving fewer resources left to remember the newer information. The last few items on the list create retroactive interference —that is, the most recently learned information overshadows some older memories that have not yet made it into long-term memory (see Figure 7.6 ). Together, these two types of interference would result in poorer memory performance for items in the middle of a list.
Figure 7.6 Proactive and Retroactive Interference Contribute to the Serial Position Effect
In addition to demonstrating behavioural differences between STM and LTM, scientists have also used neuroimaging to attempt to identify the different brain regions responsible for each form of
memory. Deborah Talmi and colleagues (2005) at the University of Toronto performed an fMRI experiment in which they asked ten volunteers to study a list of 12 words presented one at a time on a computer screen. Next, the computer screen flashed a word and the participants had to determine whether the word was from their study list. The researchers were mostly concerned about the brain activity that occurred when the volunteers correctly recognized words. When volunteers remembered information from early in the serial position curve, the hippocampus was active (this area is associated with the formation of LTM, as you will read about later). By comparison, the brain areas associated with sensory information—hearing or seeing the words—were more active when people recalled items at the end of the serial position curve. Thus, the researchers believed they had isolated the effects of two different neural
systems which, working simultaneously, produce the serial position curve.
Can we critically evaluate the distinction between STM and LTM? In order to evaluate the idea that the serial-position effect is caused by two interacting memory systems, we need at least two types of tests. First, we need to find evidence that it is possible to change the performance on one test but not the other. Then we need to find medical cases in which brain damage affected one system, but not the other. Together, these findings would support the view that STM and LTM stores can be distinguished from each other.
The fact that it is possible to separately affect the primacy and recency effects was demonstrated in the 1950s and 1960s. When items on a list are presented quickly, it becomes more difficult to completely encode those items into long-term memory. The result is a reduction in the primacy effect; however, STM will still contain the most recently presented items, thus leaving the recency effect
unchanged (Murdock, 1962). The recency effect can be reduced by inserting a delay between the presentation of the list and the test. This delay will allow other information to fill up STM; LTM, as
shown by the primacy effect, will be unaffected (Bjork & Whitten, 1974).
Evidence from neurological patients also supports the distinction between STM and LTM. STM deficits can occur after damage to the lower portions of the temporal and parietal lobes, as well as to
lateral (outside) areas of the frontal lobes (Müller & Knight, 2006). In contrast, damage to the hippocampus will prevent the transfer of memories from STM to LTM (Scoville & Milner, 1957). These patients will have relatively preserved memories of their past, but will be unable to add to them with new information from short-term memory.
Why is this relevant? The idea of multiple memory stores is theoretically interesting and can explain some of the minor memory problems we all experience (e.g., forgetting parts of a phone number). But, being able to distinguish between STM and LTM has more wide- reaching implications. The fact that it is possible to separate STM and LTM—and that these stores are driven by different brain systems—suggests that you could use simple tests like the serial- position effect to predict where a neurological patient’s brain damage had occurred. Many common assessment tools such as
the Wechsler Memory Scales (Wechsler, 2009) include tests of both types of memory in order to do just that. Clues uncovered by these initial assessment tests can be used by emergency room physicians and neurologists to assist with their diagnosis and may lead them to request a brain scan for a patient (to look for damage) when they might not otherwise have done so.
The Atkinson-Shiffrin Model provides a very good introduction to the different stages of memory formation. However, memory is much more complex than is implied by this box-and-arrow diagram. There are many instances in which information that we didn’t pay much attention to still seems to influence our later behaviour, suggesting that this information entered our memory without us putting effort into encoding it. For instance, children learn new languages and mimic the behaviours of those around them (i.e., exhibit observational learning) without being able to articulate how or why they do it. Additionally, brain-imaging studies have shown that both encoding and retrieval involve complex networks of interacting brain structures. Throughout the rest of this module, we will move beyond the Atkinson-Shiffrin Model to examine more complex and nuanced aspects of human memory. In the next section, we will discuss working memory, a sophisticated form of STM that involves a number of different, complementary, pieces.
Module 7.1a Quiz:
The Atkinson-Shiffrin Model
Know . . . 1. Which elements of memory do not actually store information, but instead
describe how information may be shifted from one type of memory to another?
A. Serial position processes B. Recency effects C. Primacy effects D. Control processes
2. lasts less than a second, whereas holds information for extended periods of time, if not permanently.
A. Sensory memory; short-term memory B. Short-term memory; sensory memory C. Sensory memory; long-term memory D. Long-term memory; process memory
Apply . . . 3. Chris forgot about his quiz, so he had only 5 minutes to learn 20
vocabulary words. He went through the list once, waited a minute, and then went through the list again in the same order. Although he felt confident, his grade indicated that he missed approximately half of the words. Which words on the list did he most likely miss, and why?
A. According to the primacy effect, he would have missed the first few words on the list.
B. According to the recency effect, he would have missed the last few words on the list.
C. According to the serial position effect, most of the items he missed were probably in the middle of the list.
D. According to the primacy effect, he would have missed all of the words on the list.
Analyze . . . 4. Brain scans show that recently encountered items are processed in one
area of the brain, whereas older items are stored in a different area. Which concept does this evidence support?
A. Multiple memory stores B. A single memory store C. Complex control processes D. Retrieval
The Working Memory Model: An Active STM System
Imagine you are driving a car when you hear the announcement for a radio
contest—the 10th caller at 1-800-555-HITS will win an all-expenses paid trip to Costa Rica! As the DJ shouts out the phone number, panic sets in. You desperately want this prize, but you’re driving—and traffic is swarming. What do you do? As you try to pull over to the side of the road as quickly as you can, you
will probably try to remember the number by using rehearsal , or repeating information (in this case, the number) until you do not need to remember it anymore. Psychological research, however, demonstrates that remembering is much more than just repeating words to yourself (see Module 7.2 ). Instead, keeping information like the radio station’s phone number available is an active process that is much more complex than one would expect.
According to the Atkinson-Shiffrin model of memory, you would attempt to retain the phone number in STM, possibly transferring it to LTM. This process would go smoothly if no other information entered STM, and if traffic cooperated so that you didn’t really have to attend to anything other than the phone number. Of course, the world is rarely that simple. Indeed, in the 1970s, psychologists led by Alan Baddeley suggested that a slightly more complex model of memory was required, one that better explained how memory relates to our moment-to-
moment conscious experiences (Baddeley & Hitch, 1974). The result was a theory of working memory , a model of short-term remembering that includes
a combination of memory components that can temporarily store small amounts of information for a short period of time.
A key feature of working memory is that it recognizes that stimuli are encoded simultaneously in a number of different ways, rather than simply as a single unit of information. Indeed, the classic working memory model for short-term
remembering can be subdivided into three storage components (Figure 7.7 ), each of which has a specialized role (Baddeley, 2001; Jonides et al., 2005): the phonological loop, the visuospatial sketchpad, and the episodic buffer. In the example above, the auditory information from the DJ needs to be remembered so that you can win the trip to Costa Rica (phonological loop). Visual information needs to be remembered so that you can keep track of the traffic patterns while you drive (visuospatial sketchpad). And, while you are juggling these bits of information, you are also linking them together into a mental narrative or story about how you had to pull your car over to try to win an exotic vacation (episodic buffer). These storage components are then coordinated by a control centre
known as the central executive. The central executive helps decide which of the working-memory stores is most important at any given moment (e.g., remembering the phonological information of the phone number). It can also draw from older information that is stored in a relatively stable way to help organize or make sense of the new information.
Figure 7.7 Components of Working Memory Work Together to Manage
Complex Tasks
As you can see, working memory provides a more nuanced model of short-term
memory processes than the Atkinson-Shiffrin model (Cowan, 2008). But is all this additional complexity necessary? Below, we will discuss this model in more detail and show how various research findings support this more complex understanding of memory.
The Phonological Loop
The phonological loop is a storage component of working memory that relies on rehearsal and that stores information as sounds, or an auditory code. It engages some portions of the brain that specialize in speech and hearing, and it can be very active without affecting memory for visual and spatial information. At first glance, it appears similar to the STM store of the Atkinson-Shiffrin model; however, a simple experiment will show you how it differs. Earlier in this module, you read about the magical number 7, the finding that the capacity of STM is
generally 7 ± 2 items. However, research into the word-length effect has shown that people remember more one-syllable words (sum, pay, bar, . . .) than four- or five-syllable words (helicopter, university, alligator, . . .) in a short-term-memory task (Baddeley et al., 1975). Psychologists have found that working memory can only store as many syllables as can be rehearsed in about two seconds, and
that this information is retained for approximately 15 to 30 seconds (Brown, 1958; Peterson & Peterson, 1959). So, in the radio-contest example, you would likely be able to remember the phone number (it can be spoken in under two seconds), but you would need to pull over to use your phone fairly quickly, before the information started to fade away.
Some readers might wonder how the word-length effect and chunking (discussed earlier in this module) can both affect memory. According to early models of
chunking, long words like helicopter and alligator and short words like bar and pay would all be one chunk, whereas the word-length effect suggests that fewer long words would be remembered. Which view is correct? As it turns out, both
can be correct, depending upon how memory is tested. If participants are allowed to recall information in any order, chunking appears to be an important factor. If participants have to recall the information in a particular order, then the
length of the stimuli limits memory (Chen & Cowan, 2005). In the case of remembering the phone number of the radio station in our example, the order of the numbers would obviously be a critical factor.
The Visuospatial Sketchpad
The visuospatial sketchpad is a storage component of working memory that maintains visual images and spatial layouts in a visuospatial code. It keeps you up to date on where objects are around you and where you intend to go. To do so, the visuospatial sketchpad engages portions of the brain related to perception of vision and space and does not affect memory for sounds. Just as the phonological store can be gauged at several levels—that is, in terms of the number of syllables, the number of words, or the number of chunks—items stored in visuospatial memory can be counted based on visual features such as shape, colour, and texture. This leads to an important question: How are these different visual features processed by the visuospatial sketchpad? Do different types of features (e.g., colour vs. shape) get stored separately, or are they integrated into one “chunk”? For example, would a smooth, square-shaped, red block count as one chunk, or three? Research has consistently shown that a square-shaped block painted in two colours is just as easy to recognize as the
same-shaped block painted in one colour (Vogel et al., 2001). Therefore, visuospatial working memory may use a form of chunking. This process of combining visual features into a single unit goes by a different name, however:
feature binding (see Figure 7.8 ).
Figure 7.8 Working Memory Binds Visual Features into a Single Chunk Working memory sometimes stores information such as shape, colour, and texture as three separate chunks, like the three pieces of information on the left. For most objects, however, it stores information as a single chunk, like the box on the right.
After visual feature binding, visuospatial memory can accurately retain approximately four whole objects, regardless of how many individual features one can find on those objects. Perhaps this is evidence for the existence of a
second magical number—four (Awh et al., 2007; Vogel et al., 2001).
To put feature binding into perspective, consider the amount of visual information available to you when you are driving a car, as in the story that started this section. If you are at the wheel, watching traffic, you probably would not look at a car in front of you and remember images of red, shiny, and smooth. Instead, you would simply have these features bound together in the image of the car, and you would be able to keep track of three or four such images without much problem as you glance at the speedometer and then back to the traffic around you. It is also possible that you might group together several cars into one visual chunk (e.g., the six cars you can see directly in front of you); it is likely that our expertise with situations will allow us to alter the size of the chunks in this component of working memory.
The Episodic Buffer
Recent research suggests that working memory also includes an episodic buffer —that is, a storage component of working memory that combines the images and sounds from the other two components into coherent, story-like episodes. These episodes allow you to organize or make sense of the images and sounds, such as “I was driving to a friend’s house when I heard the radio DJ give a number to call.”
The episodic buffer is the most recently hypothesized working memory system
(Baddeley, 2001). It seems to hold 7 to 10 pieces of information, which may be combined with other memory stores. This aspect of its operation can be demonstrated by comparing memory for prose (words strung into sentences) to memory for unrelated words. When people are asked to read and remember
meaningful prose, they usually remember 7 to 10 more words than when reading a random list of unrelated words. Some portion of working memory is able to connect the prose with information found in LTM (“knowledge”) to increase memory capacity.
The Central Executive
Finally, working memory includes one component that is not primarily used for
storing information. Instead, the central executive is the control centre of working memory; it coordinates attention and the exchange of information among the three storage components. It does so by examining what information is relevant to the person’s goals, interests, and prior knowledge and then focusing attention on the working memory component whose information will be most useful in that situation. For example, when you see a series of letters from a familiar alphabet, it is easy to remember the letters by rehearsing them in the phonological loop. In contrast, if you were to look at letters or characters from a foreign language, you may not be able to convert them to sounds; thus you
would assign them to the visuospatial sketchpad instead (Paulesu et al., 1993). Regions within the frontal lobes of the brain are responsible for carrying out these tasks for the central executive.
Working Memory: Putting the Pieces Together
Thus far, we’ve talked about the different pieces of working memory as separate functions. In reality, however, these pieces would work together to influence what information you are able to remember. So how do these four components of the working-memory system work for you when you cannot pull your car over immediately to place the 10th call to win the trip to Costa Rica? Most of us would rely on our phonological loop, repeating the number 1-800-555-HITS to ourselves until we can call. Meanwhile, our visuospatial sketchpad is remembering where other drivers are in relation to our car, even as we look away to check the speedometer, the rearview mirror, or the volume knob. Finally, the episodic buffer binds together all this information into episodes, which might include information such as “I was driving to school,” “the DJ announced a contest,” and “I wanted to pull over and call the station.” In the middle of all this activity is the central executive, which guides attention and ensures that each component is working on the appropriate task. So, if a bus suddenly changed lanes in front of you, the central executive would focus more on the visuospatial sketchpad until you were sure that you were safe; then it would again focus on the phonological loop. Thus, although your memories often seem almost automatic, there is actually a lot of work being performed by your working memory.
Module 7.1b Quiz:
The Working Memory Model: An Active STM System
Know . . . 1. Which of the following systems maintains information in memory by
repeating words and sounds?
A. Episodic buffer B. Central executive C. Phonological loop D. Visuospatial sketchpad
2. Which of the following systems coordinates attention and the exchange of information among memory storage components?
A. Episodic buffer B. Central executive C. Phonological loop D. Visuospatial sketchpad
Apply . . . 3. When Nick looks for his friend’s motorcycle in a parking lot, he sees a
single object, not two wheels, a seat, and a red body. This is an example
of . A. a phonological loop B. feature binding C. buffering D. proactive interference
Long-Term Memory Systems: Declarative and Nondeclarative Memories
Figure 7.1 at the beginning of this module suggests that humans have just one type of long-term memory (LTM). However, as you read in the story about the neurological patient K.C., LTM has a number of different components. K.C. could learn new skills, draw maps, and remember basic facts. Yet, he was
unable to recall specific episodes in his own life (Tulving & Markowitsch, 1998). What do cases like K.C.’s tell us about the organization of LTM?
One way to categorize LTM is based on whether or not we are conscious of a
given memory (see Figure 7.9 ). Specifically, declarative memories (or explicit memories ) are memories that we are consciously aware of and that can be verbalized, including facts about the world and one’s own personal experiences; an easy way to remember this is that declarative memories are, handily, about things we can declare. In contrast, nondeclarative memories (or implicit memories
) include actions or behaviours that you can remember and perform without awareness; that is, these are memories about things that we cannot declare. But, this initial division only scratches the surface of LTM’s complexity. Both declarative and nondeclarative memories have multiple subtypes, each with its own characteristics and brain networks.
Figure 7.9 Varieties of Long-Term Memory Long-term memory can be divided into different systems based on the type of information that is stored.
Declarative Memory
Declarative memory comes in two varieties (Tulving, 1972). Episodic memories are declarative memories for personal experiences that seem to be organized around “episodes” and are recalled from a first-person (“I” or “my”) perspective. Examples of episodic memories would be your first day of university, the party you went to last month, and that time you remember
watching the Olympics on TV. Semantic memories , on the other hand, are declarative memories that include facts about the world. Examples of semantic memories would include knowing that Fredericton is the capital of New Brunswick, remembering that your mother’s birthday is April 6th, and that bananas are (generally) yellow. The two types of memory can be contrasted in an example: Your semantic memory is your knowledge of what a bike is,
whereas episodic memory is the memory of a specific time when you rode a bike. It is worth clarifying that both episodic and semantic memory
representations can be active at the same time. If someone asks you, “Can you ride a bike?”, you will likely think of both semantic information about bikes as well as episodic instances in which you rode one. But, there are also instances in which only one type of memory can be active, such as if someone asked you if you had ever piloted a space shuttle. The term “space shuttle” would activate semantic memory but, unless you are one of the ten Canadians who have been in space, it would not activate episodic memories of you flying through the atmosphere.
The case of K.C. provides compelling evidence that semantic and episodic memories are distinct forms of declarative memory. Although K.C. had no specific memories of events that took place in his high school or his house, he did understand that he had attended high school and that he lived in a specific home in Mississauga, ON. However, K.C. is not the only example of the distinction between these types of memory. Studies of older adults have noted that they show similar (but much less severe) impairments to K.C. on memory tests. As people get older, their episodic memory declines more rapidly than their
semantic memory (Luo & Craik, 2008). Older people are more likely to forget going on vacation five years ago than they are to forget something like the
names of provincial capitals (Levine et al., 2002). Interestingly, they also show normal performance on a number of tests related to nondeclarative memories.
Nondeclarative Memory
Nondeclarative memory occurs when previous experiences influence performance on a task that does not require the person to intentionally
remember those experiences (Graf & Schacter, 1985). The earliest published report of this form of memory came in 1845 when a British physician named
Robert Dunn described the details of a woman with amnesia (Schacter, 1985). This woman learned how to make dresses following her injury, but had no conscious memory of learning to do so. A more pointed example was published
in the early 20th century by Claparède (1911/1951). He reported on an amnesic
woman who learned not to shake his hand because he had previously stuck her with a pin attached to his palm. In both cases, the behaviours of patients with no conscious memories were altered because of previous experiences, thus suggesting that this previous information was encoded into LTM in some form.
But, nondeclarative memories are not isolated to cases of amnesia. You have thousands of nondeclarative memories in your brain right now. However, these two historical examples provide nice examples of two common forms of nondeclarative memories. The example of a woman being able to sew dresses is
an example of a procedural memory , a pattern of muscle movements (motor memory) such as how to walk, play piano, tie your shoes, or drive a car. We often don’t think of the individual steps involved in these behaviours, yet we execute them flawlessly most of the time.
The patient learning not to shake hands with the physician who had a pin
attached to his hand is an example of classical conditioning, when a previously neutral stimulus (e.g., the sound of a metronome) produces a new response (e.g., salivating) because it has a history of being paired with another stimulus that produces that response (e.g., food). Although these associations can sometimes be consciously recalled, this recollection is not necessary for
conditioning to successfully take place (see Module 6.1 ).
Module 7.1c Quiz:
Long-Term Memory Systems: Declarative and Nondeclarative Memories
Know . . . 1. Memories learned without our awareness of them are known as
. A. semantic memories B. episodic memories C. nondeclarative memories D. declarative memories
2. Memories that can be verbalized, whether they are about your own
experiences or your knowledge about the world, are called . A. nondeclarative memories B. procedural memories C. conditioned memories D. declarative memories
Apply . . . 3. Mary suffered a head injury during an automobile accident and was
knocked unconscious. When she woke up in a hospital the next day, she could tell that she was in a hospital room, and she immediately recognized her sister, but she had no idea why she was in the hospital or how she got there. Which memory system seems to be affected in Mary’s case?
A. Semantic memories B. Episodic memories C. Nondeclarative memories D. Working memories
The Cognitive Neuroscience of Memory
Many psychologists who are interested in memory examine it from a biological perspective, examining how the nervous system changes with the formation of new memories. To explore the cognitive neuroscience of memory, we will take a brief look at the neuronal changes that occur as memories are forming and strengthening, and will then examine the brain structures involved in long-term storage. Finally, we will use examples from studies of amnesia and other forms of memory loss to understand how our memory models fit with biological data.
Memory At the Cellular Level
Memory at the cellular level can be summed up in the following way: Cells that fire together, wire together. This idea was proposed in the 1940s by Canadian neuroscientist Donald Hebb. Specifically, he suggested that when neurons fire at
the same time, it leads to chemical and physical changes in the neurons, making
them more likely to fire together again in the future (Hebb, 1949). Later research proved Hebb correct, and demonstrated that changes occur across numerous
brain cells as memories are forming, strengthening, and being stored (Lømo, 1966). This process, long-term potentiation (LTP) , demonstrated that there is an enduring increase in connectivity and transmission of neural signals between nerve cells that fire together.
The discovery of LTP occurred when researchers electrically stimulated two neurons in a rabbit’s hippocampus—a key memory structure of the brain located
in an area called the medial temporal lobes (see Figure 7.10 ). Stimulation of the hippocampus increased the number of electrical potentials from one neuron
to the other. Soon, the neurons began to generate stronger signals than before, a change that could last up to a few hours (Bliss & Lømo, 1973). This finding does not mean that LTP is memory—no one has linked the strengthening of a particular synapse with a specific memory like your first day of university. In fact, no one has seen LTP outside of a laboratory. But, the strengthening of synapses shown in LTP studies may be one of the underlying mechanisms that allow memories to form.
Figure 7.10 The Hippocampus
The hippocampus resides within the temporal lobe and is critical for memory processes.
To see how such microscopic detail relates to memory, consider the very simple case of learning and remembering discussed in a previous module: eyeblink conditioning. Imagine you hear a simple tone right before a puff of air is blown in your eye; you will reflexively blink. After two or three pairings, just the tone will be enough to cause an eye blink—this is an example of classical conditioning (see Module 6.1 ). At the neural level, the tone causes a series of neurons to respond, and the puff of air causes another series of neurons to respond. With repeated tone and air puff pairings, the neurons that are involved in hearing the tone, and those that control the blinking response, develop a history of firing together. This simultaneous activation provides the opportunity for synapses to become strengthened, representing the first stages of memory.
This relationship is not permanent, however. Lasting memories require consolidation , the process of converting short-term memories into long-term memories in the brain, which may happen at the level of small neuronal groups or across the cortex (Abraham, 2006). When neurons fire together a number of times, they will adapt and make the changes caused by LTP more permanent—a
process called cellular consolidation. This process involves physical changes to the synapse between the cells so that the presynaptic cell is more likely to
stimulate a specific postsynaptic cell (or group of cells). Without the consolidation process, the initial changes to the synapse (LTP) eventually fade away, and presumably so does the memory. (This process can therefore be summed up with the saying: Use it or lose it.) To demonstrate the distinction between the initial learning and longer-term consolidation, researchers administered laboratory rats a drug that allowed LTP, but prevented consolidation from occurring (by blocking biochemical actions). The animals were able to learn a task for a brief period, but they were not able to form long-term memories. By comparison, rats in the placebo group, whose brains were able to consolidate the information, went through the same tasks and formed long-term memories
without any apparent problems (Squire, 1986).
The initial strengthening of synapses (LTP) and longer-term consolidation of these connections allow us to form new memories, thus providing us with an ability to learn and to adapt our behaviour based on previous experiences. However, these processes are not performed in all areas of the brain. Instead, specific structures and regions serve essential roles in allowing us to form and maintain our memories, a fact powerfully demonstrated by the memory deficits of patients with amnesia.
Memory, the Brain, and Amnesia
On August 31, 1953, Henry Molaison was a 27-year-old man with intractable epilepsy. Because his seizures could not be controlled by medications, Mr. Molaison had been referred to Dr. William Scoville, a respected Hartford-based neurosurgeon, for treatment. Dr. Scoville and his colleagues had suggested that removing the areas of Molaison’s brain that triggered the seizures would cure, or at least tame, his epilepsy. On September 1, 1953, Henry Molaison underwent a resection (removal) of his medial temporal lobes—including the hippocampus— on both sides of his brain. After that day, he became known to the world as neurological patient H.M.
H.M.’s surgery was successful in that he no longer had seizures. However, as he recovered from his surgery, it became apparent that the procedure had produced some unintended consequences. The doctors quickly determined that H.M. had amnesia —a profound loss of at least one form of memory. However, not all of his memories were lost; in fact, numerous studies conducted by Brenda Milner of McGill University demonstrated that H.M. retained many forms of memory
(Milner, 1962; Scoville & Milner, 1957). He was able to recall aspects of his childhood. He could also remember the names of the nurses who had treated him before the surgery, although he was unable to learn the names of nurses he met afterward. Indeed, H.M. appeared unable to encode new information at all. Therefore, H.M. was experiencing a specific subtype of amnesia known as anterograde amnesia , the inability to form new memories for events occurring after a brain injury.
H.M.’s anterograde amnesia was not due to problems with his sensory memory
or his STM. Both abilities remained normal throughout his life (Corkin, 2002). He was also able to recall details of his past, such as incidents from his school years and from jobs he had held before his surgery; this demonstrates that his LTM
was largely intact (Milner et al., 1968). He was also able to form new implicit memories—he was able to learn new skills such as drawing a picture by looking at its reflection in the mirror despite the fact that he had no memory for learning
this skill (Milner, 1962). Similar improvements were found for solving puzzles (Cohen et al., 1985). After extensive testing, researchers concluded that H.M.’s amnesia was not due to problems with a particular memory store, but was instead due to problems with one of the control processes associated with those stores. Specifically, H.M. could not transfer declarative memories from STM into LTM.
The fact that H.M.’s brain damage was due to a precise surgical procedure (rather than to widespread damage from an accident like patient K.C.) allowed researchers to pinpoint the area of the brain responsible for this specific memory problem. H.M. was missing the medial temporal lobes of both hemispheres. This damage included the hippocampus and surrounding cortex as well as the amygdala. Based on H.M. and several similar cases, researchers concluded that this region of the brain must be involved with consolidating memories (see Figure 7.11 ), enabling information from STM to enter and remain in LTM, a process that most of us take for granted.
Figure 7.11 Damage to the Hippocampus: Disruption of Consolidation When the hippocampus is damaged, the injury interferes with consolidation, the
formation of long-term memories. Such damage does not prevent recall of pre- existing memories, however.
The hippocampus also appears to be essential for spatial memories such as remembering the layout of your house or recalling the route you would take to get to a friend’s apartment. In fact, brain-imaging studies suggest that the size of a person’s hippocampus can vary with the amount of spatial information that people are asked to consolidate. Researchers at King’s College London (U.K.) examined the brains of taxi drivers in that maze-like city and compared them to the brains of age-matched control participants. The taxi drivers, who were required to undergo extensive training and to memorize most of London, had
substantially larger hippocampi than did the control participants (Maguire et al., 2000). This result implies that the demanding memory requirements of that job altered the structure of brain areas related to memory consolidation and spatial memory.
Stored Memories and the Brain
It is important to note that our long-term memories do not just sit on a
neurological shelf and collect dust after they have formed. Memory storage
refers to the time and manner in which information is retained between encoding and retrieval. In other words, memory storage is an active process; stored memories can be updated regularly, such as when someone reminds you of an event from years ago, or when you are reminded of information you learned as a
child. In this way, memories undergo a process called reconsolidation, in which the hippocampus functions to update, strengthen, or modify existing long-term
memories (Lee, 2010; Söderlund et al., 2012). These memories then form networks in different regions of the cortex, where they can (sometimes) be retrieved when necessary. These long-term declarative memories are distributed throughout the cortex of the brain, rather than being localized in one region—a
phenomenon known as cross-cortical storage (Paller, 2004). Interestingly, with enough use, some of the memory networks will no longer need input from the hippocampus. The cortical networks themselves will become self-sustaining. The more that memory is retrieved, the larger and more distributed that network will
become.
Researchers in London found that the hippocampi of taxi drivers, who navigate the complex maze of the city, are larger than the hippocampi of non-taxi drivers
(Maguire et al., 2000). Kamira/Shutterstock
Memories that were recently formed and have not had time to develop extensive cross-cortical networks are much more likely to be lost following a head injury than are older memories. Indeed, many people who have experi enced a brain injury—including concussions—report that they cannot recall some of the events
leading up to their accident. This type of memory deficit is known as retrograde amnesia , a condition in which memory for the events preceding trauma or injury is lost (see Figure 7.12 ). Despite what you might see on soap operas, the “lost time” is generally limited to the seconds or minutes leading up to the injury. The loss of extensive periods of time, as seen in K.C., is quite rare.
Figure 7.12 Retrograde and Anterograde Amnesia The term amnesia can apply to memory problems in both directions. It can wipe out old memories, and it can prevent consolidation of new memories.
The fact that memories can be lost after even minor brain damage shows us that our memory systems are quite delicate. Each of the boxes and arrows in the
Atkinson-Shiffrin model (Figure 7.1 ) can be disrupted in some way; but, the formation and storage of long-term memories seems to be particularly sensitive to injuries. K.C.’s devastating injury shows us that when we lose our memories, we lose an important part of ourselves. So be careful.
Module 7.1d Quiz:
The Cognitive Neuroscience of Memory
Know . . . 1. is a process that all memories must undergo to become long-
term memories.
A. Consolidation B. Retrieval C. Amnesia D. Chunking
Understand . . .
2. Long-term potentiation can be described as A. a decrease in a neuron’s electrical signalling. B. neurons generating stronger signals than before, which then
persist.
C. decreased neural networking. D. an example of working memory.
Apply . . . 3. Damage to the hippocampus is most likely to produce .
A. retrograde amnesia B. consolidation C. anterograde amnesia D. seizures
Module 7.1 Summary
amnesia
anterograde amnesia
attention
central executive
chunking
consolidation
control process
declarative (explicit) memory
echoic memory
encoding
episodic buffer
episodic memory
Know . . . the key terminology of memory systems:7.1a
iconic memory
long-term memory (LTM)
long-term potentiation (LTP)
nondeclarative (implicit) memory
phonological loop
proactive interference
procedural memory
rehearsal
retrieval
retroactive interference
retrograde amnesia
semantic memory
sensory memory
serial position effect
short-term memory (STM)
storage
stores
tip-of-the-tongue (TOT) phenomenon
visuospatial sketchpad
working memory
Understand . . . which structures of the brain are associated with specific memory tasks and how the brain changes as new memories form.
7.1b
The hippocampus is critical to the formation of new declarative memories. Long- term potentiation at the level of individual synapses between nerve cells is the basic mechanism underlying this process. Long-term memory stores are distributed across the cortex. Working memory likely utilizes the parts of the brain associated with visual and auditory perception, as well as the frontal lobes (for functioning of the central executive).
Apply Activity Try responding to these questions for practice:
1. Dr. Richard trains a rat to navigate a maze and then administers a drug that blocks the biochemical activity involved in long-term potentiation. What will happen to the rat’s memory? Will it become stronger? Weaker? Or is it likely the rat will not remember the maze at all?
2. In another study, Dr. Richard removes a portion of the rat’s hippocampus one week after it learns to navigate a maze. What will happen to the rat’s memory? Will it become stronger? Weaker? Or will it be unaffected by the procedure?
Consider all the evidence from biological and behavioural research, not to mention the evidence from amnesia. Data related to the serial position effect indicate that information at the beginning and end of a list is remembered differently, and even processed and stored differently in the brain. Also, evidence from amnesia studies suggests that LTM and STM can be affected separately by brain damage or disease. Most psychologists agree that these investigations provide evidence supporting the existence of multiple storage systems and control processes.
Apply . . . your knowledge of the brain basis of memory to predict what types of damage or disease would result in which types of memory loss.
7.1c
Analyze . . . the claim that humans have multiple memory systems.7.1d
Module 7.2 Encoding and Retrieving Memories
Tkreykes/Fotolia
Learning Objectives
Know . . . the key terminology related to forgetting, encoding, and retrieval. Understand . . . how the type of cognitive processing employed can affect
7.2a
7.2b
According to legend, the first person to develop methods of improving memory was the Greek poet Simonides of Ceos (556–468 BCE). After presenting one of his lyric poems at a dinner party in northern Greece, the host, Scopas, told him that he was only going to pay half of the cost of the poem (he clearly wasn’t impressed by the work). Soon after this exchange, a grumpy Simonides was told that two men on horses wanted to talk to him outside. While talking to the horsemen, the roof of Scopas’ house collapsed, killing everyone inside (Greek legends are not happy places…). When relatives wanted to bury the family, they were unable to figure out who the remains belonged to; no one could recall where the family members had been sitting. Simonides had encoded the information differently than the rest of the guests; he was able to assist the family by creating a visual image of the dinner party and listing who was sitting in each chair. His story demonstrates one of the key points to be discussed in this module—that how you encode information affects the likelihood of you remembering that information later.
Focus Questions
1. What causes some memories to be strong while others are weak?
2. How can we improve our memory abilities?
Why are some memories easier to recall than others? Why do we forget things? How can you use memory research to improve your performance at school and at work? These questions are addressed in this module, where we focus on
the chances of remembering what you encounter. Apply . . . what you have learned to improve your ability to memorize information. Analyze . . . whether emotional memories are more accurate than non- emotional ones.
7.2c
7.2d
factors that influence the encoding and retrieval of memories.
Encoding and Retrieval
In its simplest form, memory consists of encoding new information, storing that information, and then retrieving that stored information at a later time. As
discussed in Module 7.1 , encoding is the process of transforming sensory and perceptual information into memory traces, and retrieval is the process of accessing memorized information in order to make use of it in the present
moment. In between these two processes is the concept of storage, the time and manner in which information is retained between encoding and retrieval. Over the past fifty years, researchers have uncovered a number of factors that influence how our memory systems work, and also how we can improve our chances of remembering information. The most important of these factors appears to be how the information was encoded in the first place.
Rehearsal: The Basics of Encoding
What would you do if someone gave you the address for a house party but you didn’t have a pen or your phone around? How would you keep the address in mind until you had a chance to write it down? If you’re like most people, you will recite the address over and over again until you can write it down. This type of memorization is known as rehearsal to psychologists (although your teachers
may have called it learning by rote), and it is something probably all of us have tried. Indeed, students often try to learn vocabulary terms by reading flashcards with key terms and definitions over and over. But is this strategy effective?
Certainly this approach works some of the time, but is it really the most effective way to remember? Unfortunately for all the cue-card-memorizing students out
there, the answer is a resounding “no” (Craik & Watkins, 1973). The limitations of this form of rehearsal were shown in a sneaky experiment performed in the
1970s (see Figure 7.13 ); in this study, participants were asked to remember a four-digit number. After seeing the number, they were asked to repeat a single
word until being prompted to report the number. The delay between the presentation of the number and the participants’ responses varied from 2 to 18 seconds; this meant that the amount of time each word was repeated also varied. Because participants were trying to remember the digits, they barely paid attention to the word they repeated. Later, when the researchers surprised the participants by asking them to recall the distracting word they had repeated, they found virtually no relationship between the duration of rehearsal (between 2 and 18 seconds) and the proportion of individuals who could recall the word
(Glenberg et al., 1977). In other words, longer rehearsal did not lead to better recall. This is not to say that repeating the word had no effect at all; rather, this study demonstrated that repeating information only had a small benefit, and that this benefit was not increased with longer rehearsal times.
Figure 7.13 Rote Rehearsal Has Limited Effects on Long-Term Memory After participants completed the procedure depicted in this figure, they were given a surprise test of their memory for the words that they had recited. There was no difference in the recall of words rehearsed for 2 or 18 seconds. This result suggests that simply repeating the word—maintenance rehearsal—has a limited effect on our memory.
It turns out that it is not how long we rehearse information, but rather how we rehearse it that determines the effectiveness of memory. Individuals in the study
just described were engaged in maintenance rehearsal —prolonging exposure to information by repeating it—which does relatively little to help the formation of long-term memories (although it is better than nothing). By
comparison, elaborative rehearsal —prolonging exposure to information by thinking about its meaning—significantly improves the process of encoding (Craik & Tulving, 1975). For example, repeating the word bottle, and then imagining what a bottle looks like and how it is used, is an elaborative technique. In the story that began this module, Simonides used a form of elaborative rehearsal by not only memorizing a list of people at a table (Scopus, Constantine, Helena, etc.), but actively imagining the dinner table and thinking about where people were relative to each other.
Although maintenance rehearsal helps us remember for a very short time, elaborative rehearsal improves long-term learning and remembering. It is worth paying attention to this research and thinking about how it applies to your success as a student (a form of elaborative rehearsal of this information). Obviously, being a student involves encoding a large amount of information into your memory in a relatively small amount of time. Imagine how the two types of rehearsal may come into play in meeting the challenge of university-level learning. Students who simply memorize key terms and repeat the definitions largely fail to employ elaborative rehearsal, and are less likely to do well on an exam. The wise strategy is to try to elaborate on the material.
Levels of Processing
Although we often find ourselves using maintenance rehearsal “in a pinch,” we rarely use that strategy for information that we intend to remember much later. Instead, we focus on elaborative encoding, where additional sensory or semantic (meaning) information is associated with the to-be-remembered item. But, not all elaborative encoding is created equal. Instead, different types of elaborative encoding can produce markedly different levels of recall. The details surrounding this variability were first described by researchers at the University of Toronto,
and led to a framework for memory known as levels of processing (LOP).
The LOP framework begins with the understanding that our ability to recall
information is most directly related to how that information was initially processed
(Craik & Lockhart, 1972). Differences in processing can be described as a continuum ranging from shallow to deep processing. Shallow processing , as you might guess, involves more superficial properties of a stimulus, such as the sound or spelling of a word. Deep processing , on the other hand, is generally related to an item’s meaning or its function. The superiority of deep processing was demonstrated in a study in which participants encoded words
using shallow processing (e.g., “Does this word rhyme with dust?. . . TRUST”) or deep processing (e.g., “Is this word a synonym for locomotive?. . .TRAIN”). When given a surprise memory test for the words, the differences ranged from recalling as few as 14% of the shallow words to 96% of the deeply processed
words (Craik & Tulving, 1975). In essence, they were almost seven times more likely to recall a deeply processed word than one that was processed at only a shallow level. Importantly, such effects are limited to LTM; STM memory rates
are unaffected by shallow or deep processing (Rose et al., 2010; Figure 7.14 ).
Figure 7.14 Levels of Processing Affect Long-Term Memory, but Not Working Memory When tested immediately after studying words, levels of processing do not seem to affect memory. In contrast, when there is a gap between studying words and being tested, levels of processing are important. When words are encoded based on their meaning (semantics), they are better retained in long-term memory. Source: Similarities and diferences between working memory and longterm memory: Evidence from the levels-of-processing
span task. Journal of Experimental Psychology: Learning, Memory, and Cognition, 36 (2), 471–483.
Similar effects have been found for another form of deep processing. The self- reference effect occurs when you think about information in terms of how it relates to you or how it is useful to you; this type of encoding will lead to you remembering that information better than you otherwise would have (Symons & Johnson, 1997). This outcome is not terribly surprising, but it is still helpful to think about when learning new material. The self-reference effect is one of the reasons why your psychology professor (and this textbook) tries to show you how psychological concepts relate to your life—linking a concept to “you” will help you remember it later.
Although encoding strategies clearly influence our ability to remember information later, they only tell part of the story. The conditions in which we attempt to retrieve information from memory can also affect whether or not that information will be recalled.
Retrieval
Once information is encoded—be it in a deep or shallow fashion—and stored in memory, the challenge is then to be able to retrieve that information when it is needed. There are two forms of intentional memory retrieval, both of which are
familiar to long-suffering students like the readers of this textbook. Recognition
involves identifying a stimulus or piece of information when it is presented to you. Examples of recognition memory would be identifying someone you know on the bus (or in a police lineup), or answering standard multiple-choice test questions.
Recall involves retrieving information when asked, but without that information being present during the retrieval process. Examples of this would be describing a friend’s appearance to someone else or answering short-answer or essay questions on an exam.
Recall is helped substantially when there are hints, or retrieval cues, that help prompt our memory. The more detailed the retrieval cue, the easier it is for us to produce the memory. For instance, if you were given a list of 30 words to remember, it is unlikely that you would be able to recall all of the words. But, if you were given a hint for a “forgotten” word, such as “gr—” for the word “grape,” you would be likely to retrieve that information. The hint “grap-” would provide even more information than “gr—” and would lead to even better retrieval
(Tulving & Watkins, 1975). However, life is not a series of word lists. Instead, retrieval cues in the real world often involve places, people, sights, and sounds— in other words, the environment or context in which you are trying to retrieve a
memory. Researchers have found that retrieval is most effective when it occurs in the same context as encoding, a tendency known as the encoding specificity principle (Tulving & Thompson, 1973).
The encoding specificity principle can take many forms. It can include internal contexts such as mood and even whether a person is intoxicated or not. As you’ll see in the next section, encoding specificity can also include external contexts such as the physical setting.
Working the Scientific Literacy Model Context- Dependent Memory
One of the most intuitive forms of encoding specificity is context- dependent memory , the idea that retrieval is more effective when it takes place in the same physical setting (context) as encoding. But, what elements of the environment make up “context”? Is one sense (e.g., smell) enough to produce this effect? And, does context specificity affect all types of memory
equally?
What do we know about context-dependent memory? The initial demonstrations of context-dependent learning and memory used very simple cues: words. In such studies, participants learned pairs of words; some of the words might be
associated with each other (e.g., bark – dog) and others might rhyme with each other (e.g., worse – nurse). A recall test for the second words in each pair (e.g., dog or nurse) generally led to respectable memory performance. However, performance improved when the original context (the first word of the word pair) was reinstated and could serve as a retrieval cue; the more information from the original context that was included, the better
the level of retrieval (Tulving & Watkins, 1975).
Subsequent studies have focused on the role of environmental contexts on memory. In a classic study, members of a scuba club volunteered to memorize word lists—half of the test participants did so while diving 20 feet (6.7 m) underwater, and half did so
while on land (Godden & Baddeley, 1975). After a short delay, the divers were tested again; however, some of the experimental participants had switched locations. This led to four test groups: trained and tested underwater, trained and tested on dry land, trained underwater but tested on land, and trained on land but
tested underwater. As you can see in Figure 7.15 , the results demonstrated that context affects memory. Those who were tested in the same context as where encoding took place (i.e., land–land or underwater–underwater) remembered approximately 40% more items than those who switched locations (i.e., land–underwater or underwater–land). Thus, both controlled laboratory studies and studies involving dramatic environmental manipulations have shown that matching the encoding and retrieval contexts leads to better recall of studied material.
Figure 7.15 Context-Dependent Learning
Divers who encoded information on land had better recall on land than underwater. Divers who encoded information underwater had the reverse experience, demonstrating better recall underwater than when on land. Source: Lilienfeld, Scott O.; Lynn, Steven J; Namy, Laura L.; Woolf, Nancy J., Psychology: From
Inquiry To Understanding, 2nd Ed., © 2011. Reprinted and Electronically reproduced by permission of
Pearson Education, Inc., New York, NY.
How can science explain context-dependent memory? Context-dependent memory clearly demonstrates that the characteristics of the environment can serve as retrieval cues for
memory. In the Godden and Baddeley (1975) study above, the primary cue was likely the feeling of being underwater; however, diving also involves a change of lighting as well as the sounds of the breathing apparatus. In other words, when we encode information, we are also encoding information from a number of different senses (vision, hearing, touch, etc.). Presumably, each of these senses can help trigger memories. For instance, most of you have had the experience where an odour (e.g., cookies) instantly brings back memories (e.g., your grandmother’s
kitchen). This common phenomenon was tested in a clever experiment by researchers in the U.K. In this study, researchers tested whether memory for a Viking museum in York, U.K., could be enhanced if the memory test occurred in a room with a similar distinctive set of smells as the museum (burned wood, apples, garbage, beef, fish, rope/tar, and earth . . . perhaps the Viking equivalent of Axe body spray). The researchers found that participants produced more accurate memories for the museum when the smell of the test room matched the smell of the
museum (Aggleton & Waskett, 1999). Similar results have been found for the effect of smells on memory for word lists (Stafford et al., 2009). Context-dependent memory has also been found for the flavour of gum being chewed during encoding and retrieval
(Baker et al., 2004) as well as for the amount of background noise when students are studying and taking a test (Grant et al., 1998). These results suggest that matching the physical and sensory characteristics of the encoding and retrieval environments affect memory, likely due to the retrieval cues provided by these attributes.
Brain-imaging studies have also provided evidence in favour of context-dependent memory. Studies using fMRI have found increased activity in the hippocampus and parts of the prefrontal cortex (part of the frontal lobes) when the retrieval conditions
match the context in which the memory was encoded (Kalisch et al., 2006; Wagner et al., 1998). Activity in the right frontal lobes is particularly sensitive to context, likely because this region is
known to be critical for the retrieval process (Tulving et al., 1994).
Can we critically evaluate this evidence? Although there is evidence that context-dependent memory exists, there are some important limitations to these effects. First, not all types of memory are equally enhanced by returning a person to the context in which he or she encoded the to-be-
remembered information. Recognition memory (e.g., multiple- choice questions) is not significantly helped by context; this is likely due to the fact that the presence of the item (e.g., a photograph or one of the options on a test question) serves as a very strong retrieval cue. Context does not add much above and
beyond this cue (Fernández & Alonso, 2001). Recall, on the other hand, requires you to generate the to-be-remembered information without any external cues. In this case, returning to the encoding context could help prompt a memory. A second, and related, limitation of context-dependent memory is that not all types of information are equally affected. Information that is central to a memory episode (e.g., a person’s face in a photograph or in a conversation) is generally unaffected by context. Peripheral information (e.g., the faces of people who were nearby when you were having a conversation) does seem to be enhanced when a person returns to the original context
(Brown, 2003; Sutherland & Hayne, 2001). As a rule, when memory for information is quite good, context will have little effect on accuracy; however, when memory is relatively poor, then returning to the encoding context can improve recall.
There is one additional issue related to context-dependent memory. Researchers at Simon Fraser University have noted that returning a person to the context in which he encoded information
can improve recall and increase the number of false positives (i.e., saying “I remember” to stimuli that were never seen). Wong and Read (2011) showed participants a video of a staged crime; viewing took place in either a large testing room or a small study room. Participants returned one week later for a follow-up test in which they were asked to identify the culprit from a photo lineup. This test took place either in the same room as the initial viewing of the video or in the opposite room. The catch was that for half of the participants, the photo lineup did not include the person from the original video (the “target absent condition”). The results of the test demonstrated the effect of context: Performance was
much higher when the testing took place in the same room as the initial encoding. However, participants who took the test in the same context as they saw the video were also more likely to
claim that a photo looked familiar even in the target-absent condition (see Figure 7.16 ). Returning to the encoding context may therefore alter a person’s threshold for saying “I remember.” This trend is likely due to the retrieval cues associated with the environment leading to a feeling of familiarity that is mistakenly
attributed to the to-be-remembered information (Leboe & Whittlesea, 2002), in this case the face of a criminal. This study has clear implications for police procedures, as many police departments encourage returning witnesses to the scene of a
crime in order to improve their memories (Hershkowitz et al., 1998; Kebbel et al., 1999).
Figure 7.16 False Familiarity and Context- Dependent Memory
In a study involving the identification of a thief in a staged robbery, participants viewed a robbery and then later selected the thief from a lineup of photographs. If both stages of the study were performed in the same room (i.e., the context had been reinstated), identification of the thief increased. However, we
should also keep in mind that participants were also more likely to
rate an incorrect face as being familiar; this is shown by the lower accuracy score for the Same than for the Different contexts in the Target Absent condition on the right. Source: From Positive and negative effects of physical context reinstatement on eyewitness recall
and identification. Applied Cognitive Psychology, 25, 2-11. Figure 2 (p. 7), 2009 by Carol K. Wong, J.
Don Read. Copyright © 2009 by John Wiley & Sons, Inc. Reproduced by permission of John Wiley &
Sons, Inc.
Why is this relevant? One of the most interesting implications of context-dependent memory research is that it implies that some forgotten information is not gone forever, but is instead simply inaccessible because
the proper cues have not been provided (Tulving, 1974). This is the assumption made by police investigators who return witnesses to the scene of the crime. It’s also similar to some memory-improvement strategies such as the mental imagery technique used by Simonides in the story at the beginning of this
module. However, the results of the Wong and Read (2011) photo lineup story do suggest that we need to be cautious in our interpretation of context-dependent memory, as the retrieval cues associated with the context could actually lead to false feelings of familiarity that could have devastating effects on people’s lives.
It is usually not difficult to spot these context effects while they are occurring. Almost everyone has had the experience of walking into a room to retrieve something—maybe a specific piece of mail or a roll of tape—only to find that they have no idea what they intended to pick up. We might call this phenomenon
context-dependent forgetting, if we believe the change in the environment influenced the forgetting. It is certainly frustrating, but can be reversed by the
context reinstatement effect, which occurs when you return to the original location and the memory suddenly comes back; in the above example, this
happens when you walk back into the original room you were in, and suddenly remember, “Oh yeah! Tape!” But, research also shows that these effects are not
isolated to external contexts; your internal environment can serve as a retrieval cue for your memory as well.
State-Dependent Memory
Although we are sure that most readers of this book dedicate their lives to healthy eating and exercise, it is likely that a few of you will have consumed substances that can affect your memory. For example, people sometimes drink enough alcohol that they are unable to remember some details of their night out with their friends. But, is that information gone forever or can it be accessed in the same way that some context-dependent memories can be retrieved with the
help of environmental cues? Research suggests that retrieval is more effective when your internal state matches the state you were in during encoding, a phenomenon known as state-dependent memory . In the first demonstration of this, Goodwin and colleagues (1969) got half of their participants extremely drunk (their blood-alcohol level was three times the legal limit); the other half were sober. Participants encoded information and completed several memory tests; they were then instructed to return 24 hours later for additional testing (and a new liver). On Day 2 of testing, half of the participants were again put into a state of severe intoxication; half of these participants had also been drunk on Day 1, and the other half had been sober. Thus, there were four groups: drunk– drunk (drunk on Day 1 and Day 2), drunk–sober, sober–drunk, and sober–sober. Not surprisingly, the sober–sober group outperformed all of the others. However, tests of recall showed that the drunk–drunk group outperformed the groups in which participants were intoxicated during only one of the two test sessions. The state of intoxication served as a retrieval cue for the participants’ memory. As with context-dependent memory, this effect appears to be strongest for declarative memory (e.g., recall), the form of memory that requires the
participant to generate the response on her own (Duka et al., 2001).
Similar effects have been found for other substances. For instance, marijuana researchers have found that “experienced smokers” who learned (encoded) information while under the effects of marijuana performed better if they received
marijuana before subsequent tests than if they were sober (Hill et al., 1973; Stillman et al., 1974). This group also outperformed participants who encoded information while sober, but were given marijuana before the testing on Day 2. However, the experimenters, in a beautiful example of understatement, did note
that “marihuana did produce some overall impairment in performance” (Stillman et al., 1974, p. 81). State-dependent memory has also been observed for caffeine (Kelemen & Creeley, 2003), a finding that might influence how some of you study and take exams. However, it is important to remember that, like context-dependent memory, the effects of state-dependent memory are fairly small and research is generally limited to artificial stimuli such as word lists. There is therefore no guarantee that drinking yourself silly will fill in the memory gaps of a previous wild night.
Mood-Dependent Memory
Just as similar contexts and chemical states can improve memory, studies of mood-dependent memory indicate that people remember better if their mood at retrieval matches their mood during encoding (Bower, 1981; Eich & Metcalfe, 1989). Volunteers in one study generated words while in a pleasant or unpleasant mood, and then attempted to remember them in either the same or a different mood. The results indicated that if the type of mood at encoding and retrieval matched, then memory was superior. However, changes in the intensity
of the mood did not seem to have an effect (Balch et al., 1999).
As with context- and state-dependent memory, mood-dependent memory has
some limitations (Eich et al., 1994). Mood has a very small effect on recognition memory; it has much larger effects on recall-based tests. Additionally, it produces larger effects when the participant must generate both the to-be- remembered information (e.g., “an example of a musical instrument is a
g “) than if the stimuli are externally generated (e.g., “remember this word: guitar”). In the first example, the participant must put more of his own cognition into the encoding process; therefore, those cognitive processes become important retrieval cues during a later recall-based test.
Although its effects are limited, mood-dependent memory does show that a
person’s emotional state can have an effect on encoding and retrieval. As we shall see, the influence of emotion can be even more dramatic when the stimuli themselves are emotional in nature.
Module 7.2a Quiz:
Encoding and Retrieval
Know . . . 1. The time and manner in which information is retained between encoding
and retrieval is known as . A. maintenance rehearsal B. storage C. elaborative rehearsal D. recall
2. Prolonging exposure to information by repeating it to oneself is referred to as .
A. maintenance rehearsal B. storage C. elaborative rehearsal D. recall
Understand . . . 3. According to the levels of processing approach to memory, thinking about
synonyms for a word is one method of processing that should memory for that term.
A. deep; decrease B. deep; increase C. shallow; increase D. shallow; decrease
Apply . . . 4. If you are learning vocabulary for a psychology exam, you are better off
using a(n) technique.
A. maintenance rehearsal B. elaborative rehearsal C. serial processing D. consolidation
5. When taking a math exam, the concept of would indicate that you would do best if you took the exam in the same physical setting as the setting where you learned the material.
A. context-dependent memory B. state-dependent memory C. environmental dependency process D. sensory-dependent memory
Emotional Memories
Do you remember what you ate for lunch last Tuesday? Is that event imprinted on your memory forever? Unless your lunch was spectacularly good or bad, it’s unlikely that the memory of your sandwich will be very vivid. But what if you saw police arrest people who were fighting in the cafeteria? Or, what if you got food poisoning from your tuna sandwich? Suddenly, that lunch would become much more memorable. Indeed, when you think back to different times in your life, the events that first come to mind are often emotional in nature, such as a wonderful birthday party or the fear of starting at a new school. Emotion seems to act as a highlighter for memories, making them easier to retrieve than neutral memories. This is because emotional stimuli and events are generally self-relevant and are associated with arousal responses such as increased heart rate and sweating. In linking emotion and memory back to topics discussed earlier in this module, it seems reasonable to assume that emotion leads to deep processing of information and involves powerful stimuli that can serve as retrieval cues.
The tendency for emotion to enhance our memory for events has been
demonstrated in a number of studies (LaBar & Cabeza, 2006; Levine & Pizarro, 2004). For instance, in one experiment, participants viewed a series of
images that were emotionally negative (e.g., a snarling dog), emotionally positive (e.g., a puppy), or neutral. The participants rated the images in terms of their emotion (positive vs. negative), arousal (high vs. low), and visual complexity. Two weeks later, the participants were given a memory test for the images that they had rated. Recollection was enhanced for negative and, to a lesser extent,
positive images (Ochsner, 2000). Similar results have been found with emotional words (e.g., Kensinger & Corkin, 2003) and images depicting someone’s daily activities (Laney et al., 2003). It seems that the emotion-related aspects of stimuli do indeed improve memory, particularly for stimuli that trigger negative emotions.
However, although it is intuitive to think that emotion will boost all forms of memory, psychology researchers have found that emotion has fairly specific effects. For example, people often focus their attention on the emotional content of a scene (e.g., a snake). This information—which typically forms the centre of one’s field of vision—is more likely to be remembered than peripheral information (e.g., the flowers near the snake). This phenomenon can take a more sinister turn in the courtroom. Many eyewitnesses to crimes have shown reductions in
memory accuracy due to weapon focus—the tendency to focus on a weapon at the expense of peripheral information including the identity of the person holding
the weapon (Kramer et al., 1990; Loftus et al., 1987).
Research has shown that the memory enhancing effect of emotion is strongest
after long (one hour or more) rather than short delays (LaBar & Phelps, 1998; Sharot & Phelps, 2004). This suggests that emotion’s largest influence is on the process of consolidation, when information that has recently been transferred from short-term memory (STM) into long-term memory (LTM) is strengthened and made somewhat permanent. Emotion has less of an effect on STM and on recognition memory; these types of memory have much less variability than LTM, thus leaving less room for emotion to influence accuracy levels.
The above studies suggest that emotional material received deeper (rather than shallow) processing. However, level of processing is not the only factor influencing memory and emotions. Emotion can influence memory consolidation even if the stimuli themselves are not emotional in nature. For example, in one
study, participants studied a list of words and were then randomly assigned to view a video of oral surgery (the emotional condition) or the way to brush your
teeth effectively (presumably not the emotional condition). Afterwards, the group members who viewed the surgery video remembered more of the words (see Figure 7.17 ) (Nielson et al., 2005). The researchers suggested that this effect was due to the emotional arousal associated with seeing the oral surgery video; this arousal could influence the process of consolidation. Other, more invasive, studies support this conclusion. In one experiment, stimulating the vagus nerve (which brings sensory information from the body and internal organs
to the brain) led to enhanced memory for neutral words (Clark et al., 1999). Thus, the physiological responses associated with emotions can lead to stronger memory formation, even if the to-be-remembered information is not directly related to the emotional event.
Figure 7.17 Does Emotion Improve Memory? In the study by Nielson and colleagues (2005), both groups remembered approximately the same percentage of words at pretest, and then watched dentistry videos unrelated to the word lists. The group whose members watched the more emotional video recalled more of the words in the end, suggesting that the emotional arousal associated with the video helped consolidate memory for the words.
Researchers have identified many of the biological mechanisms that allow
emotion to influence memory (Phelps, 2004). Much of this relationship involves structures in the temporal lobe of the brain: the hippocampus (the structure associated with the encoding of long-term memories) and the amygdala (a structure involved in emotional processing and responding). Brain imaging
shows that emotional memories often activate the amygdala, whereas non-
emotional memories generated at the same time do not (Sharot et al., 2007). These studies have shown that the amygdala can also alter the activity of
several temporal-lobe areas that send input to the hippocampus (Dolcos et al., 2004). As a result, the cells in these brain regions fire together more than they normally would, which may lead to more vivid memories (Kilpatrick & Cahill, 2003; Paz & Paré, 2013; see Figure 7.18 ). However, this coordinated neural activity still does not guarantee that all of the details of an experience will be remembered with complete accuracy.
Figure 7.18 Emotion, Memory, and the Brain Activity in the amygdala influences the activity of nearby regions in the temporal lobes, increasing the degree to which they fire together. This alters the type of input received by the hippocampus from regions of the cortex (the outer part of the temporal lobes).
Flashbulb Memories
Can you remember where you were when Sidney Crosby scored “the golden goal” against Team USA in the 2010 Olympic hockey final? For non-hockey fans, that afternoon might simply have been a fun time with friends and family, or
perhaps was entirely forgettable if they weren’t watching the game. But for others, the memory of that event might take on a vivid, almost photographic, quality. This phenomenon led researchers to label such an intense and unique
memory as being a flashbulb memory —an extremely vivid and detailed memory about an event and the conditions surrounding how one learned about the event (Brown & Kulik, 1977). (The term flashbulb refers to the flash of an old-fashioned camera.) These highly charged emotional memories typically involve recollections of location, what was happening around oneself at the time
of the event, and the emotional reactions of self and others (Brown & Kulik, 1977). Some may be personal memories, such as the memory of an automobile accident. Other events are so widely felt that they seem to form flashbulb memories for an entire society, such as the assassination of U.S. President
Kennedy in 1963 (Brown & Kulik, 1977), the explosion of the space shuttles Challenger or Columbia (Kershaw et al., 2009; Neisser & Harsch, 1992), and the terrorist attacks of September 11, 2001 (Hirst et al., 2009; Paradis et al., 2004). One defining feature of flashbulb memories is that people are highly confident that their recollections are accurate. But is this confidence warranted? Several studies (described in the Myths in Mind section above) suggest that we should give flashbulb memories a second look.
Myths in Mind The Accuracy of Flashbulb
Memories Although flashbulb memories are very detailed and individuals reciting the details are very confident of their accuracy, it might surprise you to learn that they are not necessarily more accurate than many other memories. For example, researchers examined how university students remembered the September 11, 2001, attacks in comparison to an
emotional but more mundane event (Talarico & Rubin, 2003). On September 12, 2001, they asked students to describe the events surrounding the moment they heard about the attacks. For a comparison event, they asked students to describe something memorable from the preceding weekend, just two or three days before the attacks. Over
several months, the students were asked to recall details of both events, and the researchers compared the accuracy of the two memories. Although their memory for both events was fading at the same rate and they were equal in accuracy, the students acknowledged the decline in memory only for the mundane events. They continued to feel highly confident in their memories surrounding the September 11 attacks, when, in fact, those memories were not any more accurate. The same pattern has been found for other major flashbulb events, such as the 1986 space
shuttle Challenger explosion and the verdict in the infamous 1995 murder trial of former NFL star and actor O. J. Simpson (Neisser & Harsch, 1992; Schmolk et al., 2000).
Module 7.2b Quiz:
Emotional Memories
Know . . . 1. are extremely vivid and detailed memories about an event.
A. Flashbulb memories B. Deep memories C. Rehearsal memories D. Semantic memories
Understand . . . 2. One study had participants view tapes of dental surgery after studying a
word list. This study concluded that
A. emotional videos have no effect on memory. B. emotional videos can enhance memory, but only for material
related to the video itself.
C. emotional videos can enhance memory even for unrelated material.
D. emotional videos can enhance memory for related material, while reducing memory for unrelated material.
Analyze . . . 3. Which statement best sums up the status of flashbulb memories?
A. Due to the emotional strain of the event, flashbulb memories are largely inaccurate.
B. Recall for only physical details is highly accurate. C. Both emotion and physical details are remembered very
accurately.
D. Over time, memory for details decays, similar to what happens with non-flashbulb memories.
Forgetting and Remembering
Have you ever had the experience of studying intensely for an exam, writing it, and then forgetting almost everything as soon as you walked out of the exam room? This phenomenon is quite common, particularly if you did all of your studying the night before (or morning of) the exam. Forgetting information is probably a good thing, at least if it occurs in moderation. We don’t need to remember every detail about every day of our lives. Instead, we want to have some control over what we do remember, thus allowing us to keep the useful information (e.g., terms for an exam) and deleting the less useful information (e.g., the details of a conversation you overheard on the bus). Of course, if we had that type of control, there would be no need to study the intricacies of why we remember and forget things. As you will see, this issue has been researched extensively.
The Forgetting Curve: How Soon We Forget . . .
It might seem odd that the first research on remembering was actually a documentation of how quickly people forget. However, this approach does make sense: Without knowledge of forgetting, it is difficult to ascertain how well we can remember. This early work was conducted by Hermann Ebbinghaus, whom
many psychologists consider the founder of memory research. Ebbinghaus (1885) was his own research participant in his studies; these experiments
involved him studying hundreds of nonsense syllables for later memory tests. His rationale was that because none of the syllables had any meaning, none of them should have been easier to remember based on past experiences. Ebbinghaus studied lists of these syllables until he could repeat them twice. He then tested himself repeatedly—this is where his persistence really shows—day after day.
How soon do we forget? The data indicated that Ebbinghaus forgot about half of a list within an hour. If Ebbinghaus had continued to forget at that rate, the rest of the list should be lost after two hours, but that was not the case. After a day, he could generally remember one-third of the material, and he could still recall
between 20–25% of the words after a week. The graph in Figure 7.19 shows the basic pattern in his test results, which has come to be known as a forgetting curve. It clearly shows that most forgetting occurs right away, and that the rate of forgetting eventually slows to the point where one does not seem to forget at all. These results have stood the test of time. In the century after Ebbinghaus conducted his research, more than 200 articles were published in psychological
journals that fit Ebbinghaus’s forgetting curve (Rubin & Wenzel, 1996). In fact, one study demonstrated that this forgetting curve applies to information learned
over 50 years before (see Figure 7.20 ; Bahrick, 1984).
Figure 7.19 Ebbinghaus’s Forgetting Curve This graph reveals Ebbinghaus’s results showing the rate at which he forgot a series of nonsense syllables. You can see that there is a steep decline in
performance within the first day and that the rate of forgetting levels off over time. Source: Memory: A Contribution to Experimental Psychology, Hermann Ebbinghaus (1885). Translated by Henry A. Ruger &
Clara E. Bussenius (1913). Originally published in New York by Teachers College, Columbia University.
Figure 7.20 Bahrick’s Long-Term Forgetting Curve This forgetting curve depicts the rate at which adults forgot the foreign language they took in high school. Compared to new graduates, those tested three years later forgot much of what they learned. After that, however, test scores stabilized, just as Ebbinghaus’s did a century earlier. Source: From Bahrick, H. P. (1984). Semantic memory content in permastore: Fifty years of memory for Spanish learned in
school. Journal of Experimental Psychology: General, 113 (1), 1–29. American Psychological Association.
Given that the forgetting curve has been documented in hundreds of experiments, it seems inevitable that we will forget most of the information that we attempt to encode. However, as you have undoubtedly learned over the course of your studies, there are techniques that will allow you to improve your memory so that the forgetting curve is not as steep.
Mnemonics: Improving Your Memory Skills
At the beginning of this module, you read about the poet Simonides and his ability to use mental imagery to improve his memory, thus allowing him to identify the remains of people crushed under a collapsed roof. Simonides was using a
primitive type of mnemonic —a technique intended to improve memory for specific information. As you will see in this section, there are a number of different mnemonics that could be used to improve memory, something that might be of interest to overwhelmed students.
The technique that Simonides was using is known as the method of loci
(pronounced “LOW-sigh”), a mnemonic that connects words to be remembered to locations along a familiar path. To use the method of loci, one must first imagine a route that has landmarks or easily identifiable spaces—for example, the things you pass on your way from your home to a friend’s house or the seats around a dinner table. Once the path is identified, the learner takes a moment to visually relate the first word on the list to the first location encountered. For example, if you need to remember to pick up noodles, milk, and soap from the store and the first thing you pass on the way to your friend’s house is an intersection with a stop sign, you might picture the intersection littered with noodles, and so on down the list. The image doesn’t need to be realistic—it just needs to be distinct enough to be memorable. When it is time to recall the items, the learner simply imagines the familiar drive, identifying the items to be purchased as they relate to each location along the path.
However, the method of loci can become a bit cumbersome when a person has to remember hundreds of different facts, as occurs for university exams. A more
practical mnemonic is the use of acronyms , pronounceable words whose letters represent the initials of an important phrase or set of items. For example, the word “scuba” came into being with the invention of the self-contained underwater breathing apparatus. “Roy G. Biv” gives you the colours of the rainbow: red, orange, yellow, green, blue, indigo, and violet. A related mnemonic,
the first-letter technique , uses the first letters of a set of items to spell out words that form a sentence. It is like an acronym, but it tends to be used when the first letters do not spell a pronounceable word (see Figure 7.21 ). One well-known example is “Every Good Boy Does Fine” for the five lines on the
treble clef in musical notation. Another is “My Very Excited Mother Just Served Us Nine Pies” for the nine planets in the solar system (Pluto is now a “dwarf planet”). These types of mnemonic techniques work by organizing the information into a pattern that is easier to remember than the original information. Acronyms have a meaning of their own, so the learner gets the benefit of both elaborative rehearsal and deeper processing.
Figure 7.21 The First-Letter Technique Students of biology often use mnemonics, such as this example of the first letter technique, which helps students remember the taxonomic system.
The method of loci relies on mental imagery of a familiar location or path, like this path that students take to class three times a week.
Lori Howard/Shutterstock
A number of mnemonic devices are based on the premise of dual coding. Dual coding occurs when information is stored in more than one form—such as a verbal description and a visual image, or a description and a sound—and it
regularly produces stronger memories than the use of one form alone (Clark & Paivio, 1991). Dual coding leads to the information receiving deeper, as opposed to shallow, processing; this is because the additional sensory representations create a larger number of memory associations. This leads to a greater number of potential retrieval cues that can be accessed later. For example, most children growing up in North America learned the alphabet with the help of a song. In fact, even adults find themselves humming portions of that song when alphabetizing documents (you’ll probably do it too if asked which letter comes after “k”). Both the visual “A-B-C-D” and the musical “eh-bee-see- dee” are encoded together, making memory easier than if you were simply given
visual information to remember (e.g., “ ”, which is ABCD in the meaningless “wingdings2” font). The simplest explanation for the dual-coding advantage is that twice as much information is stored.
The application of mnemonic strategies can be found in restaurants where servers are not allowed to write out orders. These servers use a variety of the techniques discussed in this chapter. Some use chunking strategies, such as remembering soft drinks for a group of three customers, and cocktails for the other four. They also use the method of loci to link faces with positions at the table. In one study, a waiter was able to recall as many as 20 dinner orders
(Ericsson & Polson, 1988). He used the method of loci by linking food type (starch, beef, or fish) with a table location, and he used acronyms to help with encoding salad dressing choices. Thus RaVoSe for a party of three would be ranch, vinegar and oil, and sesame. Servers, as well as memory researchers, will tell you that the worst thing restaurant patrons can do is switch seats, as it completely disrupts the mnemonic devices being used to remember the order
(Bekinschtein et al., 2008).
While these mnemonic devices can help with rote memorization, they may not
necessarily improve your understanding of material. Researchers have begun to examine other memory boosters that may offer more benefits understanding and
retaining information. For example, some research has shown that desirable difficulties can aid learning. These techniques make studying slower and more effortful, but result in better overall remembering. For instance, in Module 1.1 you read about the benefits of spreading out study sessions rather than cramming for an exam in one long session (spaced vs. massed learning). When you space out your sessions, it is likely that you will forget some of the items
from the previous study session (Smolen et al., 2016). As a result, you’ll reread those notes and study them in more depth, a behaviour that will improve your chances of remembering the information later. Studying material in varying orders has a similar effect.
Another popular approach to studying is to use flashcards. Although psychologists have begun to understand how this process benefits students, they also have identified a few pitfalls that can hinder its effects. First is the spacing effect. When studying with flashcards, it is better to use one big stack rather than several smaller stacks; using the entire deck helps take advantage of the effect of spacing the cards. A second potential problem is the fact that students become overconfident and drop flashcards as soon as they believe they have learned the material. In reality, doing so seems to reduce the benefits of overlearning the material (making it more difficult to forget) and spacing out
cards in the deck (Kornell, 2009; Kornell & Bjork, 2007). No matter how you study, you should take advantage of the testing effect , the finding that taking practice tests can improve exam performance, even without additional studying. In fact, researchers have directly compared testing to additional studying and have found that, in some cases, testing actually improves memory more
(Roediger et al., 2010). That’s why psychology textbooks such as this one include quizzes and online tests.
Module 7.2c Quiz:
Forgetting and Remembering
Know . . .
1. Dual coding seems to help memory by A. allowing for maintenance rehearsal. B. ensuring that the information is encoded in multiple ways. C. ensuring that the information is encoded on two separate
occasions.
D. duplicating the rehearsal effect.
Apply . . . 2. If you are preparing for an exam by using flashcards, you will probably
find that you are more confident about some of the items than others. To improve your exam performance, you should
A. drop the cards you already know. B. keep the cards in the deck even if you feel like you know them. C. use maintenance rehearsal. D. use the method of loci.
3. If you wanted to remember a grocery list using the method of loci, you should
A. imagine the items on the list on your path through the grocery store.
B. match rhyming words to each item on your list. C. repeat the list to yourself over and over again. D. tell a story using the items from the list.
Module 7.2 Summary
acronym
context-dependent memory
deep processing
dual coding
Know . . . the key terminology related to forgetting, encoding, and retrieval.
7.2a
elaborative rehearsal
encoding specificity principle
first-letter technique
flashbulb memory
maintenance rehearsal
method of loci
mnemonic
mood-dependent memory
recall
recognition
self-reference effect
state-dependent memory
shallow processing
testing effect
Generally speaking, deeper processing makes things more likely to be remembered. Greater depth of processing may be achieved by elaborating on the meaning of the information, through increased emotional content, and through coding in images and sounds simultaneously.
Try putting some tools from the chapter into practice. One mnemonic device that might be helpful is the method of loci.
Understand . . . how the type of cognitive processing employed can affect the chances of remembering what you encounter.
7.2b
Apply . . . what you have learned to improve your ability to memorize information.
7.2c
Apply Activity Have someone create a shopping list for you while you prepare yourself by imagining a familiar path (perhaps the route you take to class or work). When you are ready to learn the list, read a single item on the list and imagine it at some point on the path. Feel free to exaggerate the images in your memory— each item could become the size of a stop sign or might take on the appearance of a particular building or tree that you pass by. Continue this pattern for each individual item until you have learned the list. Then try what Ebbinghaus did: Test your memory over the course of a few days. How do you think you will do?
Both personal experiences and controlled laboratory studies demonstrate that emotion enhances memory. However, as we learned in the case of flashbulb memories, even memories for details of significant events decline over time, although confidence in memory accuracy typically remains very high.
Analyze . . . whether emotional memories are more accurate than non-emotional ones.
7.2d
Module 7.3 Constructing and Reconstructing Memories
RiceWithSugar/Shutterstock.com
Learning Objectives
Know . . . the key terminology used in discussing how memories are organized and constructed. Understand . . . how schemas serve as frameworks for encoding and constructing memories. Understand . . . how psychologists can produce false memories in the laboratory.
7.3a
7.3b
7.3c
In 1992, the Saskatchewan town of Martensville was rocked by a sex abuse scandal. A complaint about a suspicious diaper rash from a parent of a toddler attending a local daycare led to a police investigation. After repeated and extensive interviewing, the children claimed to remember astonishing things including extensive sexual abuse, human sacrifice, a “Devil Church,” and a Satanic cult known as The Brotherhood of the Ram. The owners of the daycare along with several other individuals— including five police officers—were eventually arrested. However, a closer examination of the police investigation identified some serious problems. Expert witnesses noted that the questions used in the interviews were leading and suggestive. Upon further examination, many charges were dropped. In fact, only one of the accused was convicted of a crime (molestation). The Saskatchewan government has since paid out millions of dollars to the other accused individuals whose lives were affected by these investigations.
While certainly well-meaning, the investigators—who were not trained to interview child witnesses—forgot a critical piece of information: Memories are not like photographs perfectly depicting an event from our past. Instead, they are reconstructed each time we retrieve them, and can therefore be altered by a number of different factors.
Focus Questions
1. How is it possible to remember events that never happened? 2. Do these false memories represent memory problems, or are they
just a normal part of remembering?
The true story that opened this module demonstrates that our memories are not
Apply . . . what you have learned to judge the reliability of eyewitness testimony. Analyze . . . the arguments in the “recovered memory” debate.
7.3d
7.3e
perfect. In a less disturbing example, cognitive psychologist and renowned memory researcher Ulric Neisser once recounted what he was doing on December 7, 1941, the day Japan attacked Pearl Harbor. Neisser was sitting in the living room listening to a baseball game on the radio when the program was
interrupted with the news (Neisser, 2000). Or was he? He had certainly constructed a very distinct memory for this emotional event, but something must have gone wrong. Baseball season does not last through December. As this example demonstrates, even memory researchers are prone to misremembering. In this module we will examine how such misremembering occurs and what it says about how memories are constructed . . . and reconstructed.
How Memories Are Organized and Constructed
Think about the last time you read a novel or watched a film. What do you recall about the story? If you have a typical memory, you will forget the proper names of locations and characters quickly, but you will be able to remember the basic
plot for a very long time (Squire, 1989; Stanhope et al., 1993). The plot may be referred to as the gist of the story and it impacts us much more than characters’ names, which are often just details. As it turns out, much of the way we store memories depends on our tendency to remember the gist of things.
The Schema: An Active Organization Process
The gist of a story gives us “the big picture,” or a general structure for the memory; details can be added around that structure. Gist is often influenced by schemas , organized clusters of memories that constitute one’s knowledge or beliefs about events, objects, and ideas. Whenever we encounter familiar events or objects, these schemas become active and affect what we expect, what we pay attention to, and what we remember. Because we use these patterns automatically, it may be difficult to understand what they are, even though we
use them throughout our lives. Here is an example; read the following passage through one time:
The procedure is quite simple. First, you arrange things into different groups. Of course,
one pile may be sufficient, depending on how much there is to do. If you have to go
somewhere else due to lack of facilities, that is the next step; otherwise, you are pretty
well set. It is important not to overdo things. That is, it is better to do too few things at
once than too many. At first the whole procedure will seem complicated. Soon,
however, it will become just another facet of life. After the procedure is completed, one
arranges the materials into different groups again. Then they can be put into their
appropriate places. Eventually they will be used once more, and the whole cycle will
have to be repeated (Bransford & Johnson, 1973).
At this point, if you were to write down the details of the paragraph solely from memory, how well do you think you would do? Most people do not have high expectations for themselves, but they would blame it on how vague the paragraph seems. Now, what if we tell you the passage is about doing laundry? If you read the paragraph a second time, you should see that it is easier to understand, as well as to remember.
Working the Scientific Literacy Model How Schemas Influence Memory
Although schemas are used to explain memory, they can be used to explain many other phenomena as well, such as the way we perceive, remember, and think about people and situations. In each case, schemas provide a ready-made structure that allows us to process new information more quickly than we could without this mental shortcut. This makes schemas extremely useful. But, are they accurate?
What do we know about schemas? The laundry demonstration tells us quite a bit about schemas and
memory. First, most of us have our own personal schema about the process of doing laundry. Refer to the definition of schema—a cluster of memories that constitutes your knowledge about an event (gathering clothes, going to the laundromat), object (what clothes are, what detergent is), or idea (why clean clothes are desirable). When you read the paragraph the first time, you probably did not know what the objects and events were. However, when you were told it was about doing laundry, it
activated your laundry schema—your personal collection of concepts and memories. Once your schema was activated, you were prepared to make sense of the story and could likely fill in the gaps of your memory for the passage with stored knowledge from your schema in long-term memory (LTM). Second, we should point out that schemas are involved in all three stages of memory: They guide what we attend to during encoding, organize stored memories, and serve as cues when it comes time to retrieve information.
How can science explain schemas?
Research indicates that we remember events using constructive memory , a process by which we first recall a generalized schema and then add in specific details (Scoboria et al., 2006; Silva et al., 2006). Where do these schemas come from? They appear to be products of culture and experience (e.g., Ross & Wang, 2010). For example, individuals within a culture tend to have schemas related to gender roles—men and women are each assumed to engage in certain jobs and to behave in certain ways. Even if an individual realizes that these schemas are not 100% accurate (in fact, they can be far from accurate in some cases), he or she is likely to engage in schematic processing when having difficulty remembering something specific.
A study by Heather Kleider and her associates (2008) demonstrates how schemas influence memory quite well. These investigators had research participants view photographs of a
handyman engaged in schema-consistent behaviour (e.g., working on plumbing) as well as a schema-inconsistent tasks (e.g., folding a baby’s clothing). Participants also viewed images of a stay-at-home mother performing schema-consistent (e.g., feeding a baby) and schema-inconsistent tasks (e.g., hammering a nail). Immediately after viewing the photographs, participants were quite successful at remembering correctly who had performed what actions. However, after two days, what types of memory mistakes do you think the researchers found? As you
can see from Figure 7.22 , individuals began making mistakes, and these mistakes were consistent with gender schemas.
Figure 7.22 Schemas Affect How We Encode and Remember
In this study, memory was accurate when tested immediately, as shown by the small proportion of errors on the “immediate” side of the graph. After two days, however, participants misremembered seeing the schema-inconsistent tasks in line with stereotypes. For example, they misremembered the stay-at-home
mother stirring cake batter even if they had actually seen the handyman doing it. Source: Data from Kleider, H., Pezdek, K., Goldinger, S., & Kirk, A. (2008). Schema–driven source
misattribution errors: Remembering the expected from a witnessed event. Applied Cognitive
Psychology, 22 (1), 1–20.
Can we critically evaluate the concept of a schema? The concept of a schema is certainly useful in describing our methods of mental organization, but some psychologists remain skeptical of its validity. After all, you cannot record brain activity
and expect to see a particular schema, and individuals generally are not aware that they are using schematic processing. It may even be the case that what we assume are schemas about laundry, gender, or ourselves are different every time we think about these topics. If that is the case, then describing this tendency as a schema might even be misleading.
However, recent brain-imaging studies suggest that schemas do exist and likely help with the process of memory consolidation
(Wang & Morris, 2010). Both encoding and retrieving information that was consistent with a schema learned during an experiment led to greater activity in a network involving parts of the medial temporal lobes (including the hippocampus) and the frontal lobes
(van Kesteren, Fernandez, et al., 2010; van Kesteren, Rijpkema, et al., 2010; see Figure 7.23 ). Additionally, adding new information to an existing schema actually changes the expression of genes in the frontal lobes in order to strengthen
connections between this region and the hippocampus (Tse et al., 2011). Thus, while we cannot identify the neural correlates for a specific schema like that for doing laundry, it is possible to see how schemas influence brain activity while new information is encoded and entered into the structure of our LTM.
Figure 7.23 A Brain Network Related to Processing Schemas
Brain-imaging data suggest that encoding information consistent with a schema activates a network involving structures in the medial temporal lobe (including our friend, the hippocampus) and parts of the frontal lobes. Source: Figure 5 from van Kesteren et al., (2013), Trends in Neuroscience, p. 2358.
Biopsychosocial Perspectives Your
Earliest Memories
Think back to the earliest memory you can recall: How old were you? It is likely that you do not have any personal or
autobiographical memories from before your third birthday. Psychologists have been trying to explain this
phenomenon—sometimes called infantile amnesia.
Research indicates that self-schemas begin to develop
around the ages of 18 to 24 months (Howe, 2003). Without these schemas, it is difficult and maybe even impossible to organize and encode memories about the self. This is not a universal phenomenon, however. Other researchers taking a cross-cultural perspective have found that a sense of self emerges earlier among European Americans than among people living in eastern Asia, which correlates with earlier ages of first memories
among European Americans (Fivush & Nelson, 2004; Ross & Wang, 2010). Why might this difference arise? The European American emphasis on developing a sense of self encourages thinking about personal experiences, which increases the likelihood that personal events—such as your third birthday party with that scary drunken clown, or getting chased by a dog—will be remembered. In contrast, Asian cultures tend to emphasize social harmony and collectiveness over individualism, resulting in a schema that is more socially integrated than in Westerners. This may explain the slightly later onset of autobiographical memory in Asian children. It will be interesting to see if this cultural difference changes as Asian cultures become more “Westernized.”
Do these findings mean that we could get infants to remember early life events by teaching them to talk about themselves at an early age? This is not likely. The brains of young children are still developing, so the neural architecture necessary to form stable schemas is not yet
in place (Newcombe et al., 2000).
Why is this relevant?
An important aspect of schema-driven processing has to do with how we process information about ourselves. Clinical psychology researchers have become particularly concerned with the ways in
which these self-schemas may contribute to psychological problems. Consider a person with clinical depression—a condition that involves negative emotion, lack of energy, self- doubt, and self-blame. An individual with depression is likely to have a very negative self-schema, which means that he will pay attention to things that are consistent with the depressive symptoms, and will be more likely to recall events and feelings that are consistent with this schema. Thus the schema contributes to a pattern of thinking and focusing on negative thoughts. Fortunately, researchers have been able to target these schemas in psychotherapy. The evidence shows that by changing their self-schema, individuals are better able to recover
from even very serious bouts of depression (Dozois et al., 2009).
Schemas about the self are based on past experiences and are used to organize the encoding of self-relevant information in a way that can influence our
responses (Markus, 1977). But self-schemas may serve an additional role during development. Some evidence suggests that the ability to form schemas, particularly self-schemas, plays a critical role in our ability to form memories about our lives.
Module 7.3a Quiz:
How Memories Are Organized and Constructed
Know . . . 1. Schemas appear to affect which of the following stages of memory?
A. Encoding B. Storage C. Retrieval
D. All of these stages
2. The act of remembering through recalling a framework and then adding specific details is known as .
A. constructive memory B. confabulation C. schematic interpretation D. distinctiveness
Understand . . . 3. Information that does not fit our expectations for a specific context is
likely to be forgotten if
A. it is extremely unusual. B. it only fits our expectations for another completely different
context.
C. it is unexpected, but really not that unusual. D. it is schema consistent.
Memory Reconstruction
You’ve all heard the cliché, “You are what you eat.” But, it’s also becoming
increasingly clear to psychologists that “You are what you remember” (Wilson & Ross, 2003). As you read earlier in this module, our memories are organized to a large degree by our schemas, including self-schemas. There is no guarantee, however, that these schemas are 100% accurate. In fact, different motivations can influence which schemas are accessible to us in a given moment, thereby biasing our memory reconstruction. As a result of these motivational influences, the past that we remember is actually influenced by our mental state and by our
view of ourselves in the present (Albert, 1977).
This type of biasing effect was nicely demonstrated in a study conducted by
researchers at Concordia University and the University of Waterloo (Conway & Ross, 1984). The researchers had one group of participants complete a study
skills course while another group remained on a waiting list. The course itself proved completely ineffective, at least in terms of improving study skills. The course did have an interesting effect on memory, however. Participants who completed the study course rated their previous study skills lower than they had rated them prior to taking the course; participants on the waiting list rated their study skills as being unchanged. Therefore, the study course participants revised their memories of their past abilities in a way that allowed them to feel as though they benefited from the course. This memory bias allowed them to feel as though they were improving over time, a bias that almost all of us have about ourselves
(Ross & Wilson, 2000).
The results of such studies demonstrate that our memories are not stable, but
instead change over time. Indeed, we have all experienced a false memory , remembering events that did not occur, or incorrectly recalling details of an event. It is important to remember that these incorrect memories do not necessarily indicate a dysfunction of memory, but rather reflect normal memory processes—which are inherently imperfect. As you read in the discussion of schemas, the elements that comprise a memory must be reconstructed each time that memory is retrieved. This reconstruction is influenced by the demands of the current situation. Psychologists have identified several ways in which our memories can be biased, and have explored how these biases can have many real-world implications, such as in the legal system.
The Perils of Eyewitness Testimony
Have you ever witnessed a crime or even a minor traffic accident? When asked later about what you witnessed, how accurate were your reports? Most of us feel quite confident in our ability to retrieve this type of information. However, psychologists have shown that a number of minor factors can dramatically influence the details of our “memories.”
In one classic study, Elizabeth Loftus and John Palmer (1974) showed undergraduate research participants film clips of traffic accidents. Participants were asked to write down a description of what they had seen, and were then asked a specific question: “About how fast were the cars going when they
smashed into each other?” However, the exact wording of this question varied across experimental conditions. For some participants, the word “smashed” was replaced by “collided,” “bumped,” “contacted,” or “hit.” The results of the study were stunning—simply changing one verb in the sentence produced large
differences in the estimated speed of the vehicles (see Figure 7.24 ). At one extreme, the word “smashed” led to an estimate of 65.2 km/h. At the low end of the spectrum, the word “contacted” led to estimates of 51.2 km/h. So, changing the verb altered the remembered speed of the vehicles by 14 km/h. In a follow- up study, Loftus and Palmer also found that participants in the “smashed” condition were more likely to insert false details such as the presence of broken glass into their accident reports. This study was a powerful demonstration of the effect of question wording on memory retrieval and provided police with important information about the need for caution when questioning witnesses.
Figure 7.24 The Power of a Word Simply changing the wording of a question altered participants’ recollections of a filmed traffic accident. All participants viewed the same filmed traffic accidents and all participants received the identical question with the exception of one key verb: smashed, collided, bumped, hit, or contacted. Source: Based on data from Loftus, E. F., & Palmer, J. C. (1974). Reconstruction of automobile destruction: An example of
the interaction between language and memory. Journal of Verbal Learning and Verbal Behavior, 13, 585–589 (p. 586.).
Another factor that can alter memories of an event—and that has implications for the legal system—is the information that is encoded after the event has occurred, such as rumours, news reports, or hearing about other people’s perceptions of the event. If such information was accurate, it could improve people’s memories; however, this type of information is not always accurate, which explains why jury members are asked to avoid reading about or watching TV reports related to the case with which they are involved. Psychologists have shown that this legal procedure is a wise one, as a number of studies have
demonstrated the misinformation effect , when information occurring after an event becomes part of the memory for that event. In the original studies of this topic (Loftus, 1975), researchers attempted to use the misinformation effect to change the details of people’s memories. For example, in one study, students viewed a videotape of a staged car crash. In the experimental conditions, participants were asked about an object that was not in the video, such as a yield sign (when in fact the scene had contained a stop sign). Later, when asked if they had seen a yield sign, participants in the experimental group were likely to say yes. As this experiment demonstrates, one can change the details of a memory by asking a leading question.
Children are particularly susceptible to misinformation effects and to the effects
of a question’s wording (Bruck & Ceci, 1999). In one study, five- and six-year- old children watched a janitor (really an actor) named Chester as he cleaned some dolls and other toys in a playroom. For half of the children, his behaviour was innocent and simply involved him cleaning the toys. For the other children, Chester’s behaviour seemed abusive and involved him treating the toys roughly. The children were later questioned by two interviewers who were (1) accusatory (implying that Chester had been playing with the dolls when he should have been working), (2) innocent (implying that Chester was simply cleaning the dolls), or (3) neutral (not implying anything about Chester’s behaviour). When the interviewer’s tone matched what the children saw, such as innocent questioning about Chester when he treated the toys nicely or accusatory questioning when Chester was rough with the toys, the children’s reports of the behaviour were quite accurate. However, when the interview technique did not match the observed behaviour (e.g., accusatory questioning when Chester had simply cleaned the toys), the children’s responses matched the interviewer’s tone. In
other words, the tone of the interviewer altered the details of the information that
the children retrieved and reported (Thompson et al., 1997).
Participants in one study viewed the top photo and later were asked about the “yield sign,” even though they saw a stop sign. This small bit of misinformation was enough to get many participants to falsely remember seeing a yield sign. Similarly, participants who first viewed the bottom photo could be led to misremember seeing a stop sign with a single misleading question. Dr. Elizabeth Loftus
Similar to adults, children are also dependent on schemas. In one study, researchers told children at school about their clumsy friend Sam Stone. On
numerous occasions, they told funny stories about Sam’s life, including the times he broke a Barbie doll and tore a sweater. Later, the children met “Sam Stone.” During his time in the classroom, he did not perform a single clumsy act. The following day, the teacher showed the children a torn book and a dirty teddy bear, but did not link Sam to these damaged items. When questioned a few weeks later, however, many of the three- and four-year-old children reported that Sam Stone had ruined these objects. Some even claimed to have witnessed
these acts themselves (Leichtman & Ceci, 1995). These findings should not lead us to ignore the eyewitness testimony of children; but, they should also remind us (and investigators) that memories—particularly those of children—are not stable and unchanging like a photograph. This research highlights how extremely important it is for legal professionals, such as the police, to practise investigative techniques that avoid biasing witnesses to crimes. Failure to do so could easily result in innocent people being convicted of crimes they did not commit, or conversely, guilty people being set free due to “reasonable doubt” because of questionable eyewitness testimony.
PSYCH@ Court: Is Eyewitness Testimony
Reliable? While trying to identify the individual responsible for a crime, investigators often present a lineup of a series of individuals (either in person or in photographs) and ask the eyewitness to identify the suspect. Given the constructive nature of memory, it should come as no surprise to hear that an eyewitness gets it wrong from time to time. The consequences of this kind of wrongful conviction are dire—an innocent person may go to jail while a potentially dangerous person stays free.
How can the science of memory improve this process? Here are the six main suggestions for reforming eyewitness identification procedures:
1. Employ double-blind procedures. Elsewhere in this book, we discussed how double-blind procedures help reduce experimenter bias. Similarly, a double-blind lineup (i.e., the investigator in the room with the eyewitness has no knowledge of
which person is the actual suspect) can prevent an investigator from biasing an eyewitness, either intentionally or accidentally.
2. Use appropriate instructions. For example, the investigator should include the statement, “The suspect might not be present in the lineup.” Eyewitnesses often assume the guilty person is in the lineup, so they are likely to choose a close match. This risk can be greatly reduced by instructing the eyewitness that the correct answer may be “none of the above.”
3. Compose the lineup carefully. The lineup should include individuals who match the eyewitness’s description of the perpetrator, not the investigator’s beliefs about the suspect.
4. Use sequential lineups. When an entire lineup is shown simultaneously, this may encourage the witness to assume one of the people is guilty, so they choose the best candidate. If the people in the lineup are presented one at a time, witnesses are less likely to pick out an incorrect suspect because they are willing to consider the next person in the sequence.
5. Require confidence statements. Eyewitness confidence can change as a result of an investigator’s response, or simply by seeing the same suspect in multiple lineups, neither of which make the testimony any more accurate. Therefore, confidence statements should be taken in the witness’s own words after an identification is made.
6. Record the procedures. Eyewitness researchers have identified at least a dozen specific things that can go wrong during identification procedures. By recording these procedures, expert witnesses can evaluate the reliability of testimony during hearings.
Recently, Canadian legal experts produced the 2011 Report of the Federal/Provincial/Territorial Heads of Prosecutions Subcommittee on the Prevention of Wrongful Convictions. This 233-page document presents recommendations to the legal community for the use of eyewitness testimony, among other investigative practices, and highlights the need for testimony from experts, including psychologists.
Imagination and False Memories
Because our memories are not always as accurate as we would like them to be, people use a number of techniques to try to help themselves retrieve information. One of these techniques is to imagine the situation that you are trying, but failing, to remember. However, although this strategy seems logical at first, the results of several studies suggest that the retrieved memories may not be very accurate. Research indicates that repeatedly imagining an action such as breaking a toothpick makes it very difficult for people to remember whether or not they
performed that action (Goff & Roediger, 1998). In fact, imagining events can often lead to imagination inflation , the increased confidence in a false memory of an event following repeated imagination of the event. The more readily and clearly we can imagine events, the more certain we are that the memories are accurate.
To study this effect, researchers created a list of events that may or may not have happened to the individuals in their study (e.g., got in trouble for calling 911, found a $10 bill in a parking lot). The volunteers were first asked to rate their confidence that the event happened. In sessions held over a period of days, participants were asked to imagine these events, until finally they were asked to rate their confidence again. For each item they were asked to imagine, repeated
imagination inflated their confidence in the memory of the event even if they initially reported that the event had not occurred (Garry et al., 1996; Garry & Polaschek, 2000).
Importantly, imagination inflation is very similar to guided imagery, a technique used by some clinicians (and some police investigators) to help people recover details of events that they are unable to remember. It involves a guide giving instructions to participants to imagine certain events. Like the misinformation effect, guided imagery can be used to alter memories for actual events, but it can also create entirely false memories. For example, in one experiment, volunteers were asked to imagine a procedure in which a nurse removed a sample of skin from a finger. Despite the fact that this is not a medical procedure and that it
almost certainly never occurred, individuals in the experimental group were more likely than those in the control group to report that this event had actually
happened to them (Mazzoni & Memon, 2003). In other words, attempting to imagine an event can implant new—and false—events into a person’s memory.
Creating False Memories in the Laboratory
Given that several research studies have shown that false memories are fairly easy to create, and given that such memories can have dramatic and tragic consequences when they appear in clinical or legal settings, it became important for researchers to develop techniques that would allow them to study false memories in more detail. The first of these techniques to be used was the
Deese-Roediger-McDermott (DRM) paradigm (see Figure 7.25 ). In the DRM procedure , participants study a list of highly related words called semantic associates (which means they are associated by meaning). The word that would be the most obvious member of the list just happens to be missing. This missing
word is called the critical lure. What happens when the participants are given a memory test? A significant proportion of participants remember the critical lure,
even though it never appeared on the list (Deese, 1959; Roediger & McDermott, 1995). When individuals recall the critical lure, it is called an intrusion, because a false memory is sneaking into an existing memory.
Figure 7.25 A Sample Word List and Its Critical Lure for the DRM Procedure
The words on the left side are all closely related to the word “bread”—but “bread” does not actually appear on the list. People who study this list of words are very likely to misremember that “bread” was present. Source: From Roediger, H., & McDermott, K. (1995). Creating false memories: Remembering words not presented in lists.
Journal of Experimental Psychology: Learning, Memory, and Cognition, 21, 803–814. American Psychological Association.
The fact that people make intrusion errors is not particularly surprising. However, the strength of the effect is astonishing. In routine studies, the DRM lures as many as 70% of the participants. The most obvious way to reduce this effect would be to simply explain the DRM procedure and warn participants that intrusions may occur. Although this approach has proved effective in reducing
intrusions, false memories still occur (Gallo et al., 1997). Obviously, intrusions are very difficult to prevent, but not because memory is prone to mistakes. In fact, memory is generally accurate and extremely efficient, given the millions of bits of information we encounter every day. Instead, the DRM effect reflects the fact that normal memory processes are constructive.
A second method of creating false memories in the laboratory comes from doctored photographs. For instance, researchers at the University of Victoria and their colleagues exposed undergraduate research participants to altered photographs showing the participant and his or her parent taking a ride on a hot-
air balloon, an event that did not actually occur (Wade et al., 2002). For this type of experiment to work, the volunteers in the study had to recruit the help of their family. Their parents provided pictures of the participant from early childhood, along with an explanation of the event, the location, and the people and objects in the photo. The researchers took one of the pictures and digitally cut and pasted it into a balloon ride. On three occasions the participants went through the set of pictures, the true originals plus the doctored photo, in a structured interview process (the kind designed to help police get more details from eyewitnesses). By the end of the third session, half the participants had some
memory for the balloon ride event, even though it never occurred (Wade et al., 2002).
Photographic images such as the ones used in the hot-air balloon study leave it
to the participant to fill in the gaps as to what “happened” on their balloon ride. Other researchers have gone so far as to create false videotaped evidence of an
event (R. Nash et al., 2009). For this method, a volunteer was videotaped watching a graduate student perform an action. The researchers also videotaped the graduate student performing an additional action that the volunteer did not witness. The videos were then spliced together to show the volunteer watching an event that she, in reality, did not actually see. Now imagine you were shown a video of yourself watching an action you had not seen before—would you believe it? In fact, a significant portion of the individuals did form memories of the events they had never witnessed. This type of false memory retrieval mirrors that created in the guided imagery exercises used in some clinical settings, a trend that sparked a very contentious debate in both the scientific and legal communities.
In one study of false memory, true photos were obtained from volunteers’ families (top), and were edited to look like a balloon ride (bottom). About half of the volunteers in this study came to recall some details of an event that never happened to them. Courtesy of K. Wade, M. Garry, J. Read, and S. Lindsay
The Danger of False Remembering
In the early 1990s, Beth Rutherford sought the help of her church counsellor to deal with personal issues. During their sessions, the counsellor managed to convince her that her father, a minister, had raped her. The memory was further elaborated so that she remembered becoming pregnant and that her father had forced her to undergo an abortion using a coat hanger. You can imagine what kind of effects this had on the family. Her father had little choice but to resign from his position, and his reputation was left in shambles. Although it can be difficult to prove some false memories, this incident is particularly disturbing
because it could have been supported by medical evidence. When a medical
investigation was finally conducted, absolutely no evidence was found that Beth
had ever been raped or that she had ever been pregnant (Loftus, 1997).
In this example, Beth’s therapist believed that Beth had experienced a recovered memory , a memory of a traumatic event that is suddenly recovered after blocking the memory of that event for a long period of time, often many years. However, the topic of recovered memories is a contentious one. In the past three decades, psychologists have performed a great deal of research investigating whether it is possible to suppress a memory and whether there are research tools available to help us distinguish between memories that are accurate and those that are not.
This idea that we suppress traumatic memories is popularly known as repression from Freudian psychoanalysis (see Module 12.3 ). According to this idea, a repressed memory could still affect other psychological processes, leading people to suffer in other ways such as experiencing depression. This school of thought suggests that if a repressed memory can be recovered, then a patient can find ways to cope with the trauma. Some therapists espouse this view and use techniques such as hypnosis and guided imagery to try to unearth repressed memories. However, given the research we have discussed about how false memories can be implanted through these types of techniques, there is an obvious danger in the use of these methods.
Can we suppress our memories of traumatic life events? As it turns out, it is
possible, although it is difficult to determine how common it is. In one survey study, researchers examined the testimony of people who had been imprisoned in Camp Erika, a Nazi concentration camp in The Netherlands, in the early 1940s
(Wagenaar & Groeneweg, 1990). Most of the prisoners were able to provide detailed information about their time in the concentration camp, but a minority of prisoners did not remember many emotional events during their imprisonment including the names and appearances of people who tortured them and the fact that they had witnessed murders! But, being able to suppress a horrific memory is very different from then recovering that memory years later.
Recovered memories, like many other types of long-term memory, are difficult to
study because one can rarely determine if they are true or false. This uncertainty
has led to the recovered memory controversy , a heated debate among psychologists about the validity of recovered memories (Davis & Loftus, 2009). On one side of the controversy are some clinical mental health workers (although certainly not the majority) who regularly attempt to recover memories they suspect have been repressed. On the opposing side are the many psychologists who point out that the techniques that might help “recover” a memory bear a striking resemblance to those that are used to create false memories in laboratory research; they often involve instructions to remember, attempts to
form images, and social reinforcement for reporting memories (Spanos et al., 1994). How can this disagreement be resolved?
One method is to use brain imaging to differentiate true and false memories. Psychologists have found that when people recount information that is true, the visual and other sensory areas of the brain become more active. When revealing falsely remembered information, these same individuals have much less activity in the sensory regions—the brain is not drawing on mental imagery because it
was not there in the first place (Dennis et al., 2012; Stark et al., 2010). Interestingly, these brain results do not always map onto the participants’ conscious memories of what they had seen. So, this method might be able to distinguish between true and false memories better than the participant himself
(M. K. Johnson et al., 2012). However, although these neuroimaging results are promising, these studies did not use stimuli that were as emotional as the recovered memories patients report. Therefore, as with most areas of psychology, much more research is needed in this controversial area.
Although this module provides some frightening examples of how malleable our memories are, there is actually something inspirational about these results. We construct our own memories and, as a result, our own reality. Therefore, we have the power to focus our memories on the positive experiences of our lives, or on the negative ones. It’s up to you—remember that.
Module 7.3b Quiz:
Memory Reconstruction
Know . . . 1. If you are presented with a list of 15 words, all of which have something
in common, you are most likely participating in a study focusing on
. A. misinformation effects B. the DRM procedure C. imagination inflation D. repression
2. Which of the following effects demonstrates that one can change the details of a memory just by phrasing a question a certain way?
A. Misinformation effects B. The DRM procedure C. Imagination inflation D. Repression
Apply . . . 3. Jonathan witnessed a robbery. The police asked him to identify the
perpetrator from a lineup. You can be most confident in his selection if
A. the authorities smiled after Jonathan’s response so that he would feel comfortable during the lineup procedure.
B. the authorities had the lineup presented all at the same time so Jonathan could compare the individuals.
C. the lineup included individuals of different races and ethnicities. D. Jonathan was given the option to not choose any of the people
from the lineup if no one fit his memory.
Analyze . . . 4. Psychologists who study false memories have engaged in a debate over
the validity of recovered memories. Why are they skeptical about claims of recovered memories?
A. They have never experienced recovered memories themselves. B. Many of the techniques used to recover memories in therapy bear
a striking similarity to the techniques used to create false
memories in research.
C. Brain scans can easily distinguish between true and false memories.
D. Scientists have proven that it is impossible to remember something that you have once forgotten.
Module 7.3 Summary
constructive memory
DRM procedure
false memory
imagination inflation
misinformation effect
recovered memory
recovered memory controversy
schema
Schemas guide our attention, telling us what to expect in certain circumstances. They organize long-term memories and provide us with cues when it comes time to retrieve those memories.
Psychologists have found that a number of factors contribute to the construction of false memories, including misinformation, imagination inflation, and the
Know . . . the key terminology used in discussing how memories are organized and constructed.
7.3a
Understand . . . how schemas serve as frameworks for encoding and constructing memories.
7.3b
Understand . . . how psychologists can produce false memories in the laboratory.
7.3c
semantic similarities used in the DRM procedure.
Eyewitness testimony is absolutely crucial to the operation of most legal systems, but how reliable is it? Since 1989, 225 U.S.-based cases of exonerations (convictions that have been overturned due to new evidence after the trial) have been made possible thanks to the help of The Innocence Project. In these cases, the original convictions were based on the following information (some cases included multiple sources):
Eyewitness misidentification (173 cases) Improper or unvalidated forensics (116 cases) False confessions (51 cases) Questionable information from informants (36 cases)
Apply Activity What percentage of the exonerations mentioned above involved eyewitness mistakes? What do these data suggest about research on eyewitness testimony?
You should first understand the premise behind the idea of recovered memories: Some people believe that if a memory is too painful, it might be blocked from conscious recollection, only to be recovered later through therapeutic techniques. Others argue that it is difficult to prove that a “recovered” memory is actually real, as opposed to falsely constructed. Given how easy it is to create false memories, they argue, any memory believed to be recovered should be viewed with skepticism.
Apply . . . what you have learned to judge the reliability of eyewitness testimony.
7.3d
Analyze . . . the arguments in the “recovered memory” debate.7.3e
Chapter 8 Thought and Language
8.1 The Organization of Knowledge Concepts and Categories 315
Working the Scientific Literacy Model: Priming and Semantic Networks 318
Module 8.1a Quiz 319
Memory, Culture, and Categories 319
Module 8.1b Quiz 323
Module 8.1 Summary 323
8.2 Problem Solving, Judgment, and Decision Making Defining and Solving Problems 325
Module 8.2a Quiz 328
Judgment and Decision Making 328
Working the Scientific Literacy Model: Maximizing and Satisficing in Complex Decisions 332
Module 8.2b Quiz 334
Module 8.2 Summary 335
8.3 Language and Communication
What Is Language? 337
Module 8.3a Quiz 341
The Development of Language 341
Module 8.3b Quiz 344
Genes, Evolution, and Language 344
Working the Scientific Literacy Model: Genes and Language 344
Module 8.3c Quiz 348
Module 8.3 Summary 348
Module 8.1 The Organization of Knowledge
Dmitry Vereshchagin/Fotolia
Learning Objectives
Know . . . the key terminology associated with concepts and categories. Understand . . . theories of how people organize their knowledge about the world. Understand . . . how experience and culture can shape the way we organize our knowledge. Apply . . . your knowledge to identify prototypical examples.
8.1a 8.1b
8.1c
8.1d
When Edward regained consciousness in the hospital, his family immediately noticed that something was wrong. The most obvious problem was that he had difficulty recognizing faces, a relatively common disorder known as prosopagosia. As the doctors performed more testing, it became apparent that Edward had other cognitive problems as well. Edward had difficulty recognizing objects—but not all objects. Instead, he couldn’t distinguish between different vegetables even though he could use language to describe their appearance. His ability to recognize most other types of objects seemed normal.
Neurological patients like Edward may seem unrelated to your own life. However, for specific categories of visual information to be lost, they must have been stored in similar areas of the brain before brain damage occurred. Therefore, these cases give us some insight into how the brain stores and organizes the information that we have encoded into memory.
Focus Questions
1. How do people form easily recognizable categories from complex information?
2. How does culture influence the ways in which we categorize information?
Each of us has amassed a tremendous amount of knowledge in the course of our lifetime. Indeed, it is impossible to put a number on just how many facts each of us knows. Imagine trying to record everything you ever learned about the world—how many books could you fill? Instead of asking how much we know, psychologists are interested in how we keep track of it all. In this module, we will explore what those processes are like and how they work. We will start by learning about the key terminology before presenting theories about how
Analyze . . . the claim that the language we speak determines how we think.
8.1e
knowledge is stored over the long term.
Concepts and Categories
A concept is the mental representation of an object, event, or idea. Although it seems as though different concepts should be distinct from each other, there are actually very few independent concepts. You do not have just one concept
for chair, one for table, and one for sofa. Instead, each of these concepts can be divided into smaller groups with more precise labels, such as arm chair or coffee table. Similarly, all of these items can be lumped together under the single label, furniture. Psychologists use the term categories to refer to these clusters of interrelated concepts. We form these groups using a process called categorization.
Classical Categories: Definitions and Rules
Categorization is difficult to define in that it involves elements of perception
(Chapter 4 ), memory (Chapter 7 ), and “higher-order” processes like decision making (Module 8.2 ) and language (Module 8.3 ). The earliest approach to the study of categories is referred to as classical categorization ; this theory claims that objects or events are categorized according to a certain set of rules or by a specific set of features—something similar to a dictionary definition (Lakoff & Johnson, 1999; Rouder & Ratcliffe, 2006). Definitions do a fine job of explaining how people categorize items, at least in certain situations. For example, a triangle can be defined as “a figure
(usually, a plane rectilinear figure) having three angles and three sides” (Oxford English Dictionary, 2011). Using this definition, you should find it easy to categorize the triangles in Figure 8.1 .
Figure 8.1 Using the Definition of a Triangle to Categorize Shapes
Classical categorization does not tell the full story of how categorization works, however. We use a variety of cognitive processes in determining which objects fit
which category. One of the major problems we confront in this process is graded membership —the observation that some concepts appear to make better category members than others. For example, see if the definition in Table 8.1
fits your definition of bird and then categorize the items in the table.
Table 8.1 Categorizing Objects According to the Definition of Bird
Definition: “Any of the class Aves of warm-blooded, egg-laying, feathered vertebrates
with forelimbs modified to form wings.” (American Heritage Dictionary, 2016)
Now categorize a set of items by answering yes or no regarding the truth of the
following sentences.
1. A sparrow is a bird.
2. An apple is a bird.
3. A penguin is a bird.
Ideally, you said yes to the sparrow and penguin, and no to the apple. But did you notice any difference in how you responded to the sparrow and penguin? Psychologists have researched classical categorization using a behavioural
measure known as the sentence-verification technique, in which volunteers wait for a sentence to appear in front of them on a computer screen and respond as quickly as they can with a yes or no answer to statements such as “A sparrow is a bird,” or, “A penguin is a bird.” The choice the participant makes, as well as her reaction time to respond, is measured by the researcher. Sentence-verification shows us that some members of a category are recognized faster than others
(Olson et al., 2004; Rosch & Mervis, 1975). In other words, subjects almost always answer “yes” faster to sparrow than to penguin. This seems to go against a classical, rule-based categorization system because both sparrows and penguins are equally good fits for the definition, but sparrows are somehow perceived as being more bird-like than penguins. Thus, a modern approach to categorization must explain how “best examples” influence how we categorize items.
Prototypes: Categorization by Comparison
When you hear the word bird, what mental image comes to mind? Does it resemble an ostrich? Or is your image closer to a robin, sparrow, or blue jay? The likely image that comes to mind when you imagine a bird is what
psychologists call a prototype (see Figure 8.2 ). Prototypes are mental representations of an average category member (Rosch, 1973). If you took an average of the three most familiar birds, you would get a prototypical bird.
Figure 8.2 A Prototypical Bird Left: chatursunil/Shutterstock; centre: Al Mueller/Shutterstock; right: Leo/Shutterstock
Prototypes allow for classification by resemblance. When you encounter a little creature you have never seen before, its basic shape—maybe just its silhouette —can be compared to your prototype of a bird. A match will then be made and you can classify the creature as a bird. Notice how different this process is from classical categorization: No rules or definitions are involved, just a set of similarities in overall shape and function.
The main advantage of prototypes is that they help explain why some category members make better examples than others. Ostriches are birds just as much as blue jays are, but they do not resemble the rest of the family very well. In other words, blue jays are closer to the prototypical bird.
Now that you have read about categories based on a set of rules or characteristics (classical categories) and as a general comparison based on resemblances (prototypes), you might wonder which approach is correct.
Research says that we can follow either approach—the choice really depends on how complicated a category or a specific example might be. If there are a few major distinctions between items, we use resemblance; if there are
complications, we switch to rules (Feldman, 2003; Rouder & Ratcliff, 2004, 2006). For example, in the case of seeing a bat dart by, your first impression might be “bird” because it resembles a bird. But if you investigated further, you will see that a bat fits the classical description of a mammal, not a bird. In other words, it has hair, gives live birth rather than laying eggs, and so on.
Networks and Hierarchies
Classical categorization and prototypes only explain part of how we organize information. Each concept that we learn about has similarities to other concepts. A sparrow has physical similarities to a bat (e.g., size and shape); a sparrow will have even more in common with a robin because they are both birds (e.g., size, shape, laying eggs, etc.). These connections among ideas can be represented in
a network diagram known as a semantic network , an interconnected set of nodes (or concepts) and the links that join them to form a category (see Figure 8.3 ). Nodes are circles that represent concepts, and links connect them together to represent the structure of a category as well as the relationships
among different categories (Collins & Loftus, 1975). In these networks, similar items have more, and stronger, connections than unrelated items.
Figure 8.3 A Semantic Network Diagram for the Category “Animal” The nodes include the basic-level categories, Bird and Fish. Another node represents the broader category of Animal, while the lowest three nodes represent the more specific categories of Robin, Emu, and Trout. Source: Based on Collins, A. M., & Quillian, M. R. (1969). Retrieval time from semantic memory. Journal of Verbal Learning
and Verbal Behavior, 8, 240–248.
Something you may notice about Figure 8.3 is that it is arranged in a hierarchy—that is, it consists of a structure moving from general to very specific. This organization is important because different levels of the category are useful in different situations. The most frequently used level, in both thought and
language, is the basic-level category, which is located in the middle row of the diagram (where birds and fish are) (Johnson & Mervis, 1997; Rosch et al., 1976). A number of qualities make the basic-level category unique:
Basic-level categories are the terms used most often in conversation. They are the easiest to pronounce. They are the level at which prototypes exist. They are the level at which most thinking occurs.
To get a sense for how different category levels influence our thinking, we can compare sentences referring to an object at different levels. Consider what would happen if someone approached you and made any one of the following statements:
There’s an animal in your yard. There’s a bird in your yard. There’s a robin in your yard.
The second sentence—”There’s a bird in your yard”—is probably the one you are most likely to hear, and it makes reference to a basic level of a category
(birds). Many people would respond that the choice of animal as a label indicates confusion, claiming that if the speaker knew it was a bird, he should have said so; otherwise, it sounds like he is trying to figure out which kind of animal he is
looking at. Indeed, superordinate categories like “animal” are generally used when someone is uncertain about an object or when he or she wishes to group together a number of different examples from the basic-level category (e.g.,
birds, cats, dogs). In contrast, when the speaker identifies a subordinate-level category like robin, it suggests that there is something special about this particular type of bird. It may also indicate that the speaker has expert-level knowledge of the basic category and that using the more specific level is necessary to get her point across in the intended way.
In order to demonstrate the usefulness of semantic networks in our attempt to explain how we organize knowledge, complete this easy test based on the
animal network in Figure 8.3 . If you were asked to react to dozens of sentences, and the following two sentences were included among them, which do you think you would mark as “true” the fastest?
A robin is a bird. A robin is an animal.
As you can see in the network diagram, robin and bird are closer together; in fact, to connect robin to animal, you must first go through bird. Sure enough,
people regard the sentence “A robin is a bird” as a true statement faster than “A robin is an animal.”
Now consider another set of examples. Which trait do you think you would verify faster?
A robin has wings. A robin eats.
Using the connecting lines as we did before, we can predict that it would be the first statement about wings. As research shows, our guess would be correct. These results demonstrate that how concepts are arranged in semantic networks can influence how quickly we can access information about them.
Working the Scientific Literacy Model Priming and Semantic Networks
The thousands of concepts and categories in long-term memory are not isolated, but connected in a number of ways. What are the consequences of forming all the connections in semantic networks?
What do we know about semantic networks? In your daily life, you notice the connections within semantic networks anytime you encounter one aspect of a category and other related concepts seem to come to mind. Hearing the word “fruit,” for example, might lead you to think of an apple, and the apple may lead you to think of a computer, which may lead you to think of a paper that is due tomorrow. These associations
illustrate the concept of priming —the activation of individual concepts in long-term memory. Interestingly, research has shown that priming can also occur without your awareness; “fruit” may not have brought the image of a watermelon to mind, but the
concept of a watermelon may have been primed nonetheless.
How can science explain priming effects? Psychologists can test for priming through reaction time measurements, such as those in the sentence verification tasks
discussed earlier or through a method called the lexical decision task. With the lexical decision method, a volunteer sits at a computer and stares at a focal point. Next, a string of letters flashes on the screen. The volunteer responds yes or no as quickly as possible to indicate whether the letters spell a word
(see Figure 8.4 ). Using this method, a volunteer should respond faster that “apple” is a word if it follows the word “fruit”
(which is semantically related) than if it follows the word “bus” (which is not semantically related).
Figure 8.4 A Lexical Decision Task
In a lexical decision task, an individual watches a computer screen as strings of letters are presented. The participant must respond as quickly as possible to indicate whether the letters spell a word (e.g., “desk”) or are a non-word (e.g., “sekd”).
Given that lexical decision tasks are highly controlled experiments, we might wonder if they have any impact outside of the laboratory. One test by Jennifer Coane suggests that priming
does occur in everyday life (Coane & Balota, 2009). Coane’s research team invited volunteers to participate in lexical decision
tasks about holidays at different times of the year. The words they chose were based on the holiday season at that time. Sure enough, without any laboratory priming, words such as “nutcracker” and “reindeer” showed priming effects at times when
they were congruent (or “in season”) in December, relative to other times of the year (see Figure 8.5 ). Similarly, words like “leprechaun” and “shamrock” showed a priming effect during the month of March. Because the researchers did not instigate the priming, it must have been the holiday spirit at work: Decorations and advertisements may serve as constant primes.
Figure 8.5 Priming Affects the Speed of Responses on a Lexical Decision Task
Average response times were faster when the holiday-themed
words were congruent (in season), as represented by the blue bars. This finding is consistent for both the first half and the second half of the list of words.
Source: Republished with permission of Springer, from Priming the Holiday Spirit: Persistent
Activation due to Extraexperimental Experiences Fig. 1, Pg.1126, Psychonomic Bulletin & Review, 16
(6), 1124–1128, 2009. Permission conveyed through Copyright Clearance Center, Inc.
Can we critically evaluate this information? Priming influences thought and behaviour, but is certainly not all- powerful. In fact, it can be very weak at times. Because the strength of priming can vary a great deal, some published experiments have been very difficult to replicate—an important criterion of quality research. So, while most psychologists agree that priming is an important area of research, there have been very open debates at academic conferences and in peer- reviewed journals about the best way to conduct the research
and how to interpret the results (Cesario, 2014; Klatzky & Creswell, 2014).
Why is this relevant? Advertisers know all too well that priming is more than just a curiosity; it can be used in a controlled way to promote specific behaviours. For example, cigarette advertising is not allowed on television stations, but large tobacco companies can sponsor anti-smoking ads. Why would a company advertise against its own product? Researchers brought a group of smokers into the lab to complete a study on television programming and subtly included a specific type of advertisement between segments (they did not reveal the true purpose of the study until after it was completed). Their participants were four times as likely to light up after watching a tobacco-company anti-smoking ad than if they saw the control group ad about supporting a youth sports league
(Harris et al., 2013). It would appear that while the verbal message is “don’t smoke,” the images actually prime the behaviour. Fortunately, more healthful behaviours have been promoted through priming; for example, carefully designed
primes have been shown to reduce mindless snacking (Papies &
Hamstra, 2010) and binge-drinking in university students (Goode et al., 2014).
Module 8.1a Quiz:
Concepts and Categories
Know . . . 1. A is a mental representation of an average member of a
category.
A. subordinate-level category B. prototype C. similarity principle D. network
2. refer to mental representations of objects, events, or ideas. A. Categories B. Concepts C. Primings D. Networks
Understand . . . 3. Classical categorization approaches do not account for , a type
of categorization that notes some items make better category members than others.
A. basic-level categorization B. prototyping C. priming D. graded membership
Memory, Culture, and Categories
In the first part of this module, we examined how we group together concepts to form categories. However, it is important to remember that these processes are based, at least in part, on our experiences. In this section of the module, we examine the role of experience—both in terms of memory processes and cultural influences—on our ability to organize our vast stores of information.
Categorization and Experience
People integrate new stimuli into categories based on what they have
experienced before (Jacoby & Brooks, 1984). When we encounter a new item, we select its category by retrieving the item(s) that are most similar to it from
memory (Brooks, 1978). Normally, these procedures lead to fast and accurate categorization. If you see an animal with wings and a beak, you can easily retrieve from memory a bird that you previously saw; doing so will lead you to infer that this new object is a bird, even if it is a type of bird that you might not have encountered before.
However, there are also times when our reliance on previously experienced items can lead us astray. In a series of studies with medical students and practising physicians, Geoffrey Norman and colleagues at McMaster University found that recent exposure to an example from one category can bias how
people diagnose new cases (Leblanc et al., 2001; Norman, Brooks, et al., 1989; Norman, Rosenthal, et a., 1989). In one experiment, medical students were taught to diagnose different skin conditions using written rules as well as photographs of these diseases. Some of the photographs were typical examples of that disorder whereas other photographs were unusual cases that resembled other disorders. When tested later, the participants were more likely to rely on the previously viewed photographs than they were on the rules (a fact that would surprise most medical schools); in fact, the unusual photographs viewed during training even led to wrong diagnoses for test items that were textbook examples
of that disorder (Allen et al., 1992)! This shows the power that our memory can have on how we take in and organize new information. As an aside, expert physicians were accurate over 90% of the time in most studies, so you can still trust your doctor.
Categories, Memory, and the Brain
The fact that our ability to make categorical decisions is influenced by previous experiences tells us that this process involves memory. Studies of neurological patients like the man discussed at the beginning of this module provide a unique perspective on how these memories are organized in the brain. Some patients with damage to the temporal lobes have trouble identifying objects such as pictures of animals or vegetables despite the fact that they were able to describe the different shapes that made up those objects (i.e., they could still see). The
fact that these deficits were for particular categories of objects was intriguing, as it suggested that damaging certain parts of the brain could impair the ability to recognize some categories while leaving others unaffected (Warrington &
McCarthy, 1983; Warrington & Shallice, 1979). Because these problems were isolated to certain categories, these patients were diagnosed as having a
disorder known as category specific visual agnosia (or CSVA).
Early attempts to find a pattern in these patients’ deficits focused on the
distinction between living and non-living categories (see Figure 8.6 ). Several patients with CSVA had difficulties identifying fruits, vegetables, and/or animals but were still able to accurately identify members of categories such as tools and
furniture (Arguin et al., 1996; Bunn et al., 1998). However, although CSVA has been observed in a number of patients, researchers also noted that it would be
physically impossible for our brains to have specialized regions for every category we have encountered. There simply isn’t enough space for this to occur. Instead, they proposed that evolutionary pressures led to the development
of specialized circuits in the brain for a small group of categories that were important for our survival. These categories included animals, fruits and
vegetables, members of our own species, and possibly tools (Caramazza & Mahon, 2003). Few, if any, other categories involve such specialized memory storage. This theory can explain most, but not all, of the problems observed in the patients tested thus far. It is also in agreement with brain-imaging studies showing that different parts of the temporal lobes are active when people view
items from different categories including animals, tools, and people (Martin et
al., 1996). Thus, although different people will vary in terms of the exact location that these categories are stored, it does appear that some categories are stored separately from others.
Figure 8.6 Naming Errors for a CSVA Patient Patients with CSVA have problems identifying members of specific categories. When asked to identify the object depicted by different line drawings, patient E. W. showed a marked impairment for the recognition of animals. Her ability to name items from other categories demonstrated that her overall perceptual abilities were preserved. Source: Based on data from Caramazza, A., & Mahon, B. Z. (2003). The organization of conceptual knowledge: the evidence
from category-specific semantic deficits. Trends in Cognitive Sciences, 7 (8), 354–361.
Biopsychosocial Perspectives Culture and
Categorical Thinking Animals, relatives, household appliances, colours, and other entities all fall into categories. However, people from different cultures might differ in how they categorize such objects. In North America, cows are sometimes referred to as “livestock” or “food animals,” whereas in India, where cows are regarded as sacred, neither category would apply.
In addition, how objects are related to each other differs considerably across cultures. Which of the two photos in Figure 8.7 a do you think someone from North America took? Researchers asked both American and Japanese university students to take a picture of someone, from whatever angle or degree of focus they chose. American students were more likely to take close-up pictures, whereas Japanese students
typically included surrounding objects (Nisbett & Masuda, 2003). When asked which two objects go together in Figure 8.7 b, American college students tend to group cows with chickens—because both are animals. In contrast, Japanese students coupled cows with grass, because grass
is what cows eat (Gutchess et al., 2010; Nisbett & Masuda, 2003). These examples demonstrate cross-cultural differences in perceiving how objects are related to their environments. People raised in North America tend to focus on a single characteristic, whereas Japanese people tend to view objects in relation to their environment.
Figure 8.7 Your Culture and Your Point of View (a) Which of these two pictures do you think a North American would be more likely to take? (b) Which two go together? Top photos: Blend Images/Shutterstock
Source, bottom: Adapted from Nisbett, R. E., & Masuda, T. (2003). Culture and point of view. Proceedings of the
National Academy of Sciences, 100 (19), 11163–11170. Copyright © 2003. Reprinted by permission of National
Academy of Sciences.
Researchers have even found differences in brain function when people
of different cultural backgrounds view and categorize objects (Park & Huang, 2010). Figure 8.8 reveals differences in brain activity when
Westerners and East Asians view photos of objects, such as an animal, against a background of grass and trees. Areas of the brain devoted to processing both objects (lateral parts of the occipital lobes) and background (the parahippocampal gyrus, an area underneath the hippocampus) become activated when Westerners view these photos, whereas only areas devoted to background processes become activated
in East Asians (Goh et al., 2007). These findings demonstrate that a complete understanding of how humans categorize objects requires application of the biopsychosocial model.
Figure 8.8 Brain Activity Varies by Culture Brain regions that are involved in object recognition and processing are activated differently in people from Western and Eastern cultures. Brain regions that are involved in processing individual objects are more highly activated when Westerners view focal objects against background scenery, whereas people from East Asian countries appear to attend to background scenery more closely than focal objects. Source: Park, D. C. & Huang, C.-M. (2010). Culture wires the brain: A cognitive neuroscience perspective.
Perspectives on Psychological Science, 5 (4), 391–400. Reprinted by permission of SAGE Publications.
Myths in Mind How Many Words for Snow?
Cultural differences in how people think and categorize items have led to
the idea of linguistic relativity (or the Whorfian hypothesis)—the theory that the language we use determines how we understand (and categorize) the world. One often-cited example is about the Inuit in Canada’s Arctic regions, who are thought to have many words for snow,
each with a different meaning. For example, aput means snow that is on the ground, and gana means falling snow. This observation, which was made in the early 19th century by anthropologist Franz Boas, was often repeated and exaggerated, with claims that Inuit people had dozens of words for different types of snow. With so many words for snow, it was thought that perhaps the Inuit people perceive snow differently than someone who does not live near it almost year-round. Scholars used the example to argue that language determines how people categorize the world.
Research tells us that we must be careful in over-generalizing the influence of language on categorization. The reality is that the Inuit seem to categorize snow the same way a person from the rest of Canada does. Someone from balmy Winnipeg can tell the difference between falling snow, blowing snow, sticky snow, drifting snow, and “oh-sweet-God-it’s- snowing-in-May-snow,” just as well as an Inuit who lives with snow for
most of the year (Martin, 1986). Therefore, we see that the linguistic relativity hypothesis is incorrect in this case: The difference in vocabulary for snow does not lead to differences in perception.
Categories and Culture
The human brain is wired to perceive similarities and differences and, as we learned from prototypes, the end result of this tendency is to categorize items based on these comparisons as well as on our previous experiences with members of different categories. However, our natural inclination to do so interacts with our cultural experiences; how we categorize objects depends to a great extent on what we have learned about those objects from others in our culture.
Various researchers have explored the relationships between culture and categorization by studying basic-level categories among people from different cultural backgrounds. For example, researchers have asked individuals from traditional villages in Central America to identify a variety of plants and animals that are extremely relevant to their diet, medicine, safety, and other aspects of their lives. Not surprisingly, these individuals referred to plants and animals at a
more specific level than North American university students would (Bailenson et al., 2002; Berlin, 1974). Thus, categorization is based—at least to some extent —on cultural learning. Psychologists have also discovered that cultural factors influence not just how we categorize individual objects, but also how objects in our world relate to one another.
Although culture and memory both clearly affect how we describe and categorize our world, we do need to remember to critically analyze the results of these studies. Specifically, as our world becomes more Westernized, it is possible— even likely—that these cultural differences will decrease. These results, then, tell
us about cultural differences at a given time. As you saw in the Myths in Mind feature above, we should also exercise caution when reading about another form of cultural influences on categorization—linguistic relativity.
Module 8.1b Quiz:
Memory, Culture, and Categories
Know . . . 1. The idea that our language influences how we understand the world is
referred to as . A. the context specificity hypothesis B. sentence verification C. the Whorfian hypothesis D. priming
Understand . . . 2. A neurologist noticed that a patient with temporal-lobe damage seemed
to have problems naming specific categories of objects. Based upon
what you read in this module, which classes of objects are most likely to be affected by this damage?
A. Animals and tools B. Household objects that he would use quite frequently C. Fruits and vegetables D. Related items such as animals and hunting weapons
Apply . . . 3. Janice, a medical school student, looked at her grandmother’s hospital
chart. Although her grandmother appeared to have problems with her intestines, Janice thought the pattern of the lab results resembled those of a patient with lupus she had seen in the clinic earlier that week. Janice is showing an example of
A. how memory for a previous example can influence categorization decisions.
B. how people rely on prototypes to categorize objects and events. C. how we rely on a set of rules to categorize objects. D. how we are able to quickly categorize examples from specific
categories.
Analyze . . . 4. Research on linguistic relativity suggests that
A. language has a complete control over how people categorize the world.
B. language can have some effects on categorization, but the effects are limited.
C. language has no effect on categorization. D. researchers have not addressed this question.
Module 8.1 Summary
categories
Know . . . the key terminology associated with concepts and categories.
8.1a
classical categorization
concept
graded membership
linguistic relativity (Whorfian hypothesis)
priming
prototypes
semantic network
Certain objects and events are more likely to be associated in clusters. The priming effect demonstrates this phenomenon; for example, hearing the word “fruit” makes it more likely that you will think of “apple” than, say, “table.” More specifically, we organize our knowledge about the world through semantic networks, which arrange categories from general to specific levels. Usually we think in terms of basic-level categories, but under some circumstances we can be either more or less specific. Studies of people with brain damage suggest that the neural representations of members of evolutionarily important categories are stored together in the brain. These studies also show us that our previous experience with a category can influence how we categorize and store new stimuli in the brain.
One of many possible examples of this influence was discussed. Specifically, ideas of how objects relate to one another differ between people from North America and people from Eastern Asia. People from North America (and Westerners in general) tend to focus on individual, focal objects in a scene, whereas people from Japan tend to focus on how objects are interrelated.
Understand . . . theories of how people organize their knowledge about the world.
8.1b
Understand . . . how experience and culture can shape the way we organize our knowledge.
8.1c
Apply Activity Try the following questions for practice.
1. What is the best example for the category of fish: a hammerhead shark, a trout, or an eel?
2. What do you consider to be a prototypical sport? Why? 3. Some categories are created spontaneously, yet still have prototypes.
For example, what might be a prototypical object for the category “what to save if your house is on fire”?
Researchers have shown that language can influence the way we think, but it cannot entirely shape how we perceive the world. For example, people can perceive visual and tactile differences between different types of snow even if they don’t have unique words for each type.
Apply . . . your knowledge to identify prototypical examples.8.1d
Analyze . . . the claim that the language we speak determines how we think.
8.1e
Module 8.2 Problem Solving, Judgment, and Decision Making
Polaris/Newscom
Learning Objectives
Ki-Suck Han was about to die. He had just been shoved onto the subway’s tracks and was desperately scrambling to climb back onto the station’s platform as the subway train rushed toward him. If you were a few metres away from Mr. Han, what would you have done? What factors would have influenced your actions?
In this case, the person on the platform was R. Umar Abbasi, a freelance photographer working for The New York Post. Mr. Abbasi did not put down his camera and run to help Mr. Han. Instead, he took a well-framed photograph that captured the terrifying scene. The photograph was published on the front page of the Post and was immediately condemned by people who were upset that the photographer didn’t try to save Mr. Han’s life (and that the Post used the photograph to make money). In a statement released to other media outlets, the Post claimed that Mr. Abbasi felt that he wasn’t strong enough to lift the man and instead tried to use his camera’s flash to signal the driver. According to this explanation, Mr. Abbasi analyzed the situation and selected a course of action that he felt would be most helpful. Regardless of whether you believe this account, it does illustrate an important point: Reasoning and decision making can be performed in a number of ways and can be influenced by a number of factors. That is why we don’t all respond the same way to the same situation.
Know . . . the key terminology of problem solving and decision making. Understand . . . the characteristics that problems have in common. Understand . . . how obstacles to problem solving are often self-imposed. Apply . . . your knowledge to determine if you tend to be a maximizer or a satisficer. Analyze . . . whether human thought is primarily logical or intuitive.
8.2a 8.2b 8.2c 8.2d
8.2e
Focus Questions
1. How do people make decisions and solve problems? 2. How can having multiple options lead people to be dissatisfied
with their decisions?
In other modules of this text, you have read about how we learn and remember
new information (Modules 7.1 and 7.2 ) and how we organize our knowledge of different concepts (Module 8.1 ). This module will focus on how we use this information to help us solve problems and make decisions. Although it may seem like such “higher-order cognitive abilities” are distinct from memory and categorization, they are actually a wonderful example of how the different topics within the field of psychology relate to each other. When we try to solve a problem or decide between alternatives, we are actually drawing on our knowledge of different concepts and using that information to try to imagine
different possible outcomes (Green et al., 2006). How well we perform these tasks depends on a number of factors including our problem-solving strategies and the type of information available to us.
Defining and Solving Problems
You are certainly familiar with the general concept of a problem, but in
psychological terminology, problem solving means accomplishing a goal when the solution or the path to the solution is not clear (Leighton & Sternberg, 2003; Robertson, 2001). Indeed, many of the problems that we face in life contain obstacles that interfere with our ability to reach our goals. The challenge, then, is to find a technique or strategy that will allow us to overcome these obstacles. As you will see, there are a number of options that people use for this purpose—although none of them are perfect.
Problem-Solving Strategies and Techniques
Each of us will face an incredible number of problems in our lives. Some of these problems will be straightforward and easy to solve; however, others will be quite complex and will require us to come up with a novel solution. How do we remember the strategies we can use for routine problems? And, how do we develop new strategies for nonroutine problems? Although these questions
appear as if they could have an infinite number of answers, there seem to be two common techniques that we use time and again.
One type of strategy is more objective, logical, and slower, whereas the other is
more subjective, intuitive, and quicker (Gilovich & Griffin, 2002; Holyoak & Morrison, 2005). The difference between them can be illustrated with an example. Suppose you are trying to figure out where you have left your phone. You’ve tried the trick of calling yourself using a landline phone, but you couldn’t
hear it ringing. So, it’s not in your house. A logical approach might involve making of list of the places you’ve been in the last 24 hours and then retracing
your steps until you (hopefully) find your phone. An intuitive approach might involve thinking about previous times you’ve lost your phone or wallet and using these experiences to guide your search (e.g., “I’m always forgetting my phone at Dan’s place, so I should look there first”).
When we think logically, we rely on algorithms , problem-solving strategies based on a series of rules. As such, they are very logical and follow a set of steps, usually in a pre-set order. Computers are very good at using algorithms because they can follow a preprogrammed set of steps and perform thousands of operations every second. People, however, are not always so rule-bound. We tend to rely on intuition to find strategies and solutions that seem like a good fit
for the problem. These are called heuristics , problem-solving strategies that stem from prior experiences and provide an educated guess as to what is the most likely solution. Heuristics are often quite efficient; these “rules of thumb” are usually accurate and allow us to find solutions and to make decisions quickly. In the example of trying to figure out where you left your phone, you are more likely to put your phone down at a friend’s house than on the bus, so that increases the likelihood that your phone is still sitting on his coffee table. Calling your friend to
ask about your phone is much simpler than retracing your steps from class to the gym to the grocery store, and so on.
The overall goal of both algorithms and heuristics is to find an accurate solution as efficiently as possible. In many situations, heuristics allow us to solve problems quite rapidly. However, the trade-off is that these shortcuts can occasionally lead to incorrect solutions, a topic we will return to later in this module.
Of course, different problems call for different approaches. In fact, in some cases, it might be useful to start off with one type of problem-solving and then switch to another. Think about how you might play the children’s word-game
known as hangman, shown in Figure 8.9 . Here, the goal state is to spell a word. In the initial state, you have none of the letters or other clues to guide you. So, your obstacles are to overcome (i.e., fill in) blanks without guessing the wrong letters. How would you go about achieving this goal?
Figure 8.9 Problem Solving in Hangman In a game of hangman, your job is to guess the letters in the word represented by the four blanks to the left. If you get a letter right, your opponent will put it in the correct blank. If you guess an incorrect letter, your opponent will draw a body part on the stick figure. The goal is to guess the word before the entire body is drawn.
On one hand, an algorithm might go like this: Guess the letter A, then B, then C,
and so on through the alphabet until you lose or until the word is spelled. However, this would not be a very successful approach. An alternative algorithm would be to find out how frequently each letter occurs in the alphabet and then guess the letters in that order until the game ends with you winning or losing. So,
you would start out by selecting E, then A, and so on. On the other hand, a heuristic might be useful. For example, if you discover the last letter is G, you might guess that the next-to-last letter is N, because you know that many words end with -ing. Using a heuristic here would save you time and usually lead to an accurate solution.
As you can see, some problems (such as the hangman game) can be approached with either algorithms or heuristics. In other words, most people start out a game like hangman with an algorithm: Guess the most frequent letters until
a recognizable pattern emerges, such as -ing, or the letters -oug (which are often followed by h, as in tough or cough) appear. At that point, you might switch to heuristics and guess which letters would be most likely to fit in the spaces.
Cognitive Obstacles
Using algorithms or heuristics will often allow you to eventually solve a problem; however, there are times when the problem-solving rules and strategies that you have established might actually get in the way of problem solving. The nine-dot
problem (Figure 8.10 ; Maier, 1930) is a good example of such a cognitive obstacle. The goal of this problem is to connect all nine dots using only four straight lines and without lifting your pen or pencil off the paper. Try solving the nine-dot problem before you read further.
Figure 8.10 The Nine-Dot Problem Connect all nine dots using only four straight lines and without lifting your pen or
pencil (Maier, 1930). The solution to the problem can be seen in Figure 8.11 .
Source: Maier, N. F. (1930). Reasoning in humans. I. On direction. Journal of Comparative Psychology, 10 (2), 115–143.
American Psychological Association.
Figure 8.11 One Solution to the Nine-Dot Problem In this case, the tendency is to see the outer edge of dots as a boundary, and to assume that one cannot go past that boundary. However, if you are willing to extend some of the lines beyond the dots, it is actually quite a simple puzzle to complete.
Here is something to think about when solving this problem: Most people impose limitations on where the lines can go, even though those limits are not a part of
the rules. Specifically, people often assume that a line cannot extend beyond the
dots. As you can see in Figure 8.11 , breaking these rules is necessary in order to find a solution to the problem.
Having a routine solution available for a problem generally allows us to solve that problem with less effort than we would use if we encountered it for the first time. This efficiency saves us time and effort. Sometimes, however, routines may impose cognitive barriers that impede solving a problem if circumstances change
so that the routine solution no longer works. A mental set is a cognitive obstacle that occurs when an individual attempts to apply a routine solution to what is actually a new type of problem. Figure 8.12 presents a problem that often elicits a mental set. The answer appears at the bottom of the figure, but make your guess before you check it. Did you get it right? If not, then you probably succumbed to a mental set.
Figure 8.12 The Five-Daughter Problem Maria’s father has five daughters: Lala, Lela, Lila, and Lola. What is the fifth daughter’s name?
The fifth daughter’s name is Maria.
Mental sets can occur in many different situations. For instance, a person may
experience functional fixedness , which occurs when an individual identifies an object or technique that could potentially solve a problem, but can think of only its most obvious function. Functional fixedness can be illustrated with a classic thought problem: Figure 8.13 shows two strings hanging from a ceiling. Imagine you are asked to tie the strings together. However, once you grab a string, you cannot let go of it until both are tied together. The problem is, unless you have extraordinarily long arms, you cannot reach the second string
while you are holding on to the first one (Maier, 1931). So how would you solve the problem? Figure 8.16 offers one possible answer and an explanation of what makes this problem challenging.
Figure 8.13 The Two-String Problem Imagine you are standing between two strings and need to tie them together.
The only problem is that you cannot reach both strings at the same time (Maier, 1931). In the room with you is a table, a piece of paper, a pair of pliers, and a ball of cotton. What do you do? For a solution, see Figure 8.16 .
Figure 8.16 A Solution to the Two-String Problem One solution to the two-string problem from Figure 8.13 is to take the pliers off the table and tie them to one string. This provides enough weight to swing one string back and forth while you grab the other. Many people demonstrate functional fixedness when they approach this problem—they do not think of using the pliers as a weight because its normal function is as a grasping tool.
Problem solving occurs in every aspect of life, but as you can see, there are basic cognitive processes that appear no matter what the context. We identify the goal we want to achieve, try to determine the best strategy to do so, and hope that we do not get caught by unexpected obstacles—especially those we create in our own minds.
Of course, not all problems are negative obstacles that must be overcome. Problem solving can also be part of some positive events as well.
PSYCH@ Problem Solving and Humour
Jokes often involve a problem that needs to be solved. Solving the problem typically requires at least two steps. The initial step requires the audience to detect that some part of the joke’s set-up is not what is
Question: Why can’t university students take exams at the zoo?
Answer: There are too many cheetahs.
expected. Theories of humour sometimes refer to this as incongruity detection. Incongruities create an initial tension. In the example we’re using, the key word in this joke is “cheetahs.” Why would the presence of cheetahs affect exam taking? The trick is to understand that “cheetahs” sounds a lot like “cheaters.” So, a zoo would have “cheetahs,” but an exam could have “cheaters.” Once we understand the incongruity, we no
longer feel any tension. Incongruity resolution has occurred (Suls, 1972).
At this point, the audience has solved the problem. But, is it funny? Wyer and Collins (1992) suggested that for an incongruity resolution to be funny, the audience or reader would need to elaborate on the joke, possibly thinking about how it relates to them or forming humourous
mental images (see Figure 8.14 ). This process of elaboration should, ideally, lead to an emotional response of amusement, although this might differ across cultures.
Figure 8.14 The Comprehension-Elaboration Theory of Humour Humour is a form of problem solving. With most jokes, we identify the incongruity or “twist” involved in the wording of the joke and then attempt to resolve it. Once we have found the solution, we think about (elaborate on) the joke, oftentimes relating it to ourselves or to mental imagery. These processes lead to a feeling of amusement or, in the case of the cheetah joke, a rolling of the eyes. Source: Republished with permission of Elsevier, Inc. from Towards a neural circuit model of verbal humor
processing: An fMRI study of the neural substrates of incongruity detection and resolution, NeuroImage 66 (2013)
169–176. Copyright © 2012. Permission conveyed through Copyright Clearance Center, Inc.
Recent neuroimaging studies have manipulated the characteristics of
verbal stimuli to allow the researchers to identify brain areas related to nonsense stimuli (incongruities that did not undergo cognitive
elaboration) and stimuli that were perceived as humourous (incongruities that did undergo elaboration). Incongruity detection and resolution activated areas in the temporal lobes and the medial frontal lobes (close to the middle of the brain). Elaboration activated a network involving the
left frontal and parietal lobes (Chan et al., 2013). The purpose of this section wasn’t to take the joy out of humour. Instead, it was to show that humour, like most of our behaviours, involves the biopsychosocial model. If we suggested otherwise, we’d be lion.
Module 8.2a Quiz:
Defining and Solving Problems
Know . . . 1. are problem-solving strategies that provide a reasonable
guess for the solution.
A. Algorithms B. Heuristics C. Operators D. Subgoals
Understand . . . 2. Javier was attempting to teach his daughter how to tie her shoes. The
strategy that would prove most effective in this situation would be a(n)
. A. heuristic B. algorithm C. obstacle D. mental set
3. Jennifer was trying to put together her new bookshelf in her bedroom. Unfortunately, she didn’t have a hammer. Frustrated, she went outside
and sat down beside some bricks that were left over from a gardening project. Her inability to see that the bricks could be used to hammer in
nails is an example of . A. a mental set B. an algorithm C. functional fixedness D. a heuristic
Judgment and Decision Making
Like problem solving, judgments and decisions can be based on logical algorithms, intuitive heuristics, or a combination of the two types of thought
(Gilovich & Griffin, 2002; Holyoak & Morrison, 2005). We tend to use heuristics more often than we realize, even those of us who consider ourselves to be logical thinkers. This isn’t necessary a bad thing—heuristics allow us to make efficient judgments and decisions all the time. In this section of the module, we will examine specific types of heuristics, how they positively influence our
decision making, and how they can sometimes lead us to incorrect conclusions.
Conjunction Fallacies and Representativeness
Linda is 31 years old, single, outspoken, and very bright. She majored in philosophy. As
a student, she was deeply concerned with issues of discrimination and social justice,
and also participated in antinuclear demonstrations. Which is more likely?
A. Linda is a bank teller. B. Linda is a bank teller and is active in the feminist movement.
Which answer did you choose? In a study that presented this problem to participants, the researchers reported that (B) was chosen more than 80% of the time. Most respondents stated that option (B) seemed more correct even though option (A) is actually much more likely and would be the correct choice based on
the question asked (Tversky & Kahneman, 1982).
So how is the correct answer (A)? Individuals who approach this problem from the stance of probability theory would apply some simple logical steps. The world has a certain number of (A) bank tellers; this number would be considered the
base rate, or the rate at which you would find a bank teller in the world’s population just by asking random people on the street if they are a bank teller. Among the base group, there will be a certain number of (B) bank tellers who are
feminists, as shown in Figure 8.15 . In other words, the number of bank tellers who are feminists will always be a fraction of (i.e., less than) the total number of bank tellers. But, because many of Linda’s qualities could relate to a “feminist,”
the idea that Linda is a bank teller and a feminist feels correct. This type of error, known as the conjunction fallacy , reflects the mistaken belief that finding a specific member in two overlapping categories (i.e., a member of the conjunction of two categories) is more likely than finding any member of one of the larger, general categories.
Figure 8.15 The Conjunction Fallacy There are more bank tellers in the world than there are bank tellers who are feminists, so there is a greater chance that Linda comes from either (A) or (B) than just (B) alone.
The conjunction fallacy demonstrates the use of the representativeness
heuristic : making judgments of likelihood based on how well an example represents a specific category. In the bank teller example, we cannot identify any traits that seem like a typical bank teller. At the same time, the traits of social activism really do seem to represent a feminist. Thus, the judgment was biased by the fact that Linda seemed representative of a feminist, even though a feminist bank teller will always be rarer than bank tellers in general (i.e., the representativeness heuristic influenced the decision more than logic or mathematical probabilities).
Seeing this type of problem has led many people to question what is wrong with people’s ability to use logic: Why is it so easy to get 80% of the people in a study
to give the wrong answer? In fact, there is nothing inherently wrong with using heuristics; they simply allow individuals to obtain quick answers based on readily available information. In fact, heuristics often lead to correct assumptions about a situation.
Consider this scenario:
You are in a department store trying to find a product that is apparently sold out. At the
end of the aisle, you see a young man in tan pants with a red polo shirt—the typical
employee’s uniform of this chain of stores. Should you stop and consider the
probabilities yielding an answer that was technically most correct?
A. A young male of this age would wear tan pants and a red polo shirt. B. A young male of this age would wear tan pants and a red polo shirt and work at
this store.
Or does it make sense to just assume (B) is correct, and to simply ask the young
man for help (Shepperd & Koch, 2005)? In this case, it would make perfect sense to assume (B) is correct and not spend time wondering about the best logical way to approach the situation. In other words, heuristics often work and, in the process, save us time and effort. However, there are many situations in which these mental shortcuts can lead to biased or incorrect conclusions.
The Availability Heuristic
The availability heuristic entails estimating the frequency of an event based on how easily examples of it come to mind. In other words, we assume that if examples are readily available, then they must be very frequent. For example, researchers asked volunteers which was more frequent in the English language:
A. Words that begin with the letter K B. Words that have K as the third letter
Most subjects chose (A) even though it is not the correct choice. The same thing
happened with the consonants L, N, R, and V, all of which appear as the third letter in a word more often than they appear as the first letter (Tversky & Kahneman, 1973). This outcome reflects the application of the availability heuristic: People base judgments on the information most readily available.
Of course, heuristics often do produce correct answers. Subjects in the same study were asked which was more common in English:
A. Words that begin with the letter K B. Words that begin with the letter T
In this case, more subjects found that words beginning with T were readily available to memory, and they were correct. The heuristic helped provide a quick, intuitive answer.
There are numerous real-world examples of the availability heuristic. In the year following the September 11, 2001 terrorist attacks, people were much more likely to overestimate the likelihood that planes could crash and/or be hijacked. As a result, fewer people flew that year than in the year prior to the attacks, opting instead to travel by car when possible. The availability of the image of planes crashing into the World Trade Center was so vivid and easily retrieved from memory that it influenced decision making. Ironically, this shift proved to be
dangerous, particularly given that driving is statistically much more dangerous than flying. Gerd Gigerenzer, a German psychologist at the Max Planck Institute
in Berlin, examined traffic fatalities on U.S. roads in the years before and after 2001. He found that in the calendar year following these terrorist attacks, there were more than 1500 additional deaths on American roads (when compared to the average of the previous years). Within a year of the attacks, the number of people using planes returned to approximately pre-9/11 levels; so did the
number of road fatalities (Gigerenzer, 2004). In other words, for almost a year, people overestimated the risks of flying because it was easier to think of examples of 9/11 than to think of all of the times hijackings and plane crashes
did not occur; and, they underestimated the risks associated with driving because these images were less available to many people. This example shows us that heuristics, although often useful, can cause us to incorrectly judge the
risks associated with many elements of our lives (Gardner, 2008).
Anchoring and Framing Effects
While the representativeness and availability heuristics involve our ability to remember examples that are similar to the current situation, other heuristics influence our responses based on the way that information is presented. Issues such as the wording of a problem and the problem’s frames of reference can
have a profound impact on judgments. One such effect, known as the anchoring effect , occurs when an individual attempts to solve a problem involving numbers and uses previous knowledge to keep (i.e., anchor) the response within a limited range. Sometimes this previous knowledge consists of facts that we can retrieve from memory. For example, imagine that you are asked to name the year that British Columbia became part of Canada. Although most of you would, of course, excitedly jump from your chair and shout, “1871!” the rest might assume that if Canada became a country in 1867, then B.C. likely joined a few years after that. In this latter case, the birth of our country in 1867 served as an anchor for the judgment about when B.C. joined Confederation.
The anchoring heuristic has also been produced experimentally. In these cases, questions worded in different ways can produce vastly different responses
(Epley & Gilovich, 2006; Kahneman & Miller, 1986). For example, consider what might happen if researchers asked the same question to two different groups, using a different anchor each time:
A. What percentage of countries in the United Nations are from Africa? Is it greater than or less than 10%? What do you think the exact percentage is?
B. What percentage of countries in the United Nations are from Africa? Is it greater than or less than 65%? What do you think the exact percentage is?
Researchers conducted a study using similar methods and found that individuals in group (A), who received the 10% anchor, estimated the number to be approximately 25%. Individuals in group (B), who received the 65% anchor, estimated the percentage at approximately 45%. In this case, the anchor obviously had a significant effect on the estimates.
The anchoring heuristic can have a large effect on your life. For example, have you ever had to bargain with someone while travelling? Or have you ever negotiated the price of a car? If you are able to establish a low anchor during bargaining, the final price is likely to be much lower than if you let the salesperson dictate the terms. So don’t be passive—use what you learn in this course to save yourself some money.
Decision making can also be influenced by how a problem is worded or framed. Consider the following dilemma: Imagine that you are a selfless doctor volunteering in a village in a disease-plagued part of Africa. You have two treatment options. Vaccine A has been used before; you know that it will save 200 of the 600 villagers. Vaccine B is untested; it has a 33% chance of saving all 600 people and a 67% chance of saving no one. Which option would you choose?
Now let’s suppose that you are given two different treatment options for the villagers. Treatment C has been used before and will definitely kill 67% of the villagers. Treatment D is untested; it has a 33% chance of killing none of the villagers and a 67% chance of killing them all. Which option would you choose?
Most people choose the vaccine that will definitely save 200 people (Vaccine A)
and the treatment that has a chance of killing no one (Treatment D). This tendency is interesting because options A and C are identical as are options B
and D. As you can see by looking at Figure 8.17 , the only difference between them is that one is framed in terms of saving people and the other is framed in terms of killing people. Yet, people become much more risk-averse when the question is framed in terms of potential losses (or deaths).
Figure 8.17 Framing Effects When people are asked which vaccine or treatment they would use to help a hypothetical group of villagers, the option they select is influenced by how the
question is worded or framed. If the question is worded in terms of saving villagers, most people choose Vaccine A. If the question is worded in terms of killing villagers, most people choose Treatment D. Source: Wade Carole; Tavris, Carol, Invitation to Psychology, 2nd Ed., ©2002, p. 121. Adapted and Electronically reproduced
by permissin of Pearson Eduation, Inc., Upper Saddle River, New Jersey.
Belief Perseverance and Confirmation Bias
Whenever we solve a problem or make a decision, we have an opportunity to evaluate the outcome to make sure we got it right and to judge how satisfied we are with the decision. However, feeling satisfied does not necessarily mean we are correct.
Let’s use an example to make this discussion more concrete. Each time there is a mass shooting in the U.S., thousands of gun owners will post messages on social media stating that Americans need to be able to easily purchase more guns in order to protect themselves. Many people (including many Americans), might think this idea is a bit illogical given that easy access to lethal weapons is what makes mass shootings so prevalent in that country. However, gun lovers often engage in (at least) two cognitive biases in order to maintain their beliefs.
One cognitive bias is belief perseverance , when an individual believes he or she has the solution to the problem or the correct answer for a question and will hold onto that belief even in the face of evidence against it. So, gun advocates will oppose any form of gun control even when presented with evidence from other countries (e.g., Australia) showing that preventing the public from owning assault rifles reduces or even eliminates mass shootings.
A second cognitive bias is the confirmation bias , when an individual searches for (or pays attention to) only evidence that will confirm his or her beliefs instead of evidence that might disconfirm them. To continue our example, gun advocates will often present statistics showing that particular U.S. states with strict gun laws still have high crime rates. These data are consistent with the claim that limiting gun access does not reduce crime. Of course, it ignores a
great deal of evidence suggesting that limiting gun access also makes it more difficult for ordinary citizens to commit gun-related violence. In other words, it is a selective representation of the data. The goal of these paragraphs isn’t to pick on gun enthusiasts or Americans! But, as mass shootings become more and more common, it is worth looking at some of the biases that are influencing the discussions around these issues.
Brain-imaging research provides an interesting perspective on belief perseverance and confirmation bias. This research shows that people treat evidence in ways that minimize negative or uncomfortable feelings while
maximizing positive feelings (Westen et al., 2006). For example, one American study examined the brain regions and self-reported feelings involved in interpreting information about presidential candidates during the 2004 campaign. The participants were all deeply committed to either the Republican (George “Dubya” Bush) or Democratic (John Kerry) candidate, and they all encountered information that was politically threatening toward each candidate (in this case, evidence that the candidate had contradicted himself). As you can see from the
results in Figure 8.18 , participants had strong emotional reactions to threatening (self-contradictory) information about their own candidate, but not to the alternative candidate, or a relatively neutral person, such as a retired network news anchor. Analyses of the brain scans demonstrated that participants from both political parties engaged in motivated reasoning. When the threat was directed at the participant’s own candidate, brain areas associated with ignoring or suppressing information were more active, whereas few of the regions
associated with logical thinking were activated (Westen et al., 2006).
Figure 8.18 Ratings of Perceived Contradictions in Political Statements Democrats and Republicans reached very different conclusions about candidates’ contradictory statements. Democrats readily identified the opponent’s contradictions but were less likely to do so for their own candidate; the same was true for Republican responders. Source: Westen, D., Blagov, P. S., & Harenski, K. (2006). Neural bases for motivated reasoning: An fMRI study of emotional
constraints on partisan political judgment in the 2004 U.S. presidential election. Journal of Cognitive Neuroscience, 18, 1974–
1958. Reprinted with permission of MIT Press.
These data demonstrate that a person’s beliefs can influence their observable behavioural responses to information as well as the brain activity underlying these behaviours. As we shall see, decision making—and our happiness with those decisions—can also be influenced by a person’s personality.
Working the Scientific Literacy Model Maximizing and Satisficing in Complex Decisions
One privilege of living in a technologically advanced, democratic society is that we get to make many decisions for ourselves. However, for each decision there can be more choices than we can possibly consider. As a result, two types of consumers have
emerged in our society. Satisficers are individuals who seek to make decisions that are, simply put, “good enough.” In contrast,
maximizers are individuals who attempt to evaluate every option for every choice until they find the perfect fit. Most people exhibit some of both behaviours, satisficing at times and maximizing at other times. However, if you consider all the people you know, you can probably identify at least one person who is an extreme maximizer—he or she will always be comparing products, jobs, classes, and so on, to find out who has made the best decisions. At the same time, you can probably identify an extreme satisficer —the person who will be satisfied with his or her choices as long as they are “good enough.”
What do we know about maximizing and satisficing? If one person settles for the good-enough option while another searches until he finds the best possible option, which individual do you think will be happier with the decision in the end? Most people believe the maximizer will be happier, but this is not always the case. In fact, researchers such as Barry Schwartz of Swarthmore College and his colleagues have no shortage of data
about the paradox of choice, the observation that more choices can lead to less satisfaction. In one study, the researchers asked participants to recollect both large (more than $100) and small (less than $10) purchases and report the number of options they considered, the time spent shopping and making the decision, and the overall satisfaction with the purchase. Sure enough, those who ranked high on a test of maximization invested more time and effort, but were actually less pleased with the outcome
(Schwartz et al., 2002).
In another study, researchers questioned recent university graduates about their job search process. Believe it or not, maximizers averaged 20% higher salaries, but were less happy
about their jobs than satisficers (Iyengar et al., 2006). This outcome occurred even though we would assume that
maximizers would be more careful when selecting a job—if humans were perfectly logical decision makers.
So, now we know that just the presence of alternative choices can drive down satisfaction—but how can that be?
How can science explain maximizing and satisficing? To answer this question, researchers asked participants to read vignettes that included a trade-off between number of choices
and effort (Dar-Nimrod et al., 2009). Try this example for yourself:
Your cleaning supplies (e.g., laundry detergent, rags, carpet cleaner,
dish soap, toilet paper, glass cleaner) are running low. You have the
option of going to the nearest grocery store (5 minutes away), which
offers 4 alternatives for each of the items you need, or you can drive to
the grand cleaning superstore (25 minutes away), which offers 25
different alternatives for each of the items (for approximately the same
price). Which store would you go to?
In the actual study, maximizers were much more likely to spend the extra time and effort to have more choices. Thus, if you decided to go to the store with more options, you are probably a maximizer. What this scenario does not tell us is whether having more or fewer choices was pleasurable for either maximizers or satisficers.
See how well you understand the nature of maximizers and satisficers by predicting the results of the next study: Participants
at the University of British Columbia completed a taste test of one piece of chocolate, but they could choose this piece of chocolate from an array of 6 pieces or an array of 30 pieces. When there were 6 pieces, who was happier—maximizers or satisficers? What happened when there were 30 pieces to choose from? As
you can see in Table 8.2 , the maximizers were happier when
there were fewer options. On a satisfaction scale indicating how much they enjoyed the piece of chocolate that they selected, the maximizers scored higher in the 6-piece condition (5.64 out of 7)
than in the 30-piece condition (4.73 out of 7; Dar-Nimrod et al., 2009). In contrast, satisficers did not show a statistical difference between the conditions (5.44 and 6.00 for the 6-piece and 30- piece conditions, respectively).
Table 8.2 Satisfaction of Maximizers and Satisficers
6 Alternatives 30 Alternatives Difference
Maximizers 5.64 4.73 −0.91
Satisficers 5.44 6.00 +0.46
Source: Adapted from Dar-Nimrod et al. (2009). The Maximization Paradox: The costs of
seeking alternatives. Personality and Individual Differences, 46, 631–635, Figure 1 and Table 1.
Can we critically evaluate this information? One hypothesis that seeks to explain the dissatisfaction of maximizers suggests that they invest more in the decision, so they expect more from the outcome. Imagine that a satisficer and a maximizer purchase the same digital camera for $175. The maximizer may have invested significantly more time and effort
into the decision so, in effect, she feels like she paid considerably more for the camera.
Regardless of the explanation, we should keep in mind that maximizers and satisficers are preexisting categories. People cannot be randomly assigned to be in one category or another, so these findings represent the outcomes of quasi-experimental
research (see Module 2.2 ). We cannot be sure that the act of maximizing leads to dissatisfaction based on these data. Perhaps maximizers are the people who are generally less satisfied, which in turn leads to maximizing behaviour.
Why is this relevant? Although we described maximizing and satisficing in terms of purchasing decisions, you might also notice that these styles of decision making can be applied to other situations, such as multiple-choice exams. Do you select the first response that sounds reasonable (satisficing), or do you carefully review each of the responses and compare them to one another before marking your choice (maximizing)? Once you make your choice, do you stick with it, believing it is good enough (satisficing), or are you willing to change your answer to make the best possible choice (maximizing)? Despite the popular wisdom that you should never change your first response, there may be an advantage to maximizing on exams. Research focusing on more than 1500 individual examinations showed that when people changed their answers, they changed them from incorrect to correct 51% of the time, from correct to incorrect 25% of the time, and from incorrect
to another incorrect option 23% of the time (Kruger et al., 2005).
The research discussed above suggests that there are some aspects of our consumer-based society that might actually be making us less happy. This seems counterintuitive given that the overwhelming number of product options
available to us almost guarantees that we will get exactly what we want (or think we want). It’s worth thinking about how the different biases discussed in this
module relate to your own life. By examining how your thinking is affected by different heuristics and biases, you will gain some interesting insights into why you behave the way you do. You will also be able to increase the amount of control you have over your own life.
Module 8.2b Quiz:
Judgment and Decision Making
Know . . . 1. When an individual makes judgments based on how easily things come
to mind, he or she is employing the heuristic. A. confirmation B. representativeness C. availability D. belief perseverance
Understand . . . 2. Belief perseverance seems to function by
A. maximizing positive feelings. B. minimizing negative feelings. C. maximizing negative feelings while minimizing positive feelings. D. minimizing negative feelings while maximizing positive feelings.
Analyze . . . 3. Why do psychologists assert that heuristics are beneficial for problem
solving?
A. Heuristics increase the amount of time we spend arriving at good solutions to problems.
B. Heuristics decrease our chances of errors dramatically. C. Heuristics help us make decisions efficiently. D. Heuristics are considered the most logical thought pattern for
problem solving.
4. The fact that humans so often rely on heuristics is evidence that A. humans are not always rational thinkers. B. it is impossible for humans to think logically. C. it is impossible for humans to use algorithms. D. humans will always succumb to the confirmation bias.
Module 8.2 Summary
algorithms
anchoring effect
availability heuristic
belief perseverance
confirmation bias
conjunction fallacy
functional fixedness
heuristics
mental set
problem solving
representativeness heuristic
All problems involve people attempting to reach some sort of goal; this goal can be an observable behaviour like learning to serve a tennis ball or a cognitive behaviour like learning Canada’s ten provincial capitals. This process involves forming strategies that will allow the person to reach the goal. It may also require a person to overcome one or more obstacles along the way.
Many obstacles arise from the individual’s mental set, which occurs when a person focuses on only one potential solution and does not consider alternatives.
Know . . . the key terminology of problem solving and decision making.
8.2a
Understand . . . the characteristics that problems have in common.8.2b
Understand . . . how obstacles to problem solving are often self- imposed.
8.2c
Similarly, functional fixedness can arise when an individual does not consider alternative uses for familiar objects.
Apply Activity Rate the following items on a scale from 1 (completely disagree) to 7 (completely agree), with 4 being a neutral response.
1. Whenever I’m faced with a choice, I try to imagine what all the other possibilities are, even ones that aren’t present at the moment.
2. No matter how satisfied I am with my job, it’s only right for me to be on the lookout for better opportunities.
3. When I am in the car listening to the radio, I often check other stations to see whether something better is playing, even if I am relatively satisfied with what I’m listening to.
4. When I watch TV, I channel surf, often scanning through the available options even while attempting to watch one program.
5. I treat relationships like clothing: I expect to try a lot on before finding the perfect fit.
6. I often find it difficult to shop for a gift for a friend. 7. When shopping, I have a difficult time finding clothing that I really love. 8. No matter what I do, I have the highest standards for myself. 9. I find that writing is very difficult, even if it’s just writing to a friend,
because it’s so difficult to word things just right. I often do several drafts of even simple things.
10. I never settle for second best.
When you are finished, average your ratings together to find your overall score. Scores greater than 4 indicate maximizers; scores less than 4 indicate satisficers. Approximately one-third of the population scores below 3.25 and approximately one-third scores above 4.75. Where does your score place you?
Apply . . . your knowledge to determine if you tend to be a maximizer or a satisficer.
8.2d
Analyze . . . whether human thought is primarily logical or intuitive.8.2e
This module provides ample evidence that humans are not always logical. Heuristics are helpful decision-making and problem-solving tools, but they do not always follow logical principles. Even so, the abundance of heuristics does not mean that humans are never logical; instead, they simply point to the limits of our rationality.
Module 8.3 Language and Communication
Manuela Hartling/Reuters
Learning Objectives
Know . . . the key terminology from the study of language. Understand . . . how language is structured. Understand . . . how genes and the brain are involved in language use. Apply . . . your knowledge to distinguish between units of language such as phonemes and morphemes. Analyze . . . whether species other than humans are able to use language.
8.3a 8.3b 8.3c 8.3d
8.3e
Dog owners are known for attributing a lot of intelligence, emotion, and “humanness” to their canine pals. Sometimes they may appear to go overboard—such as Rico’s owners, who claimed their border collie understood 200 words, most of which referred to different toys and objects he liked to play with. His owners claimed that they could show Rico a toy, repeat its name a few times, and toss the toy into a pile of other objects; Rico would then retrieve the object upon verbal command. Rico’s ability appeared to go well beyond the usual “sit,” “stay,” “heel,” and perhaps a few other words that dog owners expect their companions to understand.
Claims about Rico’s language talents soon drew the attention of scientists, who skeptically questioned whether the dog was just responding to cues by the owners, such as their possible looks or gestures toward the object they asked their pet to retrieve. The scientists set up a carefully controlled experiment in which no one present in the room knew the location of the object that was requested. Rico correctly retrieved 37 out of 40 objects. The experimenters then tested the owners’ claim that Rico could learn object names in just one trial. Rico again confirmed his owners’ claims, and the researchers concluded that his ability to understand new words was comparable to that of a three-year-
old child (Kaminski et al., 2004).
However, as you will see in this module, Rico’s abilities, while impressive, are dwarfed by those of humans. Our ability to reorganize words into complex thoughts is unique in the animal kingdom and may even have aided our survival as a species.
Focus Questions
1. What is the difference between language and other forms of communication?
2. Might other species, such as chimpanzees, also be capable of learning human language?
Communication happens just about anywhere you can find life. Dogs bark, cats meow, monkeys chatter, and mice can emit sounds undetectable to the human ear when communicating. Honeybees perform an elaborate dance to
communicate the direction, distance, and quality of food sources (von Frisch, 1967). Animals even communicate by marking their territories with their distinct scent, much to the chagrin of the world’s fire hydrants. Language is among the ways that humans communicate. It is quite unlike the examples of animal communication mentioned previously. So what differentiates language from these other forms of communication? And, what is it about our brains that enables us to turn different sounds and lines into the sophisticated languages found across different human cultures?
What Is Language?
Language is one of the most intensively studied areas in all of psychology. Thousands of experiments have been performed to identify different characteristics of language as well as the brain regions associated with them. But, all fields of study have a birthplace. In the case of the scientific study of language, it began with an interesting case study of a patient in Paris in the early 1860s.
Early Studies of Language
In 1861, Paul Broca, a physician and founder of the Society of Anthropology of Paris, heard of an interesting medical case. The patient appeared to show a very specific impairment resulting from a stroke suffered 21 years earlier. He could understand speech and had fairly normal mental abilities; however, he had great
difficulty producing speech and often found himself uttering single words separated by pauses (uh, er . . .). In fact, this patient acquired the nickname “Tan” because it was one of the only sounds that he could reliably produce. Tan
had what is known as aphasia , a language disorder caused by damage to the
brain structures that support using and understanding language.
Tan died a few days after being examined by Broca. During the autopsy, Broca noted that the brain damage appeared primarily near the back of the frontal lobes in the left hemisphere. Over the next couple of years, Broca found 12 other patients with similar symptoms and similar brain damage, indicating that Tan was
not a unique case. This region of the left frontal lobe that controls our ability to articulate speech sounds that compose words is now known as Broca’s area
(see Figure 8.19 ). The symptoms associated with damage to this region, as seen in Tan, are known as Broca’s aphasia.
Figure 8.19 Two Language Centres of the Brain Broca’s and Wernicke’s areas of the cerebral cortex are critical to language function.
The fact that a brain injury could affect one part of language while leaving others preserved suggested that the ability to use language involves a number of different processes using different areas of the brain. In the years following the publication of Broca’s research, other isolated language impairments were discovered. In 1874, a young Prussian (German) physician named Carl
Wernicke published a short book detailing his study of different types of aphasia. Wernicke noted that some of his patients had trouble with language
comprehension rather than language production. These patients typically had damage to the posterior superior temporal gyrus (the back and top part of the
temporal lobe). This region, now known as Wernicke’s area , is the area of the brain most associated with finding the meaning of words (see Figure 8.19 ). Damage to this area results in Wernicke’s aphasia, a language disorder in which a person has difficulty understanding the words he or she hears. These patients are also unable to produce speech that other people can understand— the words are spoken fluently and with a normal intonation and accent, but these words seem randomly thrown together (i.e., what is being said does not make sense). Consider the following example:
Examiner: I’d like to have you tell me something about your problem.
Person with Wernicke’s aphasia: Yes, I, ugh, cannot hill all of my way. I cannot talk all of the things I do, and part of the part I can go alright, but I cannot tell from the other people. I usually most of my things. I know what can I talk and know what they are, but I cannot always come back even though I know they should be in, and I know should something eely I should know what I’m doing . . .
The important thing to look for in this sample of speech is how the wrong words appear in an otherwise fluent stream of utterances. Contrast this with an example of Broca’s aphasia:
Examiner: Tell me, what did you do before you retired?
Person with Broca’s aphasia: Uh, uh, uh, pub, par, partender, no.
Examiner: Carpenter?
Person with Broca’s aphasia: (Nodding to signal yes) Carpenter, tuh, tuh, twenty year.
Notice that the individual has no trouble understanding the question or coming
up with the answer. His difficulty is in producing the word carpenter and then putting it into an appropriate phrase. Did you also notice the missing “s” from
twenty year? This is another characteristic of Broca’s aphasia: The individual words are often produced without normal grammatical flair: no articles, suffixes, or prefixes.
Broca’s aphasia can include some difficulties in comprehending language as well. In general, the more complex the sentence structure, the more difficult it will be to understand. Compare these two sentences:
The girl played the piano.
The piano was played by the girl.
These are two grammatically correct sentences (although the second is somewhat awkward) that have the same meaning but are structured differently. Patients with damage to Broca’s area would find it much more difficult to understand the second sentence than the first. This impairment suggests that the distinction between speech production and comprehension is not as simple as was first thought. Indeed, as language became a central topic of research in psychology, researchers quickly realized that this ability—or set of abilities—is among the most complex processes humans perform.
Properties of Language
Language, like many other cognitive abilities, flows so automatically that we often overlook how complicated it really is. However, cases like those described above show us that language is indeed a complex set of skills. Researchers
define language as a form of communication that involves the use of spoken, written, or gestural symbols that are combined in a rule-based form. With this definition in mind, we can distinguish which features of language make it a unique form of communication.
Language can involve communication about objects and events that are not in the present time and place. We can use language to talk about events happening on another planet or that are happening within atoms. We can also use different tenses to indicate that the topic of the sentence occurred or
will occur at a different time. For instance, you can say to your roommate, “I’m going to order pizza tonight,” without her thinking the pizza is already there.
Languages can produce entirely new meanings. It is possible to produce a sentence that has never been uttered before in the history of humankind, simply by reorganizing words in different ways. As long as you select English words and use correct grammar, others who know the language should be able to understand it. You can also use words in novel ways. Imagine the
tabloid newspaper headline: Bat Boy Found in Cave! In North American culture, “bat boys” are regular kids who keep track of the baseball bats for baseball players. In this particular tabloid, the story concerned a completely novel creature that was part bat and part boy. Both meanings could be
correct, depending upon the context in which the term bat boy is used. Language is passed down from parents to children. As we will discuss later in this module, children learn to pay attention to the particular sounds of their
native language(s) at the expense of other sounds (Werker, 2003). Children also learn words and grammatical rules from parents, teachers, and peers. In
other words, even if we have a natural inclination to learn a language, experience dictates which language(s) we will speak.
Language requires us to link different sounds (or gestures) with different meanings in order to understand and communicate with other people. Therefore, understanding more about these seemingly simple elements of language is essential for understanding language as a whole.
Words can be arranged or combined in novel ways to produce ideas that have never been expressed before. Weekly World News
Phonemes and Morphemes: The Basic Ingredients
of Language
Languages contain discrete units that exist at differing levels of complexity. When people speak, they assemble these units into larger and more complex units. Some psychologists have used a cooking analogy to explain this phenomenon: We all start with the same basic language ingredients, but they
can be mixed together in an unlimited number of ways (Pinker, 1999).
Phonemes are the most basic of units of speech sounds. You can identify phonemes rather easily; the phoneme associated with the letter t (which is written as /t/, where the two forward slashes indicate a phoneme) is found at the
end of the word pot or near the beginning of the word stop. If you pay close attention to the way you use your tongue, lips, and vocal cords, you will see that phonemes have slight variations depending on the other letters around them.
Pay attention to how you pronounce the /t/ phoneme in stop, stash, stink, and stoke. Your mouth will move in slightly different ways each time, and there will be very slight variations in sound, but they are still the same basic phoneme. Individual phonemes typically do not have any meaning by themselves; if you want someone to stop doing something, asking him to /t/ will not suffice.
Morphemes are the smallest meaningful units of a language. Some morphemes are simple words, whereas others may be suffixes or prefixes. For
example, the word pig is a morpheme—it cannot be broken down into smaller units of meaning. You can combine morphemes, however, if you follow the rules
of the language. If you want to pluralize pig, you can add the morpheme /-s/, which will give you pigs. If you want to describe a person as a pig, you can add the morpheme /-ish/ to get piggish. In fact, you can add all kinds of morphemes to a word as long as you follow the rules. You could even say piggable (able to be pigged) or piggify (to turn into a pig). These words do not make much literal sense, but they combine morphemes according to the rules; thus we can make a reasonable guess as to the speaker’s intended meaning. Our ability to combine morphemes into words is one distinguishing feature of language that sets it apart from other forms of communication (e.g., we don’t produce a lengthy series of facial expressions to communicate a new idea). In essence, language gives us
productivity—the ability to combine units of sound into an infinite number of meanings.
Finally, there are the words that make up a language. Semantics is the study of how people come to understand meaning from words. Humans have a knack for this kind of interpretation, and each of us has an extensive mental dictionary to prove it. Not only do normal speakers know tens of thousands of words, but they can often understand new words they have never heard before based on
their understanding of morphemes.
Although phonemes, morphemes, and semantics have an obvious role in spoken language, they also play a role in our ability to read. When you recognize a word,
you effortlessly translate the word’s visual form (known as its orthography) into the sounds that make up that word (known as its phonology or phonological code). These sounds are combined into a word, at which point you can access its meaning or semantics. However, not all people are able to translate
orthography into sounds. Individuals with dyslexia have difficulties translating words into speech sounds. Indeed, children with dyslexia show less activity in the left fusiform cortex (at the bottom of the brain where the temporal and occipital lobes meet), a brain area involved with word recognition and with linking
word and sound representations (Desroches et al., 2010). This difficulty linking letters with phonemes leads to unusually slow reading in both children and adults despite the fact that these people have normal hearing and are cognitively and
neurologically healthy (Desroches & Joanisse, 2009; Shaywitz, 1998).
This research into the specific impairments associated with dyslexia allows scientists and educators to develop treatment programs to help children improve their reading and language abilities. One of the most successful programs has been developed by Maureen Lovett and her colleagues at Sick Kids Hospital in Toronto and Brock University. Their Phonological and Strategy Training (PHAST)
program (now marketed as Empower Reading to earn research money for the hospital) has been used to assist over 6000 students with reading disabilities. Rather than focusing on only one aspect of language, this program teaches children new word-identification and reading-comprehension strategies while also educating them about how words and phrases are structured (so that they know what to expect when they see new words or groups of words). Children who completed these programs showed improvements on a number of
measures of reading and passage comprehension (Frijters et al., 2013; Lovett et al., 2012). Given that 5–15% of the population has some form of reading impairment, treatment programs like PHAST could have a dramatic effect on our educational system.
As you can see, languages derive their complexity from several elements,
TM
including phonemes, morphemes, and semantics. And, when these systems are not functioning properly, language abilities suffer. But phonemes, morphemes, and semantics are just the list of the ingredients of language—we still need to figure out how to mix these ingredients together.
Syntax: The Language Recipe
Perhaps the most remarkable aspect of language is syntax , the rules for combining words and morphemes into meaningful phrases and sentences—the recipe for language. Children master the syntax of their native language before they leave elementary school. They can string together morphemes and words
when they speak, and they can easily distinguish between well-formed and ill- formed sentences. But despite mastering those rules, most speakers cannot tell you what the rules are; syntax just seems to come naturally. It might seem odd that people can do so much with language without a full understanding of its inner workings. Of course, people can also learn how to walk without any understanding of the biochemistry that allows their leg muscles to contract and relax.
The most basic units of syntax are nouns and verbs. They are all that is required
to construct a well-formed sentence, such as Goats eat. Noun–verb sentences are perfectly adequate, if a bit limited, so we build phrases out of nouns and
verbs, as the diagram in Figure 8.20 demonstrates.
Figure 8.20 Syntax Allows Us to Understand Language by the Organization of the Words The rules of syntax help us divide a sentence into noun phrases, verb phrases, and other parts of speech. Source: Adapted from S. Pinker. (1994). The Language Instinct. New York: HarperCollins.
Syntax also helps explain why the order of words in a sentence has such a strong effect on what the sentence means. For example, how would you make a question out of this statement?
A. A goat is in the garden. B. IS a goat in the garden?
This example demonstrates that a statement (A) can be turned into a well-
formed question (B) just by moving the verb is to the beginning of the sentence. Perhaps that is one of the hidden rules of syntax. Try it again:
A. A goat that is eating a flower is in the garden. B. IS a goat that eating a flower is in the garden?
As you can see, the rule “move is to the beginning of the sentence” does not apply in this case. Do you know why? It is because we moved the wrong is. The phrase that is eating a flower is a part of the noun phrase because it describes the goat. We should have moved the is from the verb phrase. Try it again:
A. A goat that is eating a flower is in the garden. B. IS a goat that is eating a flower in the garden?
This is a well-formed sentence. It may be grammatically awkward, but the syntax
is understandable (Pinker, 1994).
As you can see from these examples, the order of words in a sentence helps determine what the sentence means, and syntax is the set of rules we use to determine that order.
Pragmatics: The Finishing Touches
If syntax is the recipe for language, pragmatics is the icing on the cake. Pragmatics is the study of nonlinguistic elements of language use. It places heavy emphasis on the speaker’s behaviours and the social situation (Carston, 2002).
Pragmatics reminds us that sometimes what is said is not as important as how it is said. For example, a student who says, “I ate a 50-pound cheeseburger,” is most likely stretching the truth, but you probably would not call him a liar. Pragmatics helps us understand what he implied. The voracious student was
actually flouting—or blatantly disobeying—a rule of language in a way that is obvious (Grice, 1975; Horn & Ward, 2004). There are all sorts of ways in which flouting the rules can lead to implied, rather than literal, meanings; a sample of
these are shown in Table 8.3 .
Table 8.3 Pragmatic Rules Guiding Language Use
The Rule Flouting the Rule The Implication
Say what
you believe
is true.
My roommate is a
giraffe.
He does not really live with a giraffe. Maybe
his roommate is very tall?
Say only
what is
relevant.
Is my blind date
good-looking? He’s
got a great
personality.
She didn’t answer my question. He’s probably
not good-looking.
Say only
as much as
you need
to.
I like my lab partner,
but he’s no Einstein.
Of course he’s not Einstein. Why is she
bothering to tell me this? She probably means
that her partner is not very smart.
Importantly, pragmatics depends upon both the speaker (or writer) and listener (or reader) understanding that rules are being flouted in order to produce a desired meaning. If you speak with visitors from a different country, you may find that they don’t understand what you mean when you flout the rules of Canadian English or use slang (shortened language). When we say “The goalie stood on his head,” most hockey-mad Canadians understand that we are commenting on a goaltender’s amazing game; however, someone new to hockey would be baffled by this expression. This is another example of how experience—in this case with a culture—influences how we use and interpret language.
Module 8.3a Quiz:
What Is Language?
Know . . . 1. What are the rules that govern how words are strung together into
meaningful sentences?
A. Semantics B. Pragmatics C. Morphemics D. Syntax
2. The study of how people extract meaning from words is called . A. syntax B. pragmatics C. semantics D. flouting
Understand . . . 3. Besides being based in a different region of the brain, a major distinction
between Broca’s aphasia and Wernicke’s aphasia is that
A. words from people with Broca’s aphasia are strung together fluently, but often make little sense.
B. Broca’s aphasia is due to a FOXP2 mutation. C. Wernicke’s aphasia results in extreme stuttering. D. words from people with Wernicke’s aphasia are strung together
fluently, but often make little sense.
Apply . . . 4. is an example of a morpheme, while is a phoneme.
A. /dis/; /ta/ B. /a/; /like/ C. /da/; /ah/ D. /non/; /able/
The Development of Language
Human vocal tracts are capable of producing approximately 200 different phonemes. However, no language uses all of these sounds. Jul’hoan, one of the “clicking languages” of Botswana, contains almost 100 sounds (including over 80 different consonant sounds). In contrast, English contains about 40 sounds. But, if Canadians are genetically identical to people in southern Africa, why are our languages different? And, why can’t we produce and distinguish between some of the sounds of these other languages? It turns out that experience plays a major role in your ability to speak the language, or languages, that you do.
Infants, Sound Perception, and Language
Acquisition
Say the following phrase out loud: “Your doll.” Now, say this phrase: “This doll.”
Did you notice a difference in how you pronounced doll in these two situations? If English is your first language, it is quite likely that you didn’t notice the slight change in how the letter “d” was expressed. But, Hindi speakers would have no
problem making this distinction. To them, the two instances of the word doll would be pronounced differently and would mean lentils and branch, respectively.
Janet Werker of the University of British Columbia and her colleagues found that very young English-learning infants are able to distinguish between these two “d” sounds. But, by 10 months of age, the infants begin hearing sounds in a way that is consistent with their native language; because English has only one “d” sound, English-learning infants stop detecting the difference between these two sounds
(Werker & Tees, 1984; Werker et al., 2012). This change is not a weakness on the part of English-learning infants. Rather, it is evidence that they are learning the statistical principles of their language. Infants who hear only English words will group different pronunciations of the letter “d” into one category because that is how this sound is used in English. Hindi-learning children will learn to separate different types of “d” sounds because this distinction is important. A related study using two “k” sounds from an Interior Salish (First Nations) language from British Columbia produced similar results—English-learning infants showed a significant drop-off in hearing sounds for the non-English language after 8–10 months
(Werker & Tees, 1984).
In addition to becoming experts at identifying the sounds of their own language, infants also learn how to separate a string of sounds into meaningful groups (i.e., into words). Infants as young as two months old show a preference for speech
sounds over perceptually similar non-speech sounds (Vouloumanos & Werker, 2004). And, when presented with pronounceable non-words (e.g., strak), infants prefer to hear words that follow the rules of their language. An English-learning baby would prefer non-words beginning in “str” to those beginning in “rst” because there are a large number of English words that begin with “str”
(Jusczyk et al., 1993). Additionally, newborn infants can distinguish between function words (e.g., prepositions) and content words (e.g., nouns and verbs)
based on their sound properties (Shi et al., 1999). By six months of age, infants prefer the content words (Shi & Werker, 2001), thus showing that they are learning which sounds are most useful for understanding the meaning of a statement.
By the age of 20 months, the children are able to use the perceptual categories that they developed in order to rapidly learn new words. In some cases, children
can perform fast mapping —the ability to map words onto concepts or objects
after only a single exposure. Human children seem to have a fast-mapping capacity that is superior to any other organism on the planet. This skill is one
potential explanation for the naming explosion, a rapid increase in vocabulary size that occurs at this stage of development.
The naming explosion has two biological explanations as well. First, at this stage of development, the brain begins to perform language-related functions in the left hemisphere, similar to the highly efficient adult brain; prior to this stage, this
information was stored and analyzed by both hemispheres (Mills et al., 1997). Second, the naming explosion has also been linked to an increase in the amount of myelin on the brain’s axons, a change that would increase the speed of
communication between neurons (Pujol et al., 2006). These changes would influence not only the understanding of language, but also how a child uses language to convey increasingly complex thoughts such as “How does Spiderman stick to walls?” and “Why did Dad’s hair fall out?”
Producing Spoken Language
Learning to identify and organize speech sounds is obviously an important part of language development. An equally critical skill is producing speech that other people will be able to understand. Early psychologists focused only on behavioural approaches to language learning. They believed that language was learned through imitating sounds and being reinforced for pronouncing and using
words correctly (Skinner, 1985). Although it is certainly true that imitation and reinforcement are involved in language acquisition, they are only one part of this
complex process (Messer, 2000). Here are a few examples that illustrate how learning through imitation and reinforcement is just one component of language development:
Children often produce phrases that include incorrect grammar or word forms. Because adults do not (often) use these phrases, it is highly unlikely that such phrases are imitations.
Children learn irregular verbs and pluralizations on a word-by-word basis. At first, they will use ran and geese correctly. However, when children begin to use grammar on their own, they over-generalize the rules. A child who learns
the /-ed/ morpheme for past tense will start saying runned instead of ran. When she learns that /-s/ means more than one, she will begin to say gooses instead of geese. It is also unlikely that children would produce these forms by imitating.
When children use poor grammar, or when they over-generalize their rules, parents may try to correct them. Although children will acknowledge their parents’ attempts at instruction, this method does not seem to work. Instead, children go right back to over-generalizing.
In light of these and many other examples, it seems clear that an exclusively behaviourist approach falls short in explaining how language is learned. After all, there are profound differences in the success of children and adults in learning a new language: Whereas adults typically struggle, children seem to learn the language effortlessly. If reinforcement and imitation were the primary means by which language was acquired, then adults should be able to learn just as well as children.
The fact that children seem to learn language differently than adults has led
psychologists to use the term language acquisition when referring to children instead of language learning. The study of language acquisition has revealed remarkable similarities among children from all over the world. Regardless of the
language, children seem to develop this capability in stages, as shown in Table 8.4 .
Table 8.4 Milestones in Language Acquisition and Speech
Average Time of Onset
(Months)
Milestone Example
1–2 Cooing Ahhh, ai-ai-ai
4–10 Babbling (consonants start) Ab-ah-da-ba
8–16 Single-word stage Up, mama, papa
24 Two-word stage Go potty
24+ Complete, meaningful phrases
strung together
I want to talk to
Grandpa.
Sensitive Periods for Language
The phases of language development described above suggest that younger brains are particularly well-suited to acquiring languages; this is not the case for older brains. Imagine a family with two young children who immigrated to Canada from a remote Russian village where no one spoke English. The parents would struggle with English courses, while the children would attend English- speaking schools. Within a few years, the parents would have accumulated some vocabulary but they would likely still have difficulty with pronunciation and
grammar (Russian-speaking people often omit articles such as the). Meanwhile, their children would likely pick up English without much effort and have language skills equivalent to those of their classmates; they would have roughly the same vocabulary, the same accents, and even the same slang.
Why can children pick up a language so much more easily than adults? Most
psychologists agree that there is a sensitive period for language—a time during childhood in which children’s brains are primed to develop language skills (see
also Module 10.1 ). Children can absorb language almost effortlessly, but this ability seems to fade away starting around age seven. Thus, when families immigrate to a country that uses a different language, young children are able to
pick up this language much more quickly than their parents (Hakuta et al., 2003; Hernandez & Li, 2007).
A stunning example of critical periods comes from Nicaragua. Until 1979, there was no sign language in this Central American country. Because there were no schools for people with hearing impairments, there was no (perceived) need for a common sign language. When the first schools for the deaf were established, adults and teenaged students attempted to learn to read lips. While few mastered this skill, these students did do something even more astonishing:
They developed their own primitive sign language. This language, Lenguaje de Signos Nicaragüese (LSN), involves a number of elaborate gestures similar to a game of charades and did not have a consistent set of grammatical rules. But, it was a start. Children who attended these schools at an early age (i.e., during the sensitive period for language acquisition) used this language as the basis for a
more fluent version of sign language: Idioma de Signos Nicaragüese (ISN). ISN has grammatical rules and can be used to express a number of complicated,
abstract ideas (Pinker, 1994). It is now the standard sign language in Nicaragua. The difference between LSN and ISN is similar to the difference between adults and children learning a new language. If you acquire the new language during childhood, you will be much more fluent than if you try to acquire it during
adulthood (Senghas, 2003; Senghas et al., 2004).
The Bilingual Brain
Let’s go back to the example of the Russian-speaking family who immigrated to balmy Canada. The young children learning English would also be speaking Russian at home with their parents. As a result, they would be learning two languages essentially at the same time. What effect would this situation have on their ability to learn each language?
Although bilingualism leads to many benefits (see below), there are some costs to learning more than one language. Bilingual children tend to have a smaller
vocabulary in each language than unilingual children (Mahon & Crutchley, 2006). In adulthood, this difference is shown not by vocabulary size, but by how easily bilinguals can access words. Compared to unilingual adults, bilingual
adults are slower at naming pictures (Roberts et al., 2002), have more difficulty on tests that ask them to list words starting with a particular letter (Rosselli et al., 2000), have more tip-of-the-tongue experiences in which they can’t quite retrieve a word (Gollan & Acenas, 2004), and are slower and less accurate when making word/non-word judgments (Ransdell & Fischler, 1987). These problems with accessing words may be due to the fact that they use each
language less than a unilingual person would use their single language (Michael & Gollan, 2005).
The benefits of bilingualism, however, appear to far outweigh the costs. One difference that has been repeatedly observed is that bilingual individuals are much better than their unilingual counterparts on tests that require them to
control their attention or their thoughts. These abilities, known as executive functions (or executive control), enable people who speak more than one language to inhibit one language while speaking and listening to another (or to limit the interference across languages). If they didn’t, they would produce
confusing sentences like The chien is tres sick. Although most of you can figure out that this person is talking about a sick dog, you can see how such sentences would make communication challenging. Researchers have found that bilinguals score better than unilinguals on tests of executive control throughout the
lifespan, beginning in infancy (Kovacs & Mehler, 2009) and the toddler years (Poulin-Dubois et al., 2011) and continuing throughout adulthood (Costa et al., 2008) and into old age (Bialystok et al., 2004). Bilingualism has also recently been shown to have important health benefits. Because the executive control involved with bilingualism uses areas in the frontal lobes, these regions may form
more connections in bilinguals than unilinguals (Bialystok, 2009, 2011a, 2011b). As a result, these brains likely have more back-up systems if damage occurs. Indeed, Ellen Bialystok at York University and her colleagues have shown that being bilingual helps protect against the onset of dementia and Alzheimer’s
disease (Bialystok et al., 2007; Schweizer et al., 2012), a finding that leaves many at a loss for words.
Module 8.3b Quiz:
The Development of Language
Know . . . 1. What is fast mapping?
A. The rapid rate at which chimpanzees learn sign language B. The ability of children to map concepts to words with only a single
example
C. The very short period of time that language input can be useful for language development
D. A major difficulty that people face when affected by Broca’s
aphasia
Understand . . . 2. The term “sensitive period” is relevant to language acquisition because
A. exposure to language is needed during this time for language abilities to develop normally.
B. Broca’s area is active only during this period. C. it is what distinguishes humans from the apes. D. it indicates that language is an instinct.
Analyze . . . 3. What is the most accurate conclusion from studies of bilingualism and the
brain?
A. Being bilingual causes the brain to form a larger number of connections than it normally would.
B. Being bilingual reduces the firing rate of the frontal lobes. C. Only knowing one language allows people to improve their
executive functioning.
D. Being bilingual makes it more likely that a person will have language problems if they suffer brain damage.
Genes, Evolution, and Language
This module began with a discussion of two brain areas that are critical for language production and comprehension: Broca’s area and Wernicke’s area, respectively. But, these brain areas didn’t appear out of nowhere. Rather, genetics and evolutionary pressures led to the development of our language- friendly brains. Given recent advances in our understanding of the human
genome (see Module 3.1 ), it should come as no surprise that researchers are actively searching for the genes involved with language abilities.
Working the Scientific Literacy Model Genes and Language
Given that language is a universal trait of the human species, it likely involves a number of different genes. These genes would, of course, also interact with the environment. In this section we examine whether it is possible that specific genes are related to language.
What do we know about genes and language? Many scientists believe that the evidence is overwhelming that language is a unique feature of the human species, and that language evolved to solve problems related to survival and reproductive fitness. Language adds greater efficiency to thought, allows us to transmit information without requiring us to have direct experience with potentially dangerous situations, and, ultimately, facilitates communicating social needs and desires. Claims that language promotes survival and reproductive success are difficult to test directly with scientific experimentation, but there is a soundness to the logic of the speculation. We can also move beyond speculation and actually examine how genes play a role in human language. As with all complex psychological traits, there are likely many genes associated with language. Nevertheless, amid all of these myriad possibilities, one gene has been identified that is of particular importance.
How can science explain a genetic basis of language? Studies of this gene have primarily focused on the KE family (their name is abbreviated to maintain their confidentiality). Many members of this family have inherited a mutated version of a
gene on chromosome 7 (see Figure 8.21 ; Vargha-Khadem et al., 2005). Each gene has a name—and this one is called FOXP2. All humans carry a copy of the FOXP2 gene, but the KE
family passes down a mutated copy. Those who inherit the mutated copy have great difficulty putting thoughts into words
(Tomblin et al., 2009). Thus, it appears that the physical and chemical processes that FOXP2 codes for are related to language function.
Figure 8.21 Inheritance Pattern for the Mutated FOXP2 Gene in the KE Family
Family members who are “affected” have inherited a mutated form of the FOXP2 gene, which results in difficulty with articulating words. As you can see from the centre of the figure, the mutated gene is traced to a female family member and has been passed on to the individuals of the next two generations. Source: Republished with permission of Nature Publishing Group, from FOXP2 and the
neuroanatomy of speech and language, Fig. 1, Nature Reviews Neuroscience, 6, 131–138 by
Faraneh Vargha-Khadem; David G. Gadian; Andrew Copp; Mortimer Mishkin. Copyright 2005;
permission conveyed through Copyright Clearance Center, Inc.
What evidence indicates that this gene is specifically involved in language? If you were to ask the members of the family who inherited the mutant form of the gene to speak about how to change the batteries in a flashlight, they would be at a loss. A rather jumbled mixture of sounds and words might come out, but nothing that could be easily understood. However, these same individuals have no problem actually performing the task. Their challenges with using language are primarily restricted to the use
of words, not with their ability to think.
Scientists have used brain-imaging methods to further test whether the FOXP2 mutation affects language. One group of researchers compared brain activity of family members who inherited the mutation of FOXP2 with those who did not
(Liégeois et al., 2003). During the brain scans, the participants were asked to generate words themselves, and also to repeat
words back to the experimenters. As you can see from Figure 8.22 , the members of the family who were unaffected by the mutation showed normal brain activity: Broca’s area of the left hemisphere became activated, just as expected. In contrast, Broca’s area in the affected family members was silent, and the brain activity that did occur was unusual for this type of task.
Figure 8.22 Brain Scans Taken While Members of the KE Family Completed a Speech Task
The unaffected group shows a normal pattern of activity in Broca’s area, while the affected group shows an unusual pattern. Source: Republished with permission of Nature Publishing Group, from Source: Language fMRI
abnormalities associated with FOXP2 gene mutation, Figure 1, Nature Neuroscience, 6, 1230–1237,
Copyright © 2003. permission conveyed through Copyright Clearance Center, Inc.
Can we critically evaluate this evidence? As you have now read, language has multiple components. Being able to articulate words is just one of many aspects of using and understanding language. The research on FOXP2 is very important, but reveals only how a single gene relates to one aspect of language use. There are almost certainly a large
number of different genes working together to produce each component of language. To their credit, FOXP2 researchers are quick to point out that many other genes will need to be identified before we can claim to understand the genetic basis of language; FOXP2 is just the beginning.
It is also worth noting that although the FOXP2 gene affects human speech production, it does occur in other species that do not produce sophisticated language. This gene is found in both mice and birds as well as in humans, and the human version shares a very similar molecular structure to the versions observed in these other species. Interestingly, the molecular structure and activity of the FOXP2 gene in songbirds (unlike non-songbirds) is similar to that in humans, again highlighting its
possible role in producing meaningful sounds (Vargha-Khadem et al., 2005).
Why is this relevant? This work illuminates at least part of the complex relationship between genes and language. Other individual genes that have direct links to language function will likely be discovered as research continues. It is possible that this information could be used to help us further understand the genetic basis of language disorders. The fact that the FOXP2 gene is found in many other species suggests that it may play a role in one of the components
of language rather than being the gene for language. Thus, scientists will have to perform additional research in order to understand why and how human language became so much more complex than that of any other species.
The fact that animals such as songbirds have some of the same language-
related genes as humans suggests that other species may have some language abilities. As it turns out, many monkey species have areas in their brains that are similar to Broca’s and Wernicke’s area. As in humans, these regions are connected by white-matter pathways, thus allowing them to communicate with
each other (Galaburda & Pandya, 1982). These areas appear to be involved with the control of facial and throat muscles and with identifying when other monkeys have made a vocalization. This is, of course, a far cry from human language. But, the fact that some monkey species have similar “neural hardware” to humans does lead to some interesting speculations about language abilities in the animal kingdom.
Can Animals Use Language?
Psychologists have been studying whether nonhuman species can acquire human language for many decades. Formal studies of language learning in nonhuman species gained momentum in the mid-1950s when psychologists
attempted to teach spoken English to a chimpanzee named Viki (Hayes & Hayes, 1951). Viki was cross-fostered , meaning that she was raised as a member of a family that was not of the same species. Like humans, chimps come into the world dependent on adults for care, so the humans who raised Viki were basically foster parents. Although the psychologists learned a lot about how smart chimpanzees can be, they did not learn that Viki was capable of language —she managed to whisper only about four words after several years of trying.
Psychologists who followed in these researchers’ footsteps did not consider the case to be closed. Perhaps Viki’s failure to learn spoken English was a limitation not of the brain, but of physical differences in the vocal tract and tongue that
distinguish humans and chimpanzees. One project that began in the mid-1960s involved teaching chimpanzees to use American Sign Language (ASL). The first chimpanzee involved in this project was named Washoe. The psychologists immersed Washoe in an environment rich with ASL, using signs instead of speaking and keeping at least one adult present and communicating with her throughout the day. By the time she turned two years old, Washoe had acquired about 35 signs through imitation and direct guidance of how to configure and move her hands. Eventually, she learned approximately 200 signs. She was able to generalize signs from one context to another and to use a sign to represent entire categories of objects, not just specific examples. For example, while Washoe learned the sign for the word “open” on a limited number of doors and cupboards, she subsequently signed “open” to many different doors, cupboards, and even her pop bottles. The findings with Washoe were later replicated with
other chimps (Gardner et al., 1989).
Washoe was the first chimpanzee taught to use some of the signs of American Sign Language. Washoe died in 2007 at age 42 and throughout her life challenged many to examine their beliefs about human uniqueness. Photo permission granted by Friends of Washoe
Instead of using sign language, some researchers have developed a completely artificial language to teach to apes. This language consists of symbols called
lexigrams—small keys on a computerized board that represent words and, therefore, can be combined to form complex ideas and phrases. One subject of the research using this language is a bonobo named Kanzi (bonobos are another species of chimpanzee). Kanzi has learned approximately 350 symbols through
training, but he learned his first symbols simply by watching as researchers attempted to teach his mother how to use the language. In addition to the lexigrams he produces, Kanzi seems to recognize about 3000 spoken words. His
trainers claim that Kanzi’s skills constitute language (Savage-Rumbaugh & Lewin, 1994). They argue that he can understand symbols and at least some syntax; that he acquired symbols simply by being around others who used them; and that he produced symbols without specific training or reinforcement. Those who work with Kanzi conclude that his communication skills are quite similar to those of a young human in terms of both the elements of language (semantics and syntax) and the acquisition of language (natural and without effortful training).
Despite their ability to communicate in complex ways, debate continues to swirl about whether these animals are using language. Many language researchers point out that chimpanzees’ signing and artificial language use is very different from how humans use language. Is the vastness of the difference important? Is using 200 signs different in some critical way from being able to use 4000 signs,
roughly the number found in the ASL dictionary (Stokoe et al., 1976)? If our only criterion for whether a communication system constitutes language is the number of words used, then we can say that nonhuman species acquire some language skills after extensive training. But as you have learned in this module, human language involves more than just using words. In particular, our manipulation of phonemes, morphemes, and syntax allow us to utter an infinite number of words and sentences, thereby conveying an infinite number of thoughts.
Kanzi is a bonobo chimpanzee that has learned to use an artificial language consisting of graphical symbols that correspond to words. Kanzi can type out responses by pushing buttons with these symbols, shown in this photo. Researchers are also interested in Kanzi’s ability to understand spoken English (which is transmitted to the headphones by an experimenter who is not in the room). MICHAEL NICHOLS/National Geographic Creative
Some researchers who have worked closely with language-trained apes observed too many critical differences between humans and chimps to conclude
that language extends beyond our species (Seidenberg & Pettito, 1979). For example:
One major argument is that apes are communicating only with symbols, not with the phrase-based syntax used by humans. Although some evidence of syntax has been reported, the majority of their “utterances” consist of single signs, a couple of signs strung together, or apparently random sequences.
There is little reputable experimental evidence showing that apes pass their language skills to other apes.
Productivity—creating new words (gestures) and using existing gestures to name new objects or events—is rare, if it occurs at all.
Some of the researchers become very engaged in the lives of these animals
and talk about them as friends and family members (Fouts, 1997; Savage- Rumbaugh & Lewin, 1994). This tendency has left critics to wonder the extent to which personal attachments to the animals might interfere with the objectivity of the data.
It must be pointed out that the communication systems of different animals have their own adaptive functions. It is possible that some species simply didn’t have a need to develop a complex form of language. However, in the case of chimpanzees, this point doesn’t hold true. Both humans and chimpanzees evolved in small groups in (for the most part) similar parts of the world; thus, chimpanzees would have faced many of the same social and environmental pressures as humans. However, their brains, although quite sophisticated, are not as large or well-developed as those of humans. It seems, therefore, that a major factor in humanity’s unique language abilities is the wonderful complexity and plasticity of the human brain.
Module 8.3c Quiz:
Genes, Evolution, and Language
Know . . . 1. Which nonhuman species has had the greatest success at learning a
human language?
A. Border collies B. Bonobo chimpanzees C. Dolphins D. Rhesus monkeys
Understand . . . 2. Studies of the KE family and the FOXP2 gene indicate that
A. language is controlled entirely by a single gene found on chromosome 7.
B. language is still fluent despite a mutation to this gene. C. this particular gene is related to one specific aspect of language. D. mutations affecting this gene lead to highly expressive language
skills.
Analyze . . . 3. What is the most accurate conclusion from research conducted on
primate language abilities?
A. Primates can learn some aspects of human language, though many differences remain.
B. Primates can learn human language in full. C. Primates cannot learn human language in any way. D. Primates can respond to verbal commands, but there is no
evidence they can respond to visual cues such as images or hand signals.
Module 8.3 Summary
aphasia
Broca’s area
cross-foster
fast mapping
language
morpheme
phoneme
pragmatics
semantics
syntax
Wernicke’s area
Know . . . the key terminology from the study of language.8.3a
Understand . . . how language is structured.8.3b
Sentences are broken down into words that are arranged according to grammatical rules (syntax). The relationship between words and their meaning is referred to as semantics. Words can be broken down into morphemes, the smallest meaningful units of speech, and phonemes, the smallest sound units that make up speech.
Studies of the KE family show that the FOXP2 gene is involved in our ability to speak. However, mutation to this gene does not necessarily impair people’s ability to think. Thus, the FOXP2 gene seems to be important for just one of many aspects of human language. Multiple brain areas are involved in language —two particularly important ones are Broca’s and Wernicke’s areas.
Apply Activity Which of these represent a single phoneme and which represent a morpheme? Do any of them represent both?
1. /dis/ 2. /s/ 3. /k/
Nonhuman species certainly seem capable of acquiring certain aspects of human language. Studies with apes have shown that they can learn and use some sign language or, in the case of Kanzi, an artificial language system involving arbitrary symbols. However, critics have pointed out that many differences between human and nonhuman language use remain.
Understand . . . how genes and the brain are involved in language use.
8.3c
Apply . . . your knowledge to distinguish between units of language such as phonemes and morphemes.
8.3d
Analyze . . . whether species other than humans are able to use language.
8.3e
Chapter 9 Intelligence Testing
9.1 Measuring Intelligence Different Approaches to Intelligence Testing 351
Module 9.1a Quiz 355
The Checkered Past of Intelligence Testing 356
Working the Scientific Literacy Model: Beliefs about Intelligence 358
Module 9.1b Quiz 360
Module 9.1 Summary 361
9.2 Understanding Intelligence Intelligence as a Single, General Ability 363
Module 9.2a Quiz 365
Intelligence as Multiple, Specific Abilities 365
Working the Scientific Literacy Model: Testing for Fluid and Crystallized Intelligence 366
Module 9.2b Quiz 371
The Battle of the Sexes 371
Module 9.2c Quiz 372
Module 9.2 Summary 373
9.3 Biological, Environmental, and Behavioural Influences on
Intelligence Biological Influences on Intelligence 375
Working the Scientific Literacy Model: Brain Size and Intelligence 377
Module 9.3a Quiz 379
Environmental Influences on Intelligence 379
Module 9.3b Quiz 382
Behavioural Influences on Intelligence 382
Module 9.3c Quiz 384
Module 9.3 Summary 384
Module 9.1 Measuring Intelligence
Leilani Muir, who passed away in Alberta in 2016. The Canadian Press/Edmonton Journal
Learning Objectives
Leilani Muir kept trying to get pregnant, but to no avail. Finally, frustrated, she went to her doctor to see if there was a medical explanation. It turned out that there was, but not one that she expected; the doctors found that her fallopian tubes had been surgically destroyed, permanently sterilizing her.
How could someone’s fallopian tubes be destroyed without them knowing? Tragically, forced sterilization was a not uncommon practice in the United States and parts of Canada for almost half of the 20th century. In 1928, Alberta passed the Sexual Sterilization Act, giving doctors the power to sterilize people deemed to be “genetically unfit,” without their consent. One of the criteria that could qualify a person for being genetically unfit was getting a low score on an IQ test, which was the reason for Leilani’s own sterilization.
Leilani Muir is one of the tens of thousands of victims of the misguided application of intelligence tests. Born into a poor farming family near Calgary, Alberta, Leilani was entered by her parents into the Provincial Training School for Mental Defectives when she was 11. A few years later, when given an intelligence test, she scored 64, which was below the 70 point cut-off required by law for forced sterilization. When she was 14, she was told by doctors she needed to have her appendix removed. Trusting the good doctors, she went under the knife, never knowing the
Know . . . the key terminology associated with intelligence and intelligence testing. Understand . . . the reasoning behind the eugenics movements and its use of intelligence tests. Apply . . . the concepts of entity theory and incremental theory to help kids succeed in school. Analyze . . . why it is difficult to remove all cultural bias from intelligence testing.
9.1a
9.1b
9.1c
9.1d
full extent of the surgery she was about to undergo. After the surgery, she was never informed that her fallopian tubes had been destroyed, and had to find out on her own after her many attempts to get pregnant. Later in her life, Leilani had her IQ re-tested. She scored 89, which is close to average.
In 1996, Leilani received some measure of justice. She sued the government of Alberta and won her case, becoming the first person to receive compensation for injustices committed under the Sexual Sterilization Act. For her lifetime of not being able to have children, she received almost $750 000 in damages.
Focus Questions
1. How have intelligence tests been misused in modern society? 2. Why do we have the types of intelligence tests that we have?
What happened to Leilani Muir was terrible and should never have happened. But this story also serves to drive home an extremely important truth about
psychology, and science in general—it is important to measure things properly. This may sound trite, but Leilani’s story underscores the importance of ensuring that the research carried out in psychology and other disciplines is as rigorous as possible. Research isn’t just about writing complicated articles that only scientists and academics read; its real-world implications may ripple through society and affect people’s lives in countless ways. In Leilani’s case, her misfortune was the result of both inhumane policies passed by government and the failure to accurately measure her intelligence. Intelligence is not something like the length or mass of a physical object; there is no “objective” standard to which we can compare our measures to see if they are accurate. Instead, we have to rely upon rigorous testing of our methodologies.
So, how can we measure intelligence accurately? What does science say? As you will see in this module, this question is not easy to answer. Intelligence
measures have a very checkered past, making the whole notion of intelligence one of the most hotly contested areas in all of psychology.
Different Approaches to Intelligence Testing
Intelligence is a surprisingly difficult concept to define. You undoubtedly know people who earn similar grades even though one may seem to be “smarter” than the other. You likely also know people who do very well in school and have “book smarts,” but have difficulty in many other aspects of life, perhaps lacking “street smarts.” Furthermore, you may perceive a person to be intelligent or unintelligent, but how do you know your perceptions are not biased by their confidence, social skills, or other qualities? The history of psychology has seen many different attempts to define and measure intelligence. In this module, we will examine some of the more influential of these attempts, and then explore some of the important social implications of intelligence testing.
Francis Galton believed that intelligence was something people inherit. Thus, he believed that an individual’s relatives were a better predictor of intelligence than practice and effort. Mary Evans Picture Library/Alamy Stock Photo
Intelligence and Perception: Galton’s
Anthropometric Approach
The systematic attempt to measure intelligence in the modern era began with Francis Galton (1822–1911) (who is often given the appellation “Sir,” because he was knighted in 1909). Galton believed that because people learn about the world through their senses, those with superior sensory abilities would be able to learn more about it. Thus, he argued, sensory abilities should be an indicator of a person’s intelligence. In 1884, Galton created a set of 17 sensory tests, such as
the highest and lowest sounds people could hear or their ability to tell the difference between objects of slightly different weights, and began testing
people’s abilities in his anthropometric laboratory. Anthropometrics (literally, “the measurement of people”) referred to methods of measuring physical and mental variation in humans. Galton’s lab attracted many visitors, allowing him to measure the sensory abilities of thousands of people in England (Gillham, 2001).
One of Galton’s colleagues, James McKeen Cattell, took his tests to the United States and began measuring the abilities of university students. This research revealed, however, that people’s abilities on different sensory tests were not correlated with each other, or only very weakly. For example, having exceptional eyesight seemed to signify little about whether one would have exceptional hearing. Clearly, this was a problem, because if two measures don’t correlate well with each other, then they can’t both be indicators of the same thing, in this case, intelligence. Cattell also found that students’ scores on the sensory tests did not predict their grades, which one would expect would also be an indicator of intelligence. As a result, Galton’s approach to measuring intelligence was generally abandoned.
Intelligence and Thinking: The Stanford–Binet Test
In contrast to Galton, a prominent French psychologist, Alfred Binet, argued that intelligence should be indicated by more complex thinking processes, such as memory, attention, and comprehension. This view has influenced most
intelligence researchers up to the present day; they define intelligence as the ability to think, understand, reason, and adapt to or overcome obstacles (Neisser et al., 1996). From this perspective, intelligence reflects how well people are able to reason and solve problems, plus their accumulated knowledge.
In 1904, Binet and his colleague, Theodore Simon, were hired by the French government to develop a test to measure intelligence. At the end of the 19th century, institutional reforms in France had made primary school education available to all children. As a result, French educators struggled to deliver a
curriculum to students ranging from the very bright to those who found school exceptionally challenging. To respond to this problem, the French government wanted an objective way of identifying “retarded” children who would benefit from
specialized education (Siegler, 1992).
Binet and Simon experimented with a wide variety of tasks, trying to capture the complex thinking processes that presumably comprised intelligence. They settled on thirty tasks, arranged in order of increasing difficulty. For example, simple tasks included repeating sentences and defining common words like “house.” More difficult tasks included constructing sentences using combinations of certain words (e.g., Paris, river, fortune), reproducing drawings from memory, and being able to explain how two things differed from each other. Very difficult tasks included being able to define abstract concepts and to logically reason
through a problem (Fancher, 1985).
Binet and Simon gave their test to samples of children from different age groups to establish the average test score for each age. Binet argued that a child’s test
score measured her mental age , the average intellectual ability score for children of a specific age. For example, if a 7-year-old’s score was the same as the average score for 7-year-olds, she would have a mental age of 7, whereas if it was the same as the average score for 10-year-olds, she would have a mental age of 10, even though her chronological age would be 7 in both cases. A child with a mental age lower than her chronological age would be expected to struggle in school and to require remedial education.
The practicality of Binet and Simon’s test was apparent to others, and soon researchers in the United States began to adapt it for their own use. Lewis Terman at Stanford University adapted the test for American children and established average scores for each age level by administering the test to thousands of children. In 1916, he published the first version of his adapted test,
and named it the Stanford-Binet Intelligence Scale (Siegler, 1992).
Terman and others almost immediately began describing the Stanford-Binet test as a test intended to measure innate levels of intelligence. This differed substantially from Binet, who had viewed his test as a measure of a child’s
current abilities, not as a measure of an innate capacity. There is a crucial difference between believing that test scores reflect a changeable ability or believing they reflect an innate capacity that is presumably fixed. The interpretation of intelligence as an innate ability set the stage for the incredibly misguided use of intelligence tests in the decades that followed, as we discuss later in this module.
To better reflect people’s presumably innate levels of intelligence, Terman
adopted William Stern’s concept of the intelligence quotient, or IQ , a label that has stuck to the present day. IQ is calculated by taking a person’s mental age, dividing it by his chronological age, and then multiplying by 100. For example, a 10-year-old child with a mental age of 7 would have an IQ of 7/10 × 100 = 70. On the other hand, if a child’s mental and chronological ages were the same, the IQ score would always be 100, regardless of the age of the child; thus, 100 became the standard IQ for the “average child.”
To see the conceptual difference implied by these two ways of reporting intelligence, consider the following two statements. Does one sound more optimistic than the other?
He has a mental age of 7, so he is 3 years behind. He has an IQ of 70, so he is 30 points below average.
To many people, being 3 years behind in mental age seems changeable; with sufficient work and assistance, it feels like such a child should be able to catch up to his peers. On the other hand, having an IQ that’s 30 points below average sounds like the diagnosis of a permanent condition; such a person seems doomed to be “unintelligent” forever.
One other odd feature of both Binet’s mental age concept and Stern’s IQ was that they didn’t generalize very well to adult populations. For example, are 80- year olds twice as intelligent as 40-year-olds? After all, an 80-year-old who was as intelligent as an average 40-year-old would have an IQ of 50 (40/80 × 100 = 50); clearly, this doesn’t make sense. Similarly, imagine a 30-year-old with a mental age of 30; her IQ would be 100. But in 10 years, when she was 40, if her
mental age stayed at 30, she would have an IQ of only 75 (30/40 × 100 = 75).
Given that IQ scores remain constant after about age 16 (Eysenck, 1994), this would mean that adults get progressively less smart with every year that they age. Although children may sometimes think exactly this about their parents, their parents would clearly have a different opinion.
To adjust for this problem, psychologists began to use a different measure,
deviation IQ, for calculating the IQ of adults (Wechsler, 1939). The deviation IQ
is calculated by comparing the person’s test score with the average score for people of the same age. In order to calculate deviation IQs, one must first establish the norm, or average, for a population. To do so, psychologists administer tests to huge numbers of people and use these scores to estimate the average for people of different ages. These averages are then used as baselines against which to compare a person. Because “average” is defined to be 100, a deviation IQ of 100 means that the person is average, whereas an IQ of 115
would mean that the person’s IQ is above average (see Figure 9.1 ). One advantage of using deviation IQ scores is that it avoids the problem of IQ scores that consistently decline with age because scores are calculated relative to others of the same age.
Figure 9.1 The Normal Distribution of Scores for a Standardized Intelligence Test
The Wechsler Adult Intelligence Scale
In an ironic twist, the Wechsler Adult Intelligence Scale (WAIS) , the most common intelligence test in use today for adolescents and adults, was developed by a man who himself had been labelled as “feeble minded” by intelligence tests after immigrating to the United States from Romania at the age of nine. David Wechsler originally developed the scale in 1955 and it is now in its fourth edition.
The WAIS provides a single IQ score for each test taker—the Full Scale IQ—but also breaks intelligence into a General Ability Index (GAI) and a Cognitive Proficiency Index (CPI), as shown in Figure 9.2 . The GAI is computed from scores on the Verbal Comprehension and Perceptual Reasoning indices. These measures tap into an individual’s intellectual abilities, but without placing much emphasis on how fast he can solve problems and make decisions. The CPI, in contrast, is based on the Working Memory and Processing Speed subtests. It is included in the Full Scale IQ category because greater working memory capacity and processing speed allow more cognitive resources to be devoted to
reasoning and solving problems. Figure 9.3 shows some sample test items from the WAIS.
Figure 9.2 Subscales of the Wechsler Adult Intelligence Scale
Figure 9.3 Types of Problems Used to Measure Intelligence These hypothetical problems are consistent with the types seen on the Wechsler Adult Intelligence Scale.
Raven’s Progressive Matrices
Although the Stanford-Binet test and the WAIS have been widely used across North America, they have also been criticized by a number of researchers. One of the key problems with many intelligence tests, such as these, is that questions often are biased to favour people from the test developer’s culture or who primarily speak the test developer’s language. This cultural bias puts people from different cultures, social classes, educational levels, and primary languages, at an immediate disadvantage. Clearly, this is a problem, because a person’s “intelligence” should not be affected by whether they are fluent in English or familiar with Western culture. In response to this problem, psychologists have tried to develop “culture-free” tests.
In the 1930s, John Raven developed Raven’s Progressive Matrices , an intelligence test that is based on pictures, not words, thus making it relatively unaffected by language or cultural background. The main set of tasks found in Raven’s Progressive Matrices measure the extent to which test takers can see patterns in the shapes and colours within a matrix and then determine which
shape or colour would complete the pattern (see Figure 9.4 ).
Figure 9.4 Sample Problem from Raven’s Progressive Matrices Which possible pattern (1–8) should go in the blank space? Check your answer at the bottom of the page. Source: “Sample Problem from Raven’s Progressive Matrices,” NCS Pearson, 1998.
Answer to Figure 9.4 : Pattern 6.
Module 9.1a Quiz:
Different Approaches to Intelligence Testing
Know . . .
1. Galton developed anthropometrics as a means to measure intelligence based on .
A. creativity B. perceptual abilities C. physical size and body type D. brain convolution
Understand . . . 2. The deviation IQ is calculated by comparing an individual’s test score
A. at one point in time to that same person’s test score at a different point in time.
B. to that same person’s test score from a different IQ test; the “deviation” between the tests is a measure of whether either test is inaccurate.
C. to that same individual’s school grades. D. to the average score for other people who are the same age.
3. In an attempt to be culturally unbiased, Raven’s Progressive Matrices relies upon what types of questions?
A. Verbal analogies B. Spatial calculations C. Visual patterns D. Practical problems that are encountered in every culture
Apply . . . 4. If someone’s mental age is double her chronological age, what would her
IQ be?
A. 100 B. 50 C. 200 D. Cannot be determined with this information
The Checkered Past of Intelligence
Testing
IQ testing in North America got a significant boost during World War I. Lewis Terman, developer of the Stanford-Binet test, worked with the United States military to develop a set of intelligence tests that could be used to identify which military recruits had the potential to become officers and which should be streamed into non-officer roles. The intention was to make the officer selection process more objective, thereby increasing the efficiency and effectiveness of officer training programs. Following World War I, Terman argued for the use of intelligence tests in schools for similar purposes—identifying students who should be channelled into more “advanced” academic topics that would prepare them for higher education, and others who should be channelled into more skill- based topics that would prepare them for direct entry into the skilled trades and the general workforce. Armed with his purportedly objective IQ tests, he was a man on a mission to improve society. However, the way he went about doing so was rife with problems.
IQ Testing and the Eugenics Movement
In order to understand the logic of Terman and his followers, it is important to examine the larger societal context in which his theories were developed. The end of the 19th and beginning of the 20th centuries was a remarkable time in human history. A few centuries of European colonialism had spread Western influence through much of the world. The Industrial Revolution, which was concentrated in the West, compounded this, making Western nations more powerful militarily, technologically, and economically. And in the sciences, Darwin’s paradigm-shattering work on the origin of species firmly established the
idea of evolution by natural selection (see Module 3.1 ), permanently transforming our scientific understanding of the living world.
Although an exciting time for the advancement of human knowledge, this confluence of events also had some very negative consequences, especially in terms of how colonialism affected non-Western cultures and people of non-White ethnicities. However, the stage was set for social “visionaries” to apply Darwin’s
ideas to human culture, and to explain the military–economic–technological dominance of Western cultures by assuming that Westerners (and especially White people) were genetically superior. This explanation served as a handy justification for the colonial powers’ imposition of Western-European values on other cultures; in fact, it was often viewed that the colonizers were actually doing other cultures a favour, helping to “civilize” them by assimilating them into a “superior” cultural system.
The social Darwinism that emerged gave rise to one of the uglier social movements of recent times—eugenics, which means “good genes” (Gillham, 2001). The history of eugenics is intimately intertwined with the history of intelligence testing. In fact, Francis Galton himself, a cousin of Charles Darwin,
coined the term eugenics, gaining credibility for his ideas after making an extensive study of the heritability of intelligence.
Many people viewed eugenics as a way to “improve” the human gene pool. Their definition of “improve” is certainly up for debate. American Philosophical Society
Galton noticed that many members of his own family were successful businessmen and some, like Charles Darwin, eminent scientists. He studied other families and concluded that eminence ran in families, which he believed
was due to “good breeding.” Although families share more than genes, such as wealth, privilege, and social status, Galton believed that genes were the basis of
the family patterns he observed (Fancher, 2009).
Galton’s views influenced Lewis Terman, who promoted an explicitly eugenic philosophy; he argued for the superiority of his own “race,” and in the interest of “improving” society, believed that his IQ tests provided a strong empirical justification for eugenic practices. One such practice was the forced sterilization of people like Leilani Muir, whom we discussed at the beginning of this module.
Supporters of eugenics often noted that its logic was based on research and philosophy from many different fields. Doing so put the focus on the abstract intellectual characteristics of eugenics rather than on some of its disturbing, real- world implications. American Philosophical Society
As Terman administered his tests to more people, it seemed like his race-based beliefs were verified by his data. Simply put, people from other cultures and other apparent ethnic backgrounds, didn’t score as highly on his tests as did White people from the West (i.e., the U.S., Canada, and Western Europe, for the most
part). For example, 40% of new immigrants to Canada and the United States
scored so low they were classified as “feebleminded” (Kevles, 1985). As a result, Terman concluded that people from non-Western cultures and non-White ethnicities generally had lower IQs, and he therefore argued that it was appropriate (even desirable) to stream them into less challenging academic pursuits and jobs of lower status. For example, he wrote, “High-grade or border- line deficiency . . . is very, very common among Spanish-Indian and Mexican families of the Southwest and also among negroes. Their dullness seems to be racial, or at least inherent in the family stocks from which they come. . . . Children of this group should be segregated into separate classes. . . . They cannot master abstractions but they can often be made into efficient workers . . . from a eugenic point of view they constitute a grave problem because of their
unusually prolific breeding” (Terman, 1916, pp. 91–92).
Such ideas gained enough popularity that forced sterilization was carried out in at least 30 states and two Canadian provinces, lasting for almost half a century.
In Alberta, the Sexual Sterilization Act remained in force until 1972, by which time more than 2800 people had undergone sterilization procedures in that province alone. And as you might have guessed, new immigrants, the poor, Native people, and Black people were sterilized far more often than middle and upper class White people.
The Race and IQ Controversy
One of the reasons intelligence tests played so well into the agendas of eugenicists is that, from Terman onwards, researchers over the last century have consistently found differences in the IQ scores of people from different ethnic groups. Before we go any further, we want to acknowledge that this is a difficult, and potentially upsetting, set of research findings. However, it’s important to take a close look at this research, and to understand the controversy that surrounds it, because these findings are well known in the world of intelligence testing and could be easily misused by those who are motivated by prejudiced views. As you will see, when you take a close look at the science, the story is not nearly as clear as it may appear at first glance.
The root of this issue about “race and IQ” is that there is a clear and reliable hierarchy of IQ scores across different ethnic groups. This was first discovered in the early 1900s, and by the 1920s, the United States passed legislation making it standard to administer intelligence tests to new immigrants arriving at Ellis Island for entry into the country. The result was that overwhelming numbers of immigrants were officially classified as “morons” or “feebleminded.” Some psychologists suspected that these tests were unfair, and that the low scores of these minority groups might be due to language barriers and a lack of knowledge of American culture. Nevertheless, as intelligence tests were developed that were increasingly culturally sensitive—such as Raven’s Progressive Matrices— these differences persisted. Specifically, Asian people tended to score the highest, followed by Whites, followed by Latinos and Blacks; this has been found
in samples in several parts of the world, including Canada (Rushton & Jensen, 2005). Other researchers have found that Native people in Canada score lower as a group than Canadians with European ancestry (e.g., Beiser & Gotowiec, 2000).
The race–IQ research hit the general public in 1994 with the publication of The Bell Curve (Herrnstein & Murray, 1994), which became a bestseller. This book focused on over two decades of research that replicated the race differences in IQ that we mentioned earlier. Herrnstein and Murray also argued that human intelligence is a strong predictor of many different personal and social outcomes, such as workplace performance, income, and the likelihood of being involved in
criminal activities. Additionally, The Bell Curve argued that those of high intelligence were reproducing less than those of low intelligence, leading to a dangerous population trend in the United States. They believed that America was becoming an increasingly divided society, populated by a small class of “cognitive elite,” and a large underclass with lower intelligence. They argued that
a healthy society would be a meritocracy, in which people who had the most ability and worked the hardest would receive the most wealth, power, and status. Those who didn’t have what it took to rise to the top, such as those with low IQs, should be allowed to live out their fates, and should not therefore be helped by programs such as Head Start, affirmative action programs, or scholarships for members of visible minorities. Instead, the system should simply allow people with the most demonstrable merit to rise to the top, regardless of their cultural or
ethnic backgrounds. Although many people agree with the idea of a meritocracy in principle, a huge problem arises in implementing a meritocracy when the system is set up to systematically give certain groups advantages over other groups; in this situation, assessing true “merit” is far from straightforward.
As you can imagine, research on the race–IQ gap sparked bitter controversy. Within the academic world, some researchers have claimed that these findings
are valid (e.g., Gottfredson, 2005), whereas others have argued that these results are based on flawed methodologies and poor measurements (e.g.,
Lieberman, 2001; Nisbett, 2005). Others have sought to discredit Herrnstein and Murray’s conclusions, in particular their argument that the differences in IQ scores between ethnic groups means that there are inherent, genetic differences in intelligence between the groups. Within the general public, reaction was similarly mixed; however, this research does get used by some people to justify policies such as limiting immigration, discontinuing affirmative action programs, and otherwise working to overturn decades of progress made in the fight for civil rights and equality.
Problems with the Racial Superiority Interpretation
In many ways, the simplest critique of the racial superiority interpretation of these test score differences is that the tests themselves are culturally biased. This critique was lodged against intelligence tests from the time of Terman and, as we discussed earlier, a considerable amount of research focused on creating tests that were not biased due to language and culture. But in spite of all this work, the test score differences between ethnic groups remained.
A more subtle critique was that it wasn’t necessarily the tests that were biased, but the very process of testing itself. If people in minority groups are less familiar with standardized tests, if they are less motivated to do well on the tests, or if they are less able to focus on performing well during the testing sessions, they will be more likely to produce lower test scores. This indeed seems to be the case; researchers have found that cultural background affects many aspects of the testing process including how comfortable people are in a formal testing environment, how motivated they are to perform well on such tests, and their
ability to establish rapport with the test administrators (Anastasi & Urbina, 1996).
Research has also indicated that the IQ differences may be due to a process
known as stereotype threat , which occurs when negative stereotypes about a group cause group members to underperform on ability tests (Steele, 1997). In other words, if a Black person is reminded of the stereotype that Black people perform more poorly than White people on intelligence tests, she may end up scoring lower on that test as a result. Researchers have identified at least three reasons why this may happen. First, stereotype threat increases arousal due to the fact that individuals are aware of the negative stereotype about their group, and are concerned that a poor performance may reflect poorly on their group; this arousal then undermines their test performance. Second, stereotype threat causes people to become more self-focused, paying more attention to how well they are performing; this leaves fewer cognitive resources for them to focus on the test itself. Third, stereotype threat increases the tendency for people to actively try to inhibit negative thoughts they may have, which also reduces the
cognitive resources that could otherwise be used to focus on the test (Schmader et al., 2008). There have now been more than 200 studies on stereotype threat (Nisbett et al., 2012), establishing it as a reliable phenomenon that regularly suppresses the test scores of members of stereotyped groups.
These concerns cast doubt on the validity of IQ scores for members of non- White ethnic and cultural groups, suggesting that differences in test scores do not necessarily reflect differences in the underlying ability being tested (i.e., intelligence), but instead may reflect other factors, such as such as linguistic or cultural bias in the testing situation.
Another important critique has been lodged against the race–IQ research, arguing that even if one believes that the tests are valid and that there are intelligence differences between groups in society, these may not be the result of innate, genetic differences between the groups. For example, consider the circumstances that poor people and ethnic minorities face in countries like Canada or the United States. People from such groups tend to experience a host of factors that contribute to poorer cognitive and neurological development, such
as poorer nutrition, greater stress, lower-quality schools, higher rates of illness
(Acevedo-Garcia et al., 2008) with reduced access to medical treatment, and greater exposure to toxins such as lead (Dilworth-Bart & Moore, 2006).
One additional, subtle factor that may interfere with the test performances of people from disadvantaged groups is that the life experiences of people in those groups may encourage them to adopt certain beliefs about themselves, which then interfere with their motivations to perform their best. For example, if early experiences in educational settings lead people to believe that they are not intelligent, and that this is a fixed quality, they will tend to believe that there is little they can do to change their own intelligence, and as a result, they won’t try
very hard to do so. However, recent research suggests that it is possible to improve one’s intelligence—but one has to believe this in order to take the necessary steps to make it happen.
Working the Scientific Literacy Model Beliefs about Intelligence
Think of something you’re not very good at (or maybe have never even tried), like juggling knives, solving Sudoku puzzles, or speaking Gaelic. Most likely, you would expect that even if your initial attempts didn’t go well, with practice you could get better.
Now think about how smart you are. Do you think you could make yourself smarter? Do you ever say things like “I’m no good at math,” or “I just can’t do multiple choice tests?” Do you think about these abilities the same way that you think about knife- juggling?
Many people hold implicit beliefs that their intelligence level is relatively fixed and find it surprising that intelligence is, in fact, highly changeable. Ironically, this mistaken belief itself will tend to limit people’s potential to change their own intelligence. This is an
especially important issue for students, as children’s self- perceptions of their mental abilities have a very strong influence
on their academic performance (Greven et al., 2009).
What do we know about the kinds of beliefs that may affect test scores? Research into this phenomenon has helped to shed light on the frustrating mystery of why some people seem to consistently fall
short of reaching their potential. Carol Dweck (2002) has found that people seem to hold one of two theories about the nature of
intelligence. They may hold an entity theory : the belief that intelligence is a fixed characteristic and relatively difficult (or impossible) to change; or they may hold an incremental theory : the belief that intelligence can be shaped by experiences, practice, and effort. Whether one holds to an entity theory or incremental theory has powerful effects on one’s academic performance.
How can science test whether beliefs affect performance? In experiments by Dweck and her colleagues, students were identified as holding either entity theory or incremental theory beliefs. The students had the chance to answer 476 general knowledge questions dealing with topics such as history, literature, math, and geography. They received immediate feedback on whether their answers were correct or incorrect. Those who held entity beliefs were more likely to give up in the face of highly challenging problems, and they were likely to withdraw from situations that resulted in failure. These individuals seemed to believe that intelligence was something you either had, or you didn’t; thus, when encountering difficult problems or feelings of failure, they seemed to conclude “Well, I guess I don’t
have it,” and as a result, gave up trying (Mangels et al., 2006). As Homer Simpson has said, “Kids, you tried your best and you
failed miserably. The lesson is, never try” (Richdale & Kirkland, 1994). To the entity theorist, difficulty is a sign of inadequacy.
In comparison, people with incremental views of intelligence were
more resilient (Mangels et al., 2006), continuing to work hard even when faced with challenges and failures. After all, if intelligence and ability can change, then rather than getting discouraged by difficulties, one should keep working hard, improving one’s abilities.
Because resilience is such a desirable trait, Dweck and her colleagues tested a group of junior high students to see whether
incremental views could be taught (Blackwell et al., 2007). In a randomized, controlled experiment, they taught one group of Grade 7 students incremental theory—that they could control and change their abilities. This group’s grades increased over the school year, whereas the control group’s grades actually declined
(Figure 9.5 ).
Figure 9.5 Personal Beliefs Influence Grades
Students who held incremental views of intelligence (i.e., the belief that intelligence can change with effort) show improved grades in math compared to students who believed that
intelligence was an unchanging entity (Blackwell et al., 2007). Source: From Implicit theories of intelligence predict achievement across an Adult Transition: A
Longitudinal Study and an intervention.” Child Development, Vol 78, No 1, Pg 246-263 byLisa S.
Blackwell, Kali H. Trzesniewski, Carol Sorich Dweck. Copyright © 2007 by John Wiley & Sons, Inc.
Reproduced by permission of John Wiley & Sons, Inc.
The moral of the story? If you think you can, you might; but if you think you can’t, you won’t.
Can we critically evaluate this research? These findings suggest that it is desirable to help people adopt incremental beliefs about their abilities. However, is this always for the best? What if, in some situations, it is true that no matter how hard a person tries, he or she is unlikely to succeed, and continuing to try at all costs may be detrimental to the person’s well-being, or may close the door on other opportunities that may have turned out better? At what point do we encourage people to be more “realistic” and to accept their limitations? So far, these remain unanswered questions in this literature.
An additional difficulty surrounding these studies is that it is not fully clear what mechanisms might be causing the improvements. Does the incremental view of intelligence lead to increased attention, effort, and time invested in studying? Does it lead to less-critical self-judgments following failure experiences? Or, does it have a positive effect on mood, which has been shown to
improve performance on tests of perception and creativity (Isen et al., 1987)? In order to better understand why these mindsets work the way they do, and perhaps, how to apply them more effectively, a great deal of research is needed to determine which mechanisms are operating in which circumstances. However, regardless of the mechanism(s) involved, the fact that it is possible to help students by changing their view of intelligence could be a powerful force for educational change in the future.
Why is this relevant?
This research has huge potential to be applied in schools and to become a part of standard parenting practice. Teaching people to adopt the view that intelligence and other abilities are trainable skills should give them a greater feeling of control over their lives, strengthen their motivations, enhance their resilience to difficulty, and improve their goal-striving success. Carol Dweck and Lisa Sorich Blackwell have designed a program called Brainology to teach students from elementary through high school that the brain can be trained and strengthened through practice. They hope that programs such as this can counteract the disempowering effects of stereotypes by helping members of stereotyped groups to have greater resilience and to avoid succumbing to negative beliefs about themselves. Not only is intelligence changeable, as this research shows, but perhaps society itself can be changed through the widespread application of this research.
Module 9.1b Quiz:
The Checkered Past of Intelligence Testing
Know . . . 1. People who believe that intelligence is relatively fixed are said to
advocate a(n) theory of intelligence. A. incremental B. entity C. sexist D. hereditary
2. When people are aware of stereotypes about their social group, and their social group membership is brought to their minds, they may experience a reduction in their performance on a stereotype-relevant task. This is
known as . A. incremental intelligence B. hereditary intelligence C. stereotype threat D. intelligence discrimination
3. Eugenics was a movement that promoted A. the use of genetic engineering technologies to improve the
human gene pool.
B. the assimilation of one culture into another, often as part of colonialism.
C. using measures of physical capabilities (e.g., visual acuity) as estimates of a person’s intelligence.
D. preventing people from reproducing if they were deemed to be genetically inferior, so as to improve the human gene pool.
Apply . . . 4. As a major exam approaches, a teacher who is hoping to reduce
stereotype threat and promote an incremental theory of intelligence would most likely
A. remind test takers that males tend to do poorly on the problems. B. remind students that they inherited their IQ from their parents. C. cite research of a recent study showing that a particular gene is
linked to IQ.
D. let students know that hard work is the best way to prepare for the exam.
Analyze . . . 5. According to the discussion of the race and IQ controversy
A. there are clear IQ differences between people of different ethnicities, and these probably have a genetic basis.
B. the use of Raven’s Progressive Matrices has shown that there are in fact no differences in IQ between the “races”; any such group differences must be due to cultural biases built into the tests.
C. many scholars believe that the ethnic differences in IQ are so large that one could argue that a person’s race should be considered a relevant factor in important decisions, such as who to let into medical school or who to hire for a specific job.
D. even if tests are constructed that are culturally unbiased, the testing process itself may still favour some cultures over others.
Module 9.1 Summary
anthropometrics
deviation IQ
entity theory
incremental theory
intelligence
intelligence quotient (IQ)
mental age
Raven’s Progressive Matrices
Stanford-Binet test
stereotype threat
Wechsler Adult Intelligence Scale (WAIS)
The eugenicists believed that abilities like intelligence were inborn, and thus, by encouraging reproduction between people with higher IQs, and reducing the birthrate of people with lower IQs, the gene pool of humankind could be
9.1a Know . . . the key terminology associated with intelligence and intelligence testing.
9.1b Understand . . . the reasoning behind the eugenics movements and its use of intelligence tests.
improved.
One of the key reasons that people stop trying to succeed in school, and then eventually drop out, is that they hold a belief that their basic abilities, such as their intelligence, are fixed. Not trying then guarantees that they perform poorly, which reinforces their tendency to not try. However, this downward spiral can be stopped by training young people to think of themselves as changeable. Specifically, learning to think that the brain is like a muscle that can be strengthened through exercise leads people to improve their scores on intelligence tests, helps them become more resilient to negative circumstances, and enables them to respond to life’s challenges more effectively.
There are many reasons why the process of intelligence testing may be systematically biased, resulting in inaccuracies when testing people from certain cultural groups: Tests may contain content that is more relevant or familiar to some cultures; the method of testing (e.g., paper- and-pencil multiple-choice questions) may be more familiar to people from some cultures; the environment of testing may make people from some cultures less comfortable; the presence of negative stereotypes about one’s group may interfere with test-taking abilities; and the internalization of self-defeating beliefs may affect performance.
9.1c Apply . . . the concepts of entity theory and incremental theory to help kids succeed in school.
9.1d Analyze . . . why it is difficult to remove all cultural bias from intelligence testing.
Module 9.2 Understanding Intelligence
Lane V. Erickson/Shutterstock
Learning Objectives
Know . . . the key terminology related to understanding intelligence. Understand . . . why intelligence is divided into fluid and crystallized types. Understand . . . intelligence differences between males and females.
9.2a 9.2b
9.2c
Blind Tom was born into a Black slave family in 1849. When his mother was bought in a slave auction by General James Bethune, Tom was included in the sale for nothing because he was blind and believed to be useless. Indeed, Tom was not “smart” in the normal sense of the term. Even as an adult he could speak fewer than 100 words and would never be able to go to school. But he could play more than 7000 pieces on the piano, including a huge classical music repertoire and many of his own compositions. Tom could play, flawlessly, Beethoven, Mendelssohn, Bach, Chopin, Verdi, Rossini, and many others, even after hearing a piece only a single time. As an 11-year-old, he played at the White House, and by 16 went on a world tour. A panel of expert musicians performed a series of musical experiments on him, and universally agreed he was “among the most wonderful phenomena in musical history.” Despite his dramatic linguistic limitations, he could reproduce, perfectly, up to a 15-minute conversation without losing a single syllable, and could do so in English, French, or German, without understanding any part of what he was saying. In the mid-1800s, he was considered to be the “eighth wonder of the world.”
Today, Tom would be considered a savant , an individual with low mental capacity in most domains but extraordinary abilities in other specific areas such as music, mathematics, or art. The existence of savants complicates our discussion of intelligence considerably. Normally, the label “intelligent” or “unintelligent” is taken to indicate some sort of overall ability, the amount of raw brainpower available to the person, akin to an engine’s horsepower. But this doesn’t map onto savants at all—they have seemingly unlimited “horsepower” for certain skills and virtually none for many others. The existence of savants, and the more general phenomenon of people being good at some things (e.g., math, science) but not others (e.g., languages, art), challenges our
Apply . . . your knowledge to identify examples from the triarchic theory of intelligence. Analyze . . . whether teachers should spend time tailoring lessons to each individual student’s learning style.
9.2d
9.2e
understanding of intelligence and makes us ask more deeply, what is intelligence? Is it one ability? Or is it many?
Focus Questions
1. Is intelligence one ability or many? 2. How have psychologists attempted to measure intelligence?
When we draw conclusions about someone’s intelligence (e.g., Sally is really smart!), we intuitively know what we mean. Right? Being intelligent has to do with a person’s abilities to think, understand, reason, learn, and find solutions to problems. But this intuitive understanding unravels quickly when you start considering the questions it raises. Are these abilities related to each other? Does the content of a person’s intelligence matter? That is, does it mean the same thing if a person is very good at different things, like math, music, history, poetry, and child rearing? Or should intelligence be thought of more as a person’s abilities on these specific types of tasks? Perhaps that would mean that there isn’t any such thing as “intelligence” per se, but rather a whole host of narrower “intelligences.” As you will learn in this module, a full picture of intelligence involves considering a variety of different perspectives.
Intelligence as a Single, General Ability
When we say someone is intelligent, we usually are implying they have a high level of generalized cognitive ability. We expect intelligent people to be “intelligent” in many different ways, about many different topics. We wouldn’t normally call someone intelligent if she were good at, say, making up limericks, but nothing else. Intelligence should manifest itself in many different domains.
Scientific evidence for intelligence as a general ability dates back to early 20th- century work by Charles Spearman, who began by developing techniques to
calculate correlations among multiple measures of mental abilities (Spearman, 1923). One of these techniques, known as factor analysis , is a statistical technique that examines correlations between variables to find clusters of related variables, or “factors.” For example, imagine that scores on tests of vocabulary, reading comprehension, and verbal reasoning correlate highly together; these would form a “language ability” factor. Similarly, imagine that scores on algebra, geometry, and calculus questions correlate highly together; these would form a “math ability” factor. However, if the language variables don’t correlate very well with the math variables, then you have some confidence that these are separate factors; in this case, it would imply that there are at least two types of independent abilities: math and language abilities. For there to be an overarching general ability called “intelligence,” one would expect that tests of different types of abilities would all correlate with each other, forming only one factor.
Spearman’s General Intelligence
Spearman found that schoolchildren’s grades in different school subjects were positively correlated, even though the content of the different topics (e.g., math vs. history) was very different. This led Spearman to hypothesize the existence
of a general intelligence factor (abbreviated as “g”). Spearman believed that g represented a person’s “mental energy,” reflecting his belief that some people’s brains are simply more “powerful” than others (Sternberg, 2003). This has greatly influenced psychologists up to the present day, cementing within the field
the notion that intelligence is a basic cognitive trait comprising the ability to learn, reason, and solve problems, regardless of their nature; common intelligence
tests in use today calculate g as an “overall” measure of intelligence (Johnson et al., 2008).
But is g real? Does it predict anything meaningful? In fact, g does predict many important phenomena. For example, g correlates quite highly with high school and university grades (Neisser et al., 1996), how many years a person will stay in school, and how much they will earn afterwards (Ceci & Williams, 1997).
General intelligence scores also predict many seemingly unrelated phenomena,
such as how long people are likely to live (Gottfredson & Deary, 2004), how
quickly they can make snap judgments on perceptual discrimination tasks (i.e.,
laboratory tasks that test how quickly people form perceptions; Deary & Stough, 1996), and how well people can exert self-control (Shamosh et al., 2008). Some other examples of g’s influences are depicted in Figure 9.6 .
Figure 9.6 General Intelligence Is Related to Many Different Life Outcomes General intelligence (g) predicts not just intellectual ability, but also psychological well-being, income, and successful long-term relationships. Source: Based on “General Intelligence is related to Various Outcomes” Adapted from Herrnstein, R., & Murray, C. (1994).
The bell curve: Intelligence and class structure in American life. New York: Free Press.; Gottfredson, L. (1997). Why g
matters : Complexity of everyday life. Intelligence, 24, 79–132.
In the workplace, intelligence test scores not only predict who gets hired, but also how well people perform at a wide variety of jobs. In fact, the correlation is so
strong that after almost a century of research (Schmidt & Hunter, 1998), general mental ability has emerged as the single best predictor of job
performance (correlation = .53; Hunter & Hunter, 1984). Overall intelligence is a far better predictor than the applicant’s level of education (correlation = .10) or how well the applicant does in the job interview itself (correlation = .14). It is amazing to think that in order to make a good hiring decision, a manager would be better off using a single number given by an IQ test than actually sitting down and interviewing applicants face to face!
The usefulness of g is also shown by modern neuroscience research findings that overall intelligence predicts how well our brains work. For example, Tony Vernon at Western University and his colleagues have found that general intelligence test scores predict how efficiently we conduct impulses along nerve
fibres and across synapses (Johnson et al., 2005; Reed et al., 2004). This
efficiency of nerve conduction allows for more efficient information processing overall. As a result, when working on a task, the brains of highly intelligent people don’t have to work as hard as those of less intelligent people; high IQ
brains show less overall brain activation than others for the same task (Grabner et al., 2003; Haier et al., 1992).
Thus, overall intelligence, as indicated by g, is related to many real-world phenomena, from how well we do at work to how well our brains function.
Does g Tell us the Whole Story?
Clearly, g reflects something real. However, we have to remember that correlation does not equal causation. It is possible that the effects of g are due to motivation, self-confidence, or other variables. For example, one would expect that being motivated to succeed, as well as being highly self-confident, could lead to better grades, better IQ scores, and better job performance. Therefore, it is important to be cautious when interpreting these results.
We should also ask whether g can explain everything about a person’s intelligence. For example, how could a single number possibly capture the kinds of genius exhibited by savants like Blind Tom, who are exceptionally talented in some domains but then severely impaired in others? It is easy to find other examples in your own experience; surely, you have known people who were very talented in art or music but terrible in math or science? Or perhaps you have known an incredibly smart person who was socially awkward, or a charismatic and charming person whom you’d never want as your chemistry partner? There may be many ways of being intelligent, and reducing such diversity to a single number seems to overlook the different types of intelligence that people have.
Module 9.2a Quiz:
Intelligence as a Single, General Ability
Know . . . 1. Spearman believed that
A. people have multiple types of intelligence. B. intelligence scores for math and history courses should not be
correlated.
C. statistics cannot help researchers understand how different types of intelligence are related to each other.
D. some people’s brains are more “powerful” than others, thus giving them more “mental energy.”
Understand . . . 2. What is factor analysis?
A. A method of ranking individuals by their intelligence B. A statistical procedure that is used to identify which sets of
psychological measures are highly correlated with each other
C. The technique of choice for testing for a single, general intelligence
D. The technique for testing the difference between two means
3. Researchers who argue that g is a valid way of understanding intelligence would NOT point to research showing
A. people with high g make perceptual judgments more quickly. B. people with high g are more likely to succeed at their jobs. C. the brains of people with low g conduct impulses more slowly. D. people with low g are better able to do some tasks than people
with high g.
Intelligence as Multiple, Specific Abilities
Spearman himself believed that g didn’t fully capture intelligence because his own analyses showed that although different items on an intelligence test were correlated with each other, their correlations were never 1.0, and usually far less
than that. Thus, g cannot be the whole story; there must, at the very least, be other factors that account for the variability in how well people respond to different questions.
One possible explanation is that in addition to a generalized intelligence, people also possess a number of specific skills. Individual differences on these skills may explain some of the variability on intelligence tests that is not accounted for
by g. In a flurry of creativity, Spearman chose the inspired name “s” to represent this specific-level, skill-based intelligence. His two-factor theory of intelligence
was therefore comprised of g and s, where g represents one’s general, overarching intelligence, and s represents one’s skill or ability level for a given task.
Nobody has seriously questioned the s part of Spearman’s theory; obviously, each task in life, from opening a coconut, to solving calculus problems, requires
abilities that are specific to the task. However, the concept of g has come under heavy fire throughout the intervening decades, leading to several different
theories of multiple intelligences.
The first influential theory of multiple intelligences was created by Louis Thurstone, who examined scores of general intelligence tests using factor
analysis, and found seven different clusters of what he termed primary mental abilities. Thurstone’s seven factors were word fluency (the person’s ability to produce language fluently), verbal comprehension, numeric abilities, spatial
visualization, memory, perceptual speed, and reasoning (Thurstone, 1938). He argued that there was no meaningful g, but that intelligence needed to be understood at the level of these primary mental abilities that functioned
independently of each other. However, Spearman (1939) fired back, arguing that Thurstone’s seven primary mental abilities were in fact correlated with each other, suggesting that there was after all an overarching general intelligence.
A highly technical and statistical debate raged for several more decades
between proponents of g and proponents of multiple intelligences, until it was eventually decided that both of them were right.
The Hierarchical Model of Intelligence
The controversy was largely settled by the widespread adoption of hierarchical
models that describe how some types of intelligence are “nested” within others in a similar manner to how, for example, a person is nested within her community, which may be nested within a city. The general hierarchical model describes how
our lowest-level abilities (those relevant to a particular task, like Spearman’s s) are nested within a middle level that roughly corresponds to Thurstone’s primary mental abilities (although not necessarily the specific ones that Thurstone
hypothesized), and these are nested within a general intelligence (Spearman’s g; Gustaffson, 1988). By the mid-1990s, analyses of prior research on intelligence concluded that almost all intelligence studies were best explained by a three-
level hierarchy (Carroll, 1993).
What this means is that we have an overarching general intelligence, which is made up of a small number of sub-abilities, each of which is made up of a large number of specific abilities that apply to individual tasks. However, even this didn’t completely settle the debate about what intelligence really is, because it left open a great deal of room for different theories of the best way to describe the middle-level factors. And as you will see in the next section, even the debate
about g has been updated in recent years.
Working the Scientific Literacy Model
Testing for Fluid and Crystallized Intelligence
The concept of g implies that performance on all aspects of an intelligence test is influenced by this central ability. But careful analyses of many data sets, and recent neurobiological evidence,
have shown that there may be two types of g that have come to be called fluid intelligence (Gf) and crystallized intelligence (Gc).
What do we know about fluid and crystallized intelligence? The distinction between fluid and crystallized intelligence is basically the difference between “figuring things out” and
“knowing what to do from past experience.” Fluid intelligence (Gf) is a type of intelligence used in learning new information
and solving new problems not based on knowledge the person already possesses. Tests of Gf involve problems such as pattern recognition and solving geometric puzzles, neither of which is heavily dependent on past experience. For example, Raven’s Progressive Matrices, in which a person is asked to complete a series of geometric patterns of increasing complexity (see Module 9.1 ), is the most widely used measure of Gf. In contrast, crystallized intelligence (Gc) is a type of intelligence that draws upon past learning and experience. Tests of Gc, such as tests of vocabulary and general knowledge, depend heavily on individuals’ prior knowledge to come up with
the correct answers (Figure 9.7 ; Cattell, 1971).
Figure 9.7 Fluid and Crystallized Intelligence
Fluid intelligence is dynamic and changing, and may eventually become crystallized into a more permanent form. AVAVA/Shutterstock
Gf and Gc are thought to be largely separate from each other, with two important exceptions. One is that having greater fluid intelligence means that the person is better able to process information and to learn; therefore, greater Gf may, over time, lead to greater Gc, as the person who processes more
information will gain more crystallized knowledge (Horn & Cattell, 1967). Note, however, that this compelling hypothesis has received little empirical support thus far (Nisbett et al., 2012). The second is that it is difficult, perhaps impossible, to measure Gf without tapping into people’s pre-existing knowledge and experience, as we discuss below.
How can science help distinguish between fluid and crystallized intelligence? One interesting line of research that supports the Gf/Gc distinction comes from examining how each type changes over
the lifespan (Cattell, 1971; Horn & Cattell, 1967). In one study, people aged 20 to 89 years were given a wide array of tasks,
including the Block Design task (see Figure 9.3 ), the Tower of London puzzle (see Figure 9.8 ), and tests of reaction time. Researchers have found that performance in Gf-tasks declines after a certain age, which some research estimates as middle
adulthood (Bugg et al., 2006), whereas other studies place the beginning of the decline as early as the end of adolescence
(Avolio & Waldman, 1994; Baltes & Lindenberger, 1997). Measures of Gc (see Figure 9.9 ), by comparison, show greater stability as a person ages (Schaie, 1994). Healthy, older adults generally do not show much decline, if any, in their crystallized knowledge, at least until they reach their elderly years
(Miller et al., 2009).
Figure 9.8 Measuring Fluid Intelligence
The Tower of London problem has several versions, each of which requires the test taker to plan and keep track of rules. For example, the task might involve moving the coloured beads from the initial position so that they match any of the various end goal positions. Source: Shallice, T. (1982). Specific impairments of planning. Philosophical Transcripts of the Royal
Society of London, B 298, 199–209. “Measuring Fluid Intelligence.” Copyright © 1982 by The Royal
Society. Reprinted by permission of The Royal Society.
Figure 9.9 Measuring Crystallized Intelligence
Crystallized intelligence refers to facts, such as names of countries.
Neurobiological evidence further backs this up. The functioning of brain regions associated with Gf tasks declines sooner than the
functioning of those regions supporting Gc tasks (Geake & Hansen, 2010). For example, the decline of Gf with age is associated with reduced efficiency in the prefrontal cortex
(Braver & Barch, 2002), a key brain region involved in the cognitive abilities that underlie fluid intelligence (as discussed below). In contrast, this brain region does not play a central role in crystallized intelligence, which is more dependent on long-term memory systems that involve a number of different regions of the cortex.
Can we critically evaluate crystallized and fluid intelligence? There are certainly questions we can ask about crystallized and fluid intelligence. For one, is there really any such thing as fluid intelligence, or does it merely break down into specific sub- abilities?
Cognitive psychologists generally accept that fluid intelligence is a blending of several different cognitive abilities. For example, the abilities to switch attention from one stimulus to another, inhibit distracting information from interfering with concentration, sustain attention on something at will, and keep multiple pieces of information in working memory at the same time, are all part of
fluid intelligence (Blair, 2006). If Gf is simply a statistical creation that reflects the integration of these different processes, perhaps researchers would be better off focusing their attention on these systems, rather than the more abstract construct Gf.
Another critique is that fluid and crystallized intelligence are not, after all, entirely separable. Consider the fact that crystallized intelligence involves not only possessing knowledge, but also being able to access that knowledge when it’s needed. Fluid cognitive processes, and the brain areas that support them such as the prefrontal cortex, play important roles in both storing and retrieving crystallized knowledge from long-term memory
(Ranganath et al., 2003).
Similarly, tests of fluid intelligence likely also draw upon crystallized knowledge. For example, complete-the-pattern tasks
such as Raven’s Progressive Matrices may predominantly reflect fluid intelligence, but people who have never seen any type of similar task or had any practice with such an exercise will likely struggle with them more than someone with prior exposure to similar tasks. Imagine learning a new card game—you would have to rely on your fluid intelligence to help you learn the rules, figure out effective strategies, and outsmart your opponents. However, your overall knowledge of cards, games, and strategies will help you, especially if you compare yourself to a person who has played no such games in his life.
Why is this relevant? Recognizing the distinctiveness of Gf and Gc can help to reduce stereotypes and expectations about intelligence in older persons, reminding people that although certain kinds of intelligence may decline with age, other types that rely on accumulated knowledge
and wisdom may even increase as we get older (Kaufman, 2001). Also, research on fluid intelligence has helped psychologists to develop a much more detailed understanding of the full complement of cognitive processes that make up intelligence, and to devise tests that measure these processes more precisely.
Sternberg’s Triarchic Theory of Intelligence
Other influential models of intelligence have been proposed in attempts to move
beyond g. For example, Robert Sternberg (1983, 1988) developed the triarchic theory of intelligence , a theory that divides intelligence into three distinct types: analytical, practical, and creative (see Figure 9.10 ). These components can be described in the following ways:
Analytical intelligence is “book smarts.” It’s the ability to reason logically
through a problem and to find solutions. It also reflects the kinds of abilities
that are largely tested on standard intelligence tests that measure g. Most intelligence tests predominantly measure analytical intelligence, while generally ignoring the other types.
Practical intelligence is “street smarts.” It’s the ability to find solutions to real-world problems that are encountered in daily life, especially those that involve other people. Practical intelligence is what helps people adjust to new environments, learn how to get things done, and accomplish their goals. Practical intelligence is believed to have a great deal to do with one’s job performance and success.
Creative intelligence is the ability to generate new ideas and novel solutions to problems. Obviously, artists must have some level of creative intelligence, because they are, by definition, trying to create things that are new. It also takes creative intelligence to be a scientist because creative thinking is often required to conceive of good scientific hypotheses and develop ways of
testing them (Sternberg et al., 2001).
Figure 9.10 The Triarchic Theory of Intelligence According to psychologist Robert Sternberg, intelligence comprises three overlapping yet distinct components. Source: Lilienfeld, Scott O.; Lynn, Steven J; Namy, Laura L.; Woolf, Nancy J., Psychology: From Inquiry To Understanding,
Books A La Carte Edition, 2nd Ed., ©2011. Reprinted and Electronically reproduced by permission of Pearson Education,
Inc., New York, NY.
Myths in Mind Learning Styles One of the biggest arenas in which people have applied the idea that there are multiple types of intelligence is the widespread belief in educational settings that different people process information better through specific modalities, such as sight, hearing, and bodily movement. If this is true, then it suggests that people have different learning styles (e.g., people may be visual learners, auditory learners, tactile learners, etc.), and therefore, educators would be more effective if they tailor their lesson plans to the learning styles of their students, or at least ensure that they appeal to a variety of learning styles.
However, finding evidence to support this has proven difficult. In fact, dozens of studies have failed to show any benefit for tailoring information
to an individual’s apparent learning style (Pasher et al., 2008). This result probably reflects the fact that regardless of how you encounter information—through reading, watching, listening, or moving around— retaining it over the long term largely depends on how deeply you
process and store the meaning of the information (Willingham, 2004), which in turn is related to how motivated students are to learn. As a result, rather than trying to match the way that information is presented to the presumed learning styles of students, it is likely far more important for teachers to be able to engage students in ways they find interesting, meaningful, fun, personally relevant, and experientially engaging.
Sternberg believed that both practical and creative intelligences are better than analytical intelligence at predicting real-world outcomes, such as job success
(Sternberg et al., 1995). However, some psychologists have criticized Sternberg’s studies of job performance, arguing that the test items that were supposed to measure practical intelligence were merely measuring job-related
knowledge (Schmidt & Hunter, 1993). Other psychologists have questioned whether creative intelligence, one of the key components of Sternberg’s theory, actually involves “intelligence” per se, or is instead measuring the tendency to
think in ways that challenge norms and conventions (Gottfredson, 2003; Jensen, 1993). These critiques show us how challenging it can be to define intelligence, and to predict how intelligence—or intelligences—will influence real- world behaviours.
Gardner’s Theory of Multiple Intelligences
Howard Gardner proposed an especially elaborate theory of multiple intelligences. Gardner was inspired by specific cases, such as people who were savants (discussed in the introduction to this module), who had extraordinary
abilities in limited domains, very poor abilities in many others, and low g. Gardner also was influenced by cases of people with brain damage, which indicated that some specific abilities could be dramatically affected while others remained
intact (Gardner, 1983, 1999). He also noted that “normal people” (presumably, those of us who are not savants and also don’t have brain damage) differ widely in their abilities and talents, having a knack for some things but hopeless at others, which doesn’t fit the notion that intelligence is a single, overarching ability.
Based on his observations, Gardner proposed a theory of multiple intelligences , a model claiming that there are seven (now updated to at least nine) different forms of intelligence, each independent from the others (see Table 9.1 ). As intuitively appealing as this is, critics have pointed out that few of Gardner’s intelligences can be accurately and reliably measured, making his theory unfalsifiable and difficult to research. For example, how would you reliably measure “existential intelligence” or “bodily/kinesthetic intelligence”? You cannot simply ask people how existential they are, or how well they are able to attune to their bodies, relative to other people. Creating operational definitions of these concepts has proven to be a difficult challenge, and has held back empirical work on Gardner’s theory. This is not a critique against Gardner specifically, but rather, highlights the need for researchers to develop better ways of measuring
intelligence (Tirri & Nokelainen, 2008).
Table 9.1 Gardner’s Proposed Forms of Intelligence Source: Based on The Nine Types of Intelligence By Howard Gardner.
Verbal/linguistic
intelligence
The ability to read, write, and speak effectively
Logical/mathematical
intelligence
The ability to think with numbers and use abstract thought; the
ability to use logic or mathematical operations to solve
problems
Visuospatial
intelligence
The ability to create mental pictures, manipulate them in the
imagination, and use them to solve problems
Bodily/kinesthetic
intelligence
The ability to control body movements, to balance, and to
sense how one’s body is situated
Musical/rhythmical
intelligence
The ability to produce and comprehend tonal and rhythmic
patterns
Interpersonal
intelligence
The ability to detect another person’s emotional states,
motives, and thoughts
Self/intrapersonal
intelligence
Self-awareness; the ability to accurately judge one’s own
abilities, and identify one’s own emotions and motives
Naturalist
intelligence
The ability to recognize and identify processes in the natural
world—plants, animals, and so on
Existential
intelligence
The tendency and ability to ask questions about purpose in life
and the meaning of human existence
PSYCH @ The NFL Draft One rather interesting application of IQ has been to try to predict who will succeed in their careers. One test in particular, the Wonderlic Personnel Test, is widely used to predict career success in many different types of
jobs (Schmidt & Hunter, 1998; Schmidt et al., 1981). It has even become famous to National Football League (NFL) fans, because Wonderlic scores are one of many factors that influence which college players are drafted by NFL teams. This is no small thing—high draft picks receive multimillion dollar contracts. The logic behind using Wonderlic scores is that football is a highly complex game, involving learning and memorizing many complicated strategies, following all the rules, and being able to update strategies “on the fly.” Football is not only about being agile, fast, and strong; it might also involve intelligence.
But does the Wonderlic, a 50-item, 12-minute IQ test, actually predict NFL success, as the NFL has believed since the 1970s? According to research, the answer is “only sometimes,” but not the way you might think.
After studying 762 players from the 2002, 2003, and 2004 drafts and measuring their performance in multiple ways, researchers concluded that there was no significant correlation between Wonderlic scores and performance. What’s more, the performance of only two football positions, tight end and defensive back, showed any significant correlation with Wonderlic scores, and it was in a negative direction
(Lyons et al., 2009)! This means that lower intelligence scores predicted greater football success for these positions.
It seems that NFL teams would be well advised to throw out the Wonderlic test entirely, or perhaps only use it to screen for defensive backs and tight ends, and choose the lower-scoring players. No offence is intended whatsoever to football players, who may be extremely intelligent individuals, but in general, being highly intelligent does not seem to be an advantage in professional football. In the now immortalized words of former Washington Redskins quarterback Joe Thiesmann, “Nobody in the game of football should be called a genius. A genius is somebody like Norman Einstein.”
The Wonderlic Personnel Test is supposed to predict success in professional football, although it is not always very successful. This failure could be because of low validity. Ed Reinke/AP Images
Gardner’s theory has set off a firestorm of controversy in the more than 30 years since its initial proposal, gaining little traction in the academic literature, but being widely embraced in applied fields, such as education. While critics point to the lack of reliable ways of measuring Gardner’s different intelligences, proponents argue that there is more to a good theory than whether you can measure its
constructs. From the applied perspective, Gardner’s theory is useful. It helps teachers to create more diverse and engaging lesson plans to connect with and motivate students with different strengths. It helps people to see themselves as capable in different ways, rather than feeling limited by their IQ score, especially if it is not very high. And, it helps explain the wide range of human abilities and accomplishments far better than a mere IQ score.
From this perspective, perhaps the “psychometric supremacists” (Kornhaber, 2004), who insist that variables must be reliably quantifiable, might be missing the point. After all, even though IQ scores, for example, predict real-world outcomes like job status and income and offer a reliable means for identifying
students who qualify for extra educational attention (such as “gifted” students or students with learning issues), they help very little in understanding people’s strengths or weaknesses, and offer little to no guidance in actually helping people to improve their performance in different areas. Besides, IQ tests are almost exclusively based on highly unrealistic and limited testing situations, such as answering questions on paper-and-pencil tests while sitting in a room, whereas Gardner’s theory was formed out of real-world observations of the abilities of people with a wide range of accomplishments. Given that it is essentially impossible to objectively quantify many different types of abilities (e.g., being a good dancer, farmer, actor, comedian), it follows that you cannot judge a theory that purports to explain such abilities on the same grounds as theories about more easily quantifiable constructs.
The debate over Gardner’s theory lays bare a fundamental tension in the psychological sciences, which is that sometimes at least, the nuances of human behaviour cannot be easily measured, or perhaps even be measured at all. Should the observations and wisdom of teachers with decades of experience be discounted because scientists cannot develop quantifiable measures of certain constructs? However, if you accept the argument that “human experience” can trump psychometrically rigorous evidence, then where do you draw the line? Does this not throw into question the whole scientific basis of psychology itself?
We can’t resolve these questions for you here, but they remain excellent questions. The debate rages on.
Module 9.2b Quiz:
Intelligence as Multiple, Specific Abilities
Know . . . 1. Which of the following is not part of the triarchic theory of intelligence?
A. Practical intelligence B. Analytical intelligence C. Kinesthetic intelligence D. Creative intelligence
2. proposed that there are multiple forms of intelligence, each independent from the others.
A. Robert Sternberg B. Howard Gardner C. L. L. Thurstone D. Raymond Cattell
3. The ability to adapt to new situations and solve new problems reflects intelligence(s), whereas the ability to draw on one’s experiences and knowledge reflects intelligence(s).
A. fluid; crystallized B. crystallized; fluid C. general; multiple D. multiple; general
Analyze . . . 4. The hierarchical model of intelligence claims that
A. some types of intelligence are more powerful and desirable than others.
B. intelligence is broken down into two factors, a higher-level factor called g, and a lower-level factor called s.
C. scores on intelligence tests are affected by different levels of factors, ranging from lower-level factors such as physical health, to higher-level factors such as a person’s motivation for doing well on a test.
D. intelligence is comprised of three levels of factors, which are roughly similar to Spearman’s g, Thurstone’s primary mental abilities, and Spearman’s s.
The Battle of the Sexes
The distinction between g and multiple intelligences plays an important role in the oft-asked question, “Who is smarter, females or males?” Although earlier
studies showed some average intelligence differences between males and females, this has not been upheld by subsequent research and is likely the result of bias in the tests that favoured males over females. One of the most conclusive studies used 42 different tests of mental abilities to compare males and females
and found almost no differences in intelligence between the sexes (Johnson & Bouchard, 2007).
Some research has found that although males and females have the same average IQ score, there is much greater variability in male scores, which suggests that there are more men with substantial intellectual challenges, as well
as more men who are at the top of the brainpower heap (Deary et al., 2007; Dykiert et al., 2009). However, this may not be as simple as it appears. For example, one type of test that shows this male advantage at the upper levels of ability examines math skills on standardized tests. A few decades ago, about 12
times more males than females scored at the very top (Benbow & Stanley, 1983). This difference has decreased in recent years to 3–4 times as many males scoring at the top end of the spectrum. Not surprisingly, this change has occurred just as the number of math courses being taken by females—and the efforts made to increase female enrollment in such courses—has increased. So, the difference in results between the sexes is still there, but has been vastly
reduced by making math education more accessible for females (Wai et al., 2010).
The apparent advantage enjoyed by males may also be the result of an unintentional selection bias. More males than females drop out of secondary school; because these males would have lower IQs, on average, the result is that fewer low-IQ men attend university. Therefore, most of the samples of students used in psychology studies are skewed in that they under-represent men with low IQs. This biased sampling of males and females would make it
seem like men have higher fluid intelligence, when in reality they may not (Flynn & Rossi-Casé, 2011).
So, who is smarter, males or females? Neither. The best data seems to show that they are basically equal in overall intelligence.
Do Males and Females have Unique Cognitive
Skills?
Although the results discussed above suggest that males and females are equally intelligent, when multiple intelligences are considered, rather than overall IQ, a clear difference between the sexes does emerge. Females are, on average, better at verbal abilities, some memory tasks, and the ability to read people’s basic emotions, whereas males have the advantage on visuospatial
abilities, such as mentally rotating objects or aiming at objects (see Figure 9.11 ; Halpern & LaMay, 2000; Johnson & Bouchard, 2007; Tottenham et al., 2005; Weiss et al., 2003).
Figure 9.11 Mental Rotation and Verbal Fluency Tasks Some research indicates that, on average, males outperform females on mental rotation tasks (a), while females outperform men on verbal fluency (b).
This finding is frequently offered as an explanation for why males are more represented in fields like engineering, science, and mathematics. However, there are many other factors that could explain the under-representation of women in these disciplines, such as prevalent stereotypes that discourage girls from entering the maths and sciences, parents from supporting them in doing so, and
teachers from evaluating females’ work without bias.
Overlooking the many other factors that limit females’ participation in the maths and sciences is a dangerous thing to do. This was dramatically shown in 2005 when the President of Harvard University, Lawrence Summers, was removed from his position shortly after making a speech in which he argued that innate differences between the sexes may be responsible for under-representation of women in science and engineering. The outrage many expressed at his comments reflected the fact that many people realize that highlighting innate differences while minimizing or ignoring systemic factors only serves to perpetuate problems, not solve them.
Module 9.2c Quiz:
The Battle of the Sexes
Know . . . 1. Men tend to outperform women on tasks requiring , whereas
women outperform men on tasks requiring . A. spatial abilities; the ability to read people’s emotions B. practical intelligence; interpersonal intelligence C. memory; creativity D. logic; intuition
Analyze . . . 2. Research on gender differences in intelligence leads to the general
conclusion that
A. males are more intelligent than females. B. females are more intelligent than males. C. males and females are equal in overall intelligence. D. it has been impossible, thus far, to tell which gender is more
intelligent.
Module 9.2 Summary
crystallized intelligence (Gc)
factor analysis
fluid intelligence (Gf)
general intelligence factor (g)
multiple intelligences
savant
triarchic theory of intelligence
Mental abilities encompass both the amount of knowledge accumulated and the ability to solve new problems. This understanding is consistent not only with our common views of intelligence, but also with the results of decades of intelligence testing. Also, the observation that fluid intelligence can decline over the lifespan, even as crystallized intelligence remains constant, lends further support to the contention that they are different abilities.
Males and females generally show equal levels of overall intelligence, as measured by standard intelligence tests. However, men do outperform women on some tasks, particularly spatial tasks such as mentally rotating objects, whereas women outperform men on other tasks, such as perceiving emotions. Although there are some male–female differences in specific abilities, such as math, it is not yet clear whether these reflect innate differences between the sexes, or whether other factors are responsible, such as reduced enrollment of women in math classes and the presence of stereotype threat in testing
9.2a Know . . . the key terminology related to understanding intelligence.
9.2b Understand . . . why intelligence is divided into fluid and crystallized types.
9.2c Understand . . . intelligence differences between males and females.
sessions.
This theory proposes the existence of analytical, practical, and creative forms of intelligence.
Apply Activity Classify whether the individual in the following scenario is low, medium, or high in regard to each of the three aspects of intelligence.
Katrina is an excellent chemist. She has always performed well in school, so it is no
surprise that she earned her PhD from a prestigious institution. Despite her many
contributions and discoveries related to chemistry, however, she seems to fall short in
some domains. For example, Katrina does not know how to cook her own meals and if
anything breaks at her house, she has to rely on someone else to fix it.
Certainly, no one would want to discourage teachers from being attentive to the unique characteristics that each student brings to the classroom. However, large- scale reviews of research suggest that there is little basis for individualized teaching based on learning styles (e.g., auditory, visual, kinesthetic).
9.2d Apply . . . your knowledge to identify examples from the triarchic theory of intelligence.
9.2e Analyze . . . whether teachers should spend time tailoring lessons to each individual student’s learning style.
Module 9.3 Biological, Environmental, and Behavioural Influences on Intelligence
Miguel Medina/AFP/Newscom
Learning Objectives
Know . . . the key terminology related to heredity, environment, and intelligence. Understand . . . different approaches to studying the genetic basis of intelligence.
9.3a
9.3b
In 1955, the world lost one of the most brilliant scientists in history, Albert Einstein. Although you are probably familiar with his greatest scientific achievements, you may not know about what happened to him after he died—or more specifically, what happened to his brain.
Upon his death, a forward-thinking pathologist, Dr. Thomas Harvey, removed Einstein’s brain (his body was later cremated) so that it could be studied in the hope that medical scientists would eventually unlock the secret to his genius. Dr. Harvey took photographs of Einstein’s brain, and then it was sliced up into hundreds of tissue samples placed on microscope slides, and 240 larger blocks of brain matter, which were preserved in fluid. Surprisingly, Dr. Harvey concluded that the brain wasn’t at all remarkable, except for being smaller than average (1230 grams, compared to the average of 1300–1400 grams).
You might expect that Einstein’s brain was intensively studied by leading neurologists. But, instead, the brain mysteriously disappeared. Twenty- two years later, a journalist named Steven Levy tried to find Einstein’s brain. The search was fruitless until Levy tracked down Dr. Harvey in Wichita, Kansas, and interviewed him in his office. Dr. Harvey was initially reluctant to tell Levy anything about the brain, but eventually admitted that he still had it. In fact, he kept it right there in his office! Sheepishly, Dr. Harvey opened a box labelled “Costa Cider” and there, inside two large jars, floated the chunks of Einstein’s brain. Levy later wrote, “My eyes were fixed upon that jar as I tried to comprehend that these pieces of gunk bobbing up and down had caused a revolution in physics and quite possibly changed the course of civilization. Swirling in formaldehyde was the power of the smashed atom, the mystery of the universe’s black holes, the utter miracle of human achievement.”
Since that time, several research teams have discovered important
Apply . . . your knowledge of environmental and behavioural effects on intelligence to understand how to enhance your own cognitive abilities. Analyze . . . the belief that older children are more intelligent than their younger siblings.
9.3c
9.3d
abnormalities in Einstein’s brain. Einstein had a higher than normal ratio
of glial cells to neurons in the left parietal lobe (Diamond et al., 1985) and parts of the temporal lobes (Kigar et al., 1997), and a higher density of neurons in the right frontal lobe (Anderson & Harvey, 1996). Einstein’s parietal lobe has been shown to be about 15% larger than
average, and to contain an extra fold (Witelson et al., 1999). The frontal lobes contain extra convolutions (folds and creases) as well. These extra folds increase the surface area and neural connectivity in those areas.
How might these unique features have affected Einstein’s intelligence? The frontal lobes are heavily involved in abstract thought, and the parietal lobes are involved in spatial processing, which plays a substantial role in mathematics. Thus, these unique brain features may provide a key part of the neuroanatomical explanation for Einstein’s remarkable abilities in math and physics. Einstein not only had a unique mind, but a unique brain.
Focus Questions
1. Which biological and environmental factors have been found to be important contributors to intelligence?
2. Is it possible for people to enhance their own intelligence?
Wouldn’t it be wonderful to be as smart as Einstein? Or even just smarter than you already are? Imagine if you could boost your IQ, upgrading your brain like you might upgrade a hard drive. You could learn more easily, think faster, and remember more. What benefits might you enjoy? Greater success? A cure for cancer? A Nobel Prize? At least you might not have to study as much to get good grades. As you will read in this module, there are in fact ways to improve your intelligence (although perhaps not to “Einsteinian” levels). However, to understand how these techniques can benefit us, we must also understand how our biology and our environment—”nature” and “nurture”—interact to influence intelligence.
Biological Influences on Intelligence
The story of Einstein’s brain shows us, once again, that our behaviours and abilities are linked to our biology. However, although scientists have been interested in these topics for over 100 years, we are only beginning to understand the complex processes that influence measures like IQ scores. In this section, we discuss the genetic and neural factors that influence intelligence, and how they may interact with our environment.
The Genetics of Intelligence: Twin and Adoption
Studies
The belief that intelligence is a capacity that we are born with has been widely held since the early studies of intelligence. However, early researchers lacked today’s sophisticated methods for studying genetic influences, so they had to rely upon their observations of whether intelligence ran in families, which it seemed
to do (see Module 9.1 ). Since those early days, many studies have been conducted to see just how large the genetic influence on intelligence may be.
Studies of twins and children who have been adopted have been key tools allowing researchers to begin estimating the genetic contribution to intelligence. Decades of such research have shown that genetic similarity does contribute to intelligence test scores. Several important findings from this line of study are
summarized in Figure 9.12 (Plomin & Spinath, 2004). The most obvious trend in the figure shows that as the degree of genetic relatedness increases,
similarity in IQ scores also increases. The last two bars on the right of Figure 9.12 present perhaps the strongest evidence for a genetic basis for intelligence. The intelligence scores of identical twins correlate with each other at about .85 when they are raised in the same home, which is much higher than the correlation for fraternal twins. Even when identical twins are adopted and raised apart, their intelligence scores are still correlated at approximately .80—a very strong relationship. In fact, this is about the same correlation that researchers
find when individuals take the same intelligence test twice and are compared with themselves!
Figure 9.12 Intelligence and Genetic Relatedness Several types of comparisons reveal genetic contributions to intelligence
(Plomin & Spinath, 2004). Generally, the closer the biological relationship between people, the more similar their intelligence scores. Source: Adapted from Plomin, R., & Spinath, F. M. (2004). Intelligence: Genetics, genes, and genomics. Journal of
Personality & Social Psychology, 86 (1), 112–129.
The Heritability of Intelligence
Overall, the heritability of intelligence is estimated to be between 40% and 80%
(Nisbett et al., 2012). However, interpreting what this means is extremely tricky. People often think that this means 40% or more of a person’s intelligence is determined by genes. But this is a serious misunderstanding of heritability.
A heritability estimate describes how much of the differences between people in a sample can be accounted for by differences in their genes (see Module 3.1 ). This may not sound like a crucial distinction, but in fact it’s extremely
important! It means that a heritability estimate is not a single, fixed number;
instead, it is a number that depends on the sample of people being studied. Heritability estimates for different samples can be very different. For example, the heritability of intelligence for wealthy people has been estimated to be about
72%, but for people living in poverty, it’s only 10% (Turkheimer et al., 2003). Why might this be?
The key to solving this puzzle is to recognize that heritability estimates depend on other factors, such as how different or similar people’s environments are. If people in a sample inhabit highly similar environments, the heritability estimate will be higher, whereas if they inhabit highly diverse environments, the heritability estimate will be lower. Because most wealthy people have access to good nutrition, good schools, plenty of enrichment opportunities, and strong parental support for education, these factors contribute fairly equally to the intelligence of wealthy people; thus, differences in their intelligence scores are largely explained by genetic differences. But the environments inhabited by people living in poverty differ widely. Some may receive good schooling and others very little. Some may receive proper nutrition (e.g., poor farming families that grow their own food), whereas others may be chronically malnourished (e.g., children in poor inner-city neighbourhoods). For poorer families, these differences in the environment would impact intelligence (as we discuss later in this module), leading to lower heritability estimates.
There are many other problems with interpreting heritability estimates as
indications that genes cause differences in intelligence. Two of the most important both have to do with an under-appreciation for how genes interact with
the environment. First, as discussed in Module 3.1 , genes do not operate in isolation from the environment. We know now that the “nature vs. nurture” debate has evolved into a discussion of how “nurture shapes nature.” Environmental factors determine how genes express themselves and influence the organism.
Second, genes that influence intelligence may do so indirectly, operating through other factors. For example, imagine genes that promote novelty-seeking. People with these genes would be more likely to expose themselves to new ideas and
new ways of doing things. This tendency to explore, rooted in their genes, may lead them to become more intelligent. However, in more dangerous environments, these novelty-seeking genes could expose the person to more danger. Therefore, genes that encourage exploratory behaviour might be related to higher intelligence in relatively safe environments, but in dangerous environments might be related to getting eaten by cave-bears more often.
Behavioural Genomics
Twin and adoption studies show that some of the individual differences observed in intelligence scores can be attributed to genetic factors. But these studies do not tell us which genes account for the differences. To answer that question,
researchers use behavioural genomics, a technique that examines how specific genes interact with the environment to influence behaviours, including those related to intelligence. Thus far, the main focus of the behavioural genomics approach to intelligence is to identify genes that are related to cognitive abilities,
such as learning and problem solving (Deary et al., 2010).
Overall, studies scanning the whole human genome show that intelligence levels can be predicted, to some degree, by the collection of genes that individuals
inherit (Craig & Plomin, 2006; Plomin & Spinath, 2004). These collections of genes seem to pool together to influence general cognitive ability; although each contributes a small amount, the contributions combine to have a larger effect. However, although almost 300 individual genes have been found to have a large
impact on various forms of mental retardation (Inlow & Restifo, 2004), very few genes have been found to explain normal variation in intelligence (Butcher et al., 2008). In one large study that scanned the entire genome of 7000 people, researchers found a mere six genetic markers that predicted cognitive ability. Taken together, these six markers only explained 1% of the variability in
cognitive ability (Butcher et al., 2008). Thus, there is still a long way to go before we can say that we understand the genetic contributors to intelligence.
One way of speeding the research up has been to develop ways of
experimenting with genes directly, in order to see what they do. Gene knockout (KO) studies involve removing a specific gene and comparing the
characteristics of animals with and without that gene. In one of the first knockout studies of intelligence, researchers discovered that removing one particular gene
disrupted the ability of mice to learn spatial layouts (Silva et al., 1992). Since this investigation was completed, numerous studies using gene knockout methods have shown that specific genes are related to performance on tasks that have
been adapted to study learning and cognitive abilities in animals (Robinson et al., 2011).
Scientists can also take the opposite approach; instead of knocking genes out, they can insert genetic material into mouse chromosomes to study the changes associated with the new gene. The animal that receives this so-called gene
transplant is referred to as a transgenic animal. Although this approach may sound like science fiction, it has already yielded important discoveries, such as
transgenic mice that are better than average learners (Cao et al., 2007; Tang et al., 1999).
One now-famous example is the creation of “Doogie mice,” named after the 1990s TV character Doogie Howser (played by a young Neil Patrick Harris), a genius who became a medical doctor while still a teenager. Doogie mice were
created by manipulating a single gene, NR2B (Tang et al., 1999). This gene encodes the NMDA receptor, which plays a crucial role in learning and memory. Having more NMDA receptors should, therefore, allow organisms to retain more information (and possibly to access it more quickly). Consistent with this view, Doogie mice with altered NR2B genes learned significantly faster and had better memories than did other mice. For example, when the Doogie mice and normal mice were put into a tank of water in which they had to find a hidden platform in order to escape, the Doogie mice took half as many trials to remember how to get out of the tank.
The Princeton University lab mouse, Doogie, is able to learn faster than other mice thanks to a bit of genetic engineering. Researchers inserted a gene known as NR2B that helps create new synapses and leads to quicker learning. Princeton University/KRT/Newscom
The different types of studies reviewed in this section show us that genes do
have some effect on intelligence. What they don’t really show us is how these effects occur. What causes individual differences in intelligence? One theory suggests that these differences could be due to varying brain size.
Working the Scientific Literacy Model Brain Size and Intelligence
Are bigger brains more intelligent? We often assume that to be the case—think of the cartoon characters that are super- geniuses; they almost always have gigantic heads. Or think about what it means to call someone a “pea brain.” Psychologists have not been immune to this belief, and many studies have searched for a correlation between brain size and intelligence.
What do we know about brain size and intelligence?
Brain-based approaches to measuring intelligence rest on a common-sense assumption: Thinking occurs in the brain, so a larger brain should be related to greater intelligence. But does scientific evidence support this assumption? In the days before modern brain imaging was possible, researchers typically obtained skulls from deceased subjects, filled them with fine- grained matter such as metal pellets, and then transferred the pellets to a flask to measure the volume. These efforts taught us very little about intelligence and brain or skull size, but a lot about problems with measurement and racial prejudice. In some cases, the studies were highly flawed and inevitably led to conclusions that Caucasian males (including the Caucasian male scientists who conducted these experiments) had the largest brains and,
therefore, were the smartest of the human race (Gould, 1981). Modern approaches to studying the brain and intelligence are far more sophisticated, thanks to newer techniques and a more enlightened knowledge of the brain’s form and functions.
How can science explain the relationship between brain size and intelligence? In relatively rare cases, researchers have had the two most important pieces of data needed: brains, and people attached to those brains who had taken intelligence tests when they were
alive. In one ambitious study at McMaster University, Sandra Witelson and her colleagues (2006) collected 100 brains of deceased individuals who had previously completed the Wechsler Adult Intelligence Scale (WAIS). Detailed anatomical examinations and size measurements were made on the entire brains and certain regions that support cognitive skills. For women and right-handed men (but not left-handed men), 36% of the variation in verbal intelligence scores was accounted for by the size of the brain; however, brain size did not significantly account for the other component of intelligence that was measured, visuospatial abilities. Thus, it appears that brain size does predict intelligence, but certainly doesn’t tell the whole story.
In addition to the size of the brain and its various regions, there are other features of our neuroanatomy that might be important to consider. The most obvious, perhaps, is the convoluted surface of fissures and folds (called gyri; pronounced “ji-rye”) that
comprise the outer part of the cerebral cortex (see Figure 9.13 ). Interestingly, the number and size of these cerebral gyri seems strongly related to intelligence across different species; species that have complex cognitive and social lives, such as elephants, dolphins, and primates, have particularly convoluted
cortices (Marino, 2002; Rogers et al., 2010). And indeed, even within humans, careful studies using brain imaging technology have shown that having more convolutions on the surface of certain parts of the cortex was also positively correlated with scores on the WAIS intelligence test, accounting for
approximately 25% of the variability in WAIS scores (Luders et al., 2008).
Figure 9.13 Does Intelligence Increase with Brain Size?
While the size of the brain may have a modest relationship to intelligence, the convolutions or “gyri” along the surface of the cortex are another important factor: Increased convolutions are associated with higher intelligence test scores.
Can we critically evaluate this issue?
A common critique of studies examining brain size and IQ is that it is not always clear what processes or abilities are being tested. IQ scores could be measuring a number of things including working memory, processing speed, ability to pay attention, or even motivation to perform well on the test. Therefore, when studies show that brain size can account for 25% of the variability in IQ scores, it is not always clear what ability (or abilities) are underlying these results.
Another potential problem is the third-variable problem; even if brain size and performance on intelligence tests are correlated with each other, it might be the case that they are both related to some other factor, like stress, nutrition, physical health, environmental toxins, or the amount of enriching stimulation
experienced during childhood (Choi et al., 2008). If these other factors can account for the relationship between brain size and intelligence, then the brain–IQ relationship itself may be overestimated.
A final critique is simply the recognition that there is more to intelligence than just the size of one’s brain. After all, if brain size explains 25% of the variability in IQ scores, the other 75% must be due to other things.
Why is this relevant? This research is important for reasons that go far beyond the issue of intelligence and IQ tests. More generally, research on the neurology of intelligence has furthered our understanding of the relationship between brain structure and function, which are related to many important phenomena. For example, certain harmful patterns of behaviour, such as anorexia nervosa (a psychological disorder marked by self-starvation) or prolonged periods of alcohol abuse, both have been shown to lead to changes in cognitive abilities and corresponding loss of brain
volume (e.g., McCormick et al., 2008; Schottenbauer et al.,
2007). Measurements of brain volume have also played a key role in understanding the impaired neurological and cognitive development of children growing up in institutional settings (e.g., orphanages), as well as how these children benefit from
adoption, foster care, or increased social contact (Sheridan et al., 2012). Better understanding of how experiences like anorexia, alcoholism, and child neglect affect brain development may provide ways of developing effective interventions that could help people who have suffered from such experiences.
Module 9.3a Quiz:
Biological Influences on Intelligence
Know . . . 1. When scientists insert genetic material into an animal’s genome, the
result is called a . A. genomic animal B. transgenic animal C. knockout animal D. fraternal twin
Understand . . . 2. How do gene knockout studies help to identify the contribution of specific
genes to intelligence?
A. After removing or suppressing a portion of genetic material, scientists can look for changes in intelligence.
B. After inserting genetic material, scientists can see how intelligence has changed.
C. Scientists can rank animals in terms of intelligence and then see how the most intelligent animals differ genetically from the least intelligent.
D. They allow scientists to compare identical and fraternal twins.
Analyze . . . 3. Identical twins, whether reared together or apart, tend to score very
similarly on standardized measures of intelligence. Which of the following statements does this finding support?
A. Intelligence levels are based on environmental factors for both twins reared together and twins reared apart.
B. Environmental factors are stronger influences on twins raised together compared to twins reared apart.
C. The “intelligence gene” is identical in both twins reared together and reared apart.
D. Genes are an important source of individual variations in intelligence test scores.
Environmental Influences on Intelligence
As described earlier, research on the biological underpinnings of intelligence repeatedly emphasizes the importance of environmental factors. For example, environmental conditions determine which genes get expressed (“turned on”) for a given individual; thus, without the right circumstances, genes can’t appropriately affect the person’s development. Also, brain areas involved in intelligence are responsive to a wide variety of environmental factors. The full story of how “nature” influences intelligence is intricately bound up with the story of how “nurture” influences intelligence.
Both animal and human studies have demonstrated how environmental factors influence cognitive abilities. Controlled experiments with animals show that growing up in physically and socially stimulating environments results in faster learning and enhanced brain development compared to growing up in a dull
environment (Hebb, 1947; Tashiro et al., 2007). For example, classic studies in the 1960s showed that rats who grew up in enriched environments (i.e., these rats enjoyed toys, ladders, and tunnels) ended up with bigger brains than rats
who grew up in impoverished environments (i.e., simple wire cages). Not only
were their cerebral cortices approximately 5% larger (Diamond et al., 1964; Rosenzweig et al., 1962), but their cortices contained 25% more synapses (Diamond et al., 1964). With more synapses, the brain can make more associations, potentially enhancing cognitive abilities such as learning and creativity. In this section, we review some of the major environmental factors that influence intelligence.
Birth Order
One of the most hotly debated environmental factors affecting intelligence is simply whether you were the oldest child in your family, or whether you were lower in the pecking order of your siblings. Debate about this issue has raged for many decades within psychology. Regardless of the larger debate about why birth order might affect intelligence, the evidence seems to indicate that it does. For example, a 2007 study of more than 240 000 people in Norway found that the IQs of first-born children are, on average, about three points higher than those of second-born children and four points higher than those of third-born
children (Kristensen & Bjerkedal, 2007).
Socioeconomic status is related to intelligence. People from low-socioeconomic backgrounds typically have far fewer opportunities to access educational and other important resources that contribute to intellectual growth. John Dominis/Getty Images
Why might this be? The most important factor, researchers believe, is that older siblings, like it or not, end up tutoring and mentoring younger siblings, imparting
the wisdom they have gained through experience on to their younger siblings. Although this may help the younger sibling, the act of teaching their knowledge
benefits the older sibling more (Zajonc, 1976). The act of teaching requires the older sibling to rehearse previously remembered information and to reorganize it in a way that their younger sibling will understand. Teaching therefore leads to a deeper processing of the information, which, in turn, increases the likelihood that
it will be remembered later (see Module 7.2 ).
Before any first-born children reading this section start building monuments to their greatness, it is important to note that the differences between the IQs of first- and later-born siblings are quite small: three or four points. There will definitely be many individual families in which the later-born kids have higher IQs than their first-born siblings. Nevertheless, this finding is one example of how environments can influence intelligence.
Socioeconomic Status
One of the most robust findings in the intelligence literature is that IQ correlates strongly with socioeconomic status (SES). It is perhaps no surprise that children growing up in wealthy homes have, on average, higher IQs than those growing
up in poverty (Turkheimer et al., 2003), but there may be many reasons for this that have nothing to do with the “innate” or potential intelligence of the rich or the poor. Think of the many environmental differences and greater access to resources and opportunities enjoyed by the wealthy! For example, consider how much language children are exposed to at home; one U.S. study estimated that by age three, children of professional parents will have heard 30 million words, children of working-class parents will have heard only 20 million words, and children of unemployed African-American mothers will have heard only 10 million
words. Furthermore, the level of vocabulary is strikingly different for families in the different socioeconomic categories, with professional families using the most
sophisticated language (Hart & Risley, 1995).
Other studies have shown that higher SES homes are much more enriching and supportive of children’s intellectual development—high SES parents talk to their children more; have more books, magazines, and newspapers in the home; give
them more access to computers; take them to more learning experiences outside the home (e.g., visits to museums); and are less punitive toward their children
(Bradley et al., 1993; Phillips et al., 1998).
Unfortunately, the effects of SES don’t end here. SES interacts with a number of other factors that can influence intelligence, including nutrition, stress, and education. The difference between rich and poor people’s exposure to these factors almost certainly affects the IQ gap between the two groups.
Nutrition
It’s a cliché we are all familiar with—“you are what you eat.” Yet over the past century, the quality of the North American diet has plummeted as we have adopted foods that are highly processed, high in sugar and fat, low in fibre and nutrients, and laden with chemicals (preservatives, colours, and flavourings). Some evidence suggests that poor nutrition could have negative effects on intelligence. For example, research has shown that diets high in saturated fat quickly lead to sharp declines in cognitive functioning in both animal and human subjects. In contrast, diets low in such fats and high in fruits, vegetables, fish,
and whole grains are associated with higher cognitive functioning (Greenwood & Winocur, 2005; Parrott & Greenwood, 2007).
A massive longitudinal study on diet is currently underway in the United Kingdom. The Avon Longitudinal Study of Parents and Children is following the development of children born to 14 000 women in the early 1990s. This research has shown that a “poor” diet (high in fat, sugar, and processed foods) early in life leads to reliably lower IQ scores by age 8.5, whereas a “health-conscious” diet (emphasizing salads, rice, pastas, fish, and fruit) leads to higher IQs. Importantly, this was true even when researchers accounted for the effects of other variables,
such as socioeconomic status (Northstone et al., 2012).
So what kinds of foods should we eat to maximize our brainpower? Although research on nutrition and intelligence is still relatively new, it would appear that eating foods low in saturated fats and rich in omega-3 fats, whole grains, and fruits and veggies are your smartest bets.
Stress
High levels of stress in economically poor populations is also a major factor in explaining the rich–poor IQ gap. People living in poverty are exposed to high levels of stress through many converging factors, ranging from higher levels of environmental noise and toxins, to more family conflict and community violence, to less economic security and fewer employment opportunities. These and many other stresses increase the amounts of stress hormones such as cortisol in their
bodies, which in turn is related to poorer cognitive functioning (Evans & Schamberg, 2009). High levels of stress also interfere with working memory (the ability to hold multiple pieces of information in memory at one time; Evans & Schamberg, 2009), and the ability to persevere when faced with challenging tasks, such as difficult questions on an IQ test (Evans & Stecker, 2004). These deficits interfere with learning in school (Blair & Razza, 2007; Ferrer & McArdle, 2004).
The toxic effects of chronic stress show up in the brain as well, damaging the neural circuitry of the prefrontal cortex and hippocampus, which are critical for working memory and other cognitive abilities (e.g., controlling attention, cognitive flexibility) as well as for the consolidation and storage of long-term memories
(McEwen, 2000). In short, too much stress makes us not only less healthy, but can make us less intelligent as well.
Education
One of the great hopes of modern society has been that universal education would level the playing field, allowing all children, rich and poor alike, access to the resources necessary to achieve success. Certainly, attending school has
been shown to have a large impact on IQ scores (Ceci, 1991). During school, children accumulate factual knowledge, learn basic language and math skills, and learn skills related to scientific reasoning and problem solving. Children’s IQ
scores are significantly lower if they do not attend school (Ceci & Williams, 1997; Nisbett, 2009). In fact, for most children, IQ drops even over the months
of summer holiday (Ceci, 1991; Jencks et al., 1972), although the wealthiest 20% actually show gains in IQ over the summer, presumably because they enjoy activities that are even more enriching than the kinds of experiences delivered in
the classroom (Burkam et al., 2004; Cooper et al., 2000). However, although education has the potential to help erase the rich–poor gap in IQ, its effectiveness at doing so will depend on whether the rich and poor have equal access to the same quality of education and other support and resources that would allow them to make full use of educational opportunities.
Clearly, environmental factors such as nutrition, stress, and education all influence intelligence, which gives us some clues as to how society can contribute to improving the intelligence of the population. Interestingly, exactly such a trend has been widely observed across the last half-century or so; it appears that generation after generation, people are getting smarter!
The Flynn Effect: IS Everyone Getting Smarter?
The Flynn effect , named after researcher James Flynn, refers to the steady population level increases in intelligence test scores over time (Figure 9.14 ). This effect has been found in numerous situations across a number of countries. For example, in the Dutch and French militaries, IQ scores of new recruits rose dramatically between the 1950s and 1980s—21 points for the Dutch and about
30 for the French (Flynn, 1987). From 1932 to 2007, Flynn estimates that, in general, IQ scores rose about one point every three years (Flynn, 2007).
Figure 9.14 The Flynn Effect For decades, there has been a general trend toward increasing IQ scores. This trend, called the Flynn effect, has been occurring since standardized IQ tests have been administered. Source: Flynn, J. R. (1999). Searching for justice: The discovery of IQ gains over time. American Psychologist, 54, 5–20.
The magnitude of the Flynn effect is striking. In the Dutch study noted above, today’s group of 18-year-olds would score 35 points higher than 18-year-olds in 1950. The average person back then had an IQ of 100, but the average person today, taking the same test, would score 135, which is above the cut-off considered “gifted” in most gifted education programs! Or consider this the opposite way—if the average person today scored 100 on today’s test, the average person in 1950 would score about 65, enough to qualify as mentally disabled.
How can we explain this increase? Nobody knows for sure, but one of the most likely explanations is that modern society requires certain types of intellectual skills, such as abstract thinking, scientific reasoning, classification, and logical analysis. These have been increasingly emphasized since the Industrial
Revolution, and particularly since the information economy and advent of computers have restructured society over the past half-century or so. Each successive generation spends more time manipulating information with their minds; more time with visual media in the form of television, video games, and now the Internet; and more time in school. It seems reasonable to propose that
these shifts in information processing led to the increases in IQ scores (Nisbett et al., 2012).
Module 9.3b Quiz:
Environmental Influences on Intelligence
Understand . . . 1. What have controlled experiments with animals found in regard to the
effects of the environment on intelligence?
A. Stimulating environments result in faster learning and enhanced brain development.
B. Deprived environments result in faster learning and enhanced brain development.
C. Stimulating environments result in slower learning and poorer brain development.
D. Deprived environments have no effect on learning and brain development.
2. In which way have psychologists NOT studied the major environmental factors that, through their interaction with genes, influence intelligence?
A. By measuring stress hormones among poor and affluent children and correlating them with intelligence test scores
B. By depriving some children of education and comparing them to others who attended school
C. By measuring children’s nutrition and then correlating it with intelligence scores
D. By correlating children’s birth order in their family with intelligence scores
Analyze . . . 3. What effect does birth order have on intelligence scores? Why is this the
case?
A. Older children often have lower IQs than their siblings because their parents spend more time taking care of younger children.
B. Younger siblings often have higher IQs because their older siblings spent time teaching them new information and skills.
C. Younger siblings have lower IQs because they have had less time to learn information and skills.
D. Older children typically have slightly higher IQs, likely because they reinforce their knowledge by teaching younger siblings.
Behavioural Influences on Intelligence
If you want to make yourself more intelligent, we’ve covered a number of ways to do that—eat a brain-healthy diet, learn how to manage stress better, keep yourself educated (if not in formal schooling, then perhaps by continuing to be an active learner), and expose yourself to diverse and stimulating activities. But is there anything else you can do? For example, if you want bigger muscles, you can go to the gym and exercise. Can you do the same thing for the brain?
Brain Training Programs
One potential technique to improve intelligence is the use of “brain training” programs designed to improve working memory and other cognitive skills. The idea behind such programs is that playing games related to memory and attention will not only improve your performance on these games, but will also help you use those abilities in other, real-world situations.
Research in this area initially appeared quite promising. For instance, in one line of research, a computer task (the “N-back” task) was used as an exercise program for working memory. In this task, people are presented with a stimulus, such as squares that light up on a grid, and are asked to press a key if the
position on the grid is the same as the last trial. The task gets progressively more difficult, requiring participants to remember what happened two, three, or more trials ago (although it takes considerable practice for most people to be able to reliably remember what happened even three trials ago). Practising the N-back task was shown to not only improve performance at that task, but also to
increase participants’ fluid intelligence (Jaeggi et al., 2008). Importantly, the benefits were not merely short term, but lasted for at least three months (Jaeggi et al., 2011).
However, recent reviews of this area of research suggest that we should be cautious when interpreting the results (and media reports). Many studies of brain-training programs involved small sample sizes; other studies included
major methodological flaws such as a lack of a control group (Simons et al., 2016). A more careful examination of this research area suggests that the effects of brain-training programs are typically quite limited. Practising games related to working memory will improve working memory, but will rarely have an effect on other types of tasks, particularly on behaviours occurring outside of the
laboratory (Melby-Lervåg & Hulme, 2013). Although these results are disappointing—particularly for people who have spent money on expensive brain-training programs—they help remind us of the importance of being critical consumers of scientific information.
Nootropic Drugs
Another behaviour that many people believe improves their cognitive functioning
is the use of certain drugs. Nootropic substances (meaning “affecting the mind”) are substances that are believed to beneficially affect intelligence. Nootropics can work through many different mechanisms, from increasing overall arousal and alertness, to changing the availability of certain neurotransmitters, to stimulating nerve growth in the brain.
Certainly, these drugs can work for many people. For example, two drugs commonly used are methylphenidate (Ritalin) and modafinil (Provigil). Methylphenidate is a drug that inhibits the reuptake of norepinephrine and dopamine, thus leaving more of these neurotransmitters in the synapses
between cells. Although generally prescribed to help people with attentional disorders, Ritalin can also boost cognitive functioning in the general population
(Elliott et al., 1997). Modafinil, originally developed to treat narcolepsy (a sleep disorder), is known to boost short-term memory and planning abilities by
affecting the reuptake of dopamine (Turner et al., 2003).
Boosting the brain, however, does not come without risk. For example, the long- term effects of such drugs are poorly understood and potential side effects can be severe. There can also be dependency issues as people come to rely on such drugs and use them more regularly, and problems with providing unfair advantages to people willing to take such drugs, which puts pressure on others
to take them as well in order to stay competitive (Sahakian & Morein-Zamir, 2007). Because of these risks, a September 2013 review in the Canadian Medical Association Journal recommended that doctors “should seriously consider refusing to prescribe medications for cognitive enhancement to healthy
individuals” (Forlini et al., 2013, p. 1047).
These risks have to be weighed against the potential benefits of developing these drugs, at least for clinical populations. For example, researchers in the United Kingdom have argued that if nootropic drugs could improve the cognitive functioning of Alzheimer’s patients by even a small amount, such as a mere 1% change in the severity of the disease each year, this would be enough not only to dramatically improve the lives of people with Alzheimer’s and their families, but to completely erase the predicted increases in long-term health care costs for the
U.K.’s aging population (Sahakian & Morein-Zamir, 2007).
As with most questions concerning the ethical and optimally desirable uses of technologies, there are no easy answers when it comes to nootropic drugs. But we would caution you—there are much safer ways to increase your performance than ingesting substances that can affect your brain in unknown ways.
In sum, although few people are blessed with brains as abnormally intelligent as Einstein’s, there are practical things anyone can do to maximize their potential brainpower. From eating better to providing our brains with challenging exercises, we can use the science of intelligence to make the most out of our
genetic inheritance.
Module 9.3c Quiz:
Behavioural Influences on Intelligence
Know . . . 1. A commonly used nootropic drug is .
A. Tylenol B. Ecstasy C. Ritalin D. Lamictal
Understand . . . 2. Which of the following seems to be affected by brain-training tasks like
the N-back task?
A. Crystallized intelligence B. Fluid intelligence C. A person’s dominant learning style D. A person’s belief that they are more intelligent
Analyze . . . 3. Research on nootropic drugs shows that
A. they have a much larger effect on intelligence than do environmental factors such as socioeconomic status.
B. they show low addiction rates and are therefore quite safe. C. they have a larger effect on long-term memory than on working
memory.
D. these drugs can produce increases in intelligence in some individuals.
Module 9.3 Summary
9.3a Know . . . the key terminology related to heredity, environment, and intelligence.
Flynn effect
gene knockout (KO) studies
nootropic substances
video deficit
Behavioural genetics typically involves conducting twin or adoption studies. Behavioural genomics involves looking at gene–behaviour relationships at the molecular level. This approach often involves using animal models, including knockout and transgenic models.
Based on the research we reviewed, there are many different strategies that are good bets for enhancing the cognitive abilities that underlie your own intelligence. (Note: some of these strategies are known to be helpful for children, and the effects on adult intelligence are not well researched.)
Choose challenging activities and environments that are stimulating and enriching.
Eat diets low in saturated fat and processed foods and high in omega-3 fatty acids, nuts, seeds, fruits, and antioxidant-rich vegetables.
Reduce sources of stress and increase your ability to handle stress well. Remain an active learner by continually adding to your education or learning. Don’t spend too much time watching TV and other media that are relatively poor at challenging your cognitive abilities.
The use of nootropic drugs remains a potential strategy for enhancing your cognitive faculties; however, given the potential side effects, addictive
9.3b Understand . . . different approaches to studying the genetic basis of intelligence.
9.3c Apply . . . your knowledge of environmental and behavioural effects on intelligence to understand how to enhance your own cognitive abilities.
possibilities, and the uncertainty regarding the long-term consequences of using such drugs, this option may not be the best way to influence intelligence.
Reviews of intelligence tests show that the oldest child in a family tends to have higher IQs than their younger siblings. However, this effect is quite small: 3 IQ points. Importantly, this difference is not due to the genetic superiority of the older siblings; rather, it is likely related to the fact that older children often spend time teaching things to their younger siblings.
9.3d Analyze . . . the belief that older children are more intelligent than their younger siblings.
Chapter 10 Lifespan Development
10.1 Physical Development from Conception through Infancy Methods for Measuring Developmental Trends 387
Module 10.1a Quiz 388
Zygotes to Infants: From One Cell to Billions 388
Working the Scientific Literacy Model: The Long-Term Effects of Premature Birth 392
Module 10.1b Quiz 394
Sensory and Motor Development in Infancy 394
Module 10.1c Quiz 399
Module 10.1 Summary 399
10.2 Infancy and Childhood: Cognitive and Emotional Development Cognitive Changes: Piaget’s Cognitive Development Theory 401
Working the Scientific Literacy Model: Evaluating Piaget 404
Module 10.2a Quiz 406
Social Development, Attachment, and Self-Awareness 406
Module 10.2b Quiz 412
Psychosocial Development 412
Module 10.2c Quiz 415
Module 10.2 Summary 415
10.3 Adolescence Physical Changes in Adolescence 418
Module 10.3a Quiz 419
Emotional Challenges in Adolescence 419
Working the Scientific Literacy Model: Adolescent Risk and Decision Making 420
Module 10.3b Quiz 422
Cognitive Development: Moral Reasoning vs. Emotions 422
Module 10.3c Quiz 425
Social Development: Identity and Relationships 425
Module 10.3d Quiz 427
Module 10.3 Summary 427
10.4 Adulthood and Aging From Adolescence through Middle Age 429
Module 10.4a Quiz 433
Late Adulthood 433
Working the Scientific Literacy Model: Aging and Cognitive Change 436
Module 10.4b Quiz 437
Module 10.4 Summary 438
Module 10.1 Physical Development from Conception through Infancy
Leungchopan/Fotolia
Learning Objectives
Know . . . the key terminology related to prenatal and infant physical development. Understand . . . the pros and cons to different research designs in
10.1a
10.1b
It is difficult to overstate the sheer miracle and profundity of birth. Consider the following story, told by a new father. “About two days after the birth of my first child, I was driving to the hospital and had one of ‘those moments,’ an awe moment, when reality seems clear and wondrous. What triggered it was that the person driving down the highway in the car next to mine yawned. Suddenly, I remembered my newborn baby yawning just the day before, and somehow, it hit me—we are all just giant babies, all of us, the power broker in the business suit, the teenager in jeans and a hoodie, the tired soccer parent in the mini- van and the elderly couple holding hands on the sidewalk. Although we have invented these complex inner worlds for ourselves, with all of our cherished opinions, political beliefs, dreams, and aspirations, at our essence, we are giant babies. We have the same basic needs as babies —food, security, love, air, water. Our bodies are basically the same, only bigger. Our brains are basically the same, only substantially more developed. Our movements are even basically the same, just more coordinated. I like to remember that now and then, when I feel intimidated by someone, or when I feel too self-important. Just giant babies!”
Of course, we don’t stay “just babies” over our lives. We develop in many complex ways as we age and learn to function in the world. Understanding how we change, and how we stay the same, over the course of our lives, is what developmental psychology is all about.
Focus Questions
1. How does the brain develop, starting even before birth? 2. What factors can significantly harm or enhance babies’
neurological development?
developmental psychology. Apply . . . your understanding to identify the best ways expectant parents can ensure the health of their developing fetus. Analyze . . . the effects of preterm birth.
10.1c
10.1d
Developmental psychology is the study of human physical, cognitive, social, and behavioural characteristics across the lifespan. Take just about anything you have encountered so far in this text, and you will probably find psychologists approaching it from a developmental perspective. From neuroscientists to cultural psychologists, examining how we function and change across different stages of life raises many central and fascinating questions.
Methods for Measuring Developmental Trends
Studying development requires some special methods for measuring and
tracking change over time. A cross-sectional design is used to measure and compare samples of people at different ages at a given point in time. For example, to study cognition from infancy to adulthood, you could compare people of different age groups—say, groups of 1-, 5-, 10-, and 20-year-olds. In
contrast, a longitudinal design follows the development of the same set of individuals through time. With this type of study, you would select a sample of infants and measure their cognitive development periodically over the course of
20 years (see Figure 10.1 ).
Figure 10.1 Cross-Sectional and Longitudinal Methods In cross-sectional studies, different groups of people—typically of different ages —are compared at a single point in time. In longitudinal studies, the same group of subjects is tracked over multiple points in time.
These different methods have different strengths and weaknesses. Cross- sectional designs are relatively cheap and easy to administer, and they allow a study to be done quickly (because you don’t have to wait around while your
participants age). On the other hand, they can suffer from cohort effects , which are differences between people that result from being born in different time periods. For example, if you find differences between people born in the 2000s with those born in the 1970s, this may reflect any number of differences between people from those time periods—such as differences in technological advances, parenting norms, cultural changes, environmental pollutants, nutritional practices, or many other factors. This creates big problems in interpreting the findings of a study—do differences between the age groups reflect normal developmental processes or do they reflect more general differences between people born into these time periods?
A longitudinal study fixes the problem of cohort effects, but these studies are often difficult to carry out and tend to be costly and time consuming to follow, due to the logistic challenges involved in following a group of people for a long period
of time. Longitudinal designs often suffer from the problem of attrition, which occurs when participants drop out of a study for various reasons, such as losing interest or moving away.
The combination and accumulation of cross-sectional and longitudinal studies has taught us a great deal about the processes of human development. This can help parents and educators who want to have a positive influence on children’s development. It can help us understand how to better serve the needs of those who are aging. And it can help all of us, who just want to better understand who we are, and why we turned out the way that we did.
One quite famous example of a longitudinal study is the Seven-up series, which is a documentary and extensive longitudinal study of a group of people who started the study at age 7, more than 50 years ago. Watching the series is a fascinating look at how people retain basic features of their personality over pretty much their entire lifespan, whereas they also change as their circumstances take them down different paths in life. If you are interested, you can find this series online; search for “7 up,” “14 up,” etc., up to “56 up,” which was released in 2013.
Patterns of Development: Stages and Continuity
One of the challenges that has faced developmental psychologists is that human development does not unfold in a gradual, smooth, linear fashion; instead, periods of seeming stability are interrupted by sudden, often dramatic upheavals and shifts in functioning as a person transitions from one pattern of functioning to a qualitatively different one. This common pattern, relatively stable periods interspersed with periods of rapid reorganization, has been reflected in many
different stage models of human development. According to these models, specific stages of development can be described, differentiated by qualitatively different patterns of how people function. In between these stages, rapid shifts in thinking and behaving occur, leading to a new set of patterns that manifest as
the next stage. Stage models have played an important role in helping psychologists understand both continuity and change over time.
Module 10.1a Quiz:
Methods for Measuring Developmental Trends
Know . . . 1. Studies that examine factors in groups of people of different ages (e.g., a
group of 15–20 year-olds; a group of 35–40 year-olds; and a group of
75–80 year-olds), are employing a research design. A. cohort B. longitudinal C. cross-sectional D. stage-model
Apply . . . 2. A researcher has only one year to complete a study on a topic that spans
the entire range of childhood. To complete the study, she should use a
design. A. cohort B. longitudinal C. correlational D. cross-sectional
Analyze . . . 3. Which of the following is a factor that would be least likely to be a cohort
effect for a study on cognitive development in healthy people?
A. Differences in genes between individuals B. Differences in educational practices over time C. Changes in the legal drinking age D. Changes in prescription drug use
Zygotes to Infants: From One Cell to
Billions
The earliest stage of development begins at the moment of conception, when a single sperm (out of approximately 200 million that start the journey into the vagina), is able to find its way into the ovum (egg cell). At this moment, the ovum
releases a chemical that bars any other sperm from entering, and the nuclei of egg and sperm fuse, forming the zygote . Out of the mysterious formation of this single cell, the rest of our lives flow.
Fertilization and Gestation
The formation of the zygote through the fertilization of the ovum marks the
beginning of the germinal stage , the first phase of prenatal development, which spans from conception to two weeks. Shortly after it forms, the zygote begins dividing, first into two cells, then four, then eight, and so on. The zygote also travels down the fallopian tubes toward the uterus, where it becomes
implanted into the lining of the uterus (Table 10.1 ). The ball of cells, now called a blastocyst, splits into two groups. The inner group of cells develops into the fetus. The outer group of cells forms the placenta, which will pass oxygen, nutrients, and waste to and from the fetus.
Table 10.1 Phases of Prenatal Development
A summary of the stages of human prenatal development and some of the major events
at each.
GERMINAL: 0 TO 2 WEEKS
Major Events
Migration of the blastocyst from the fallopian tubes and its implantation in
the uterus. Cellular divisions take place that eventually lead to multiple
organ, nervous system, and skin tissues.
EMBRYONIC: 2 TO 8 WEEKS
Major Events
Stage in which basic cell layers become differentiated. Major structures
such as the head, heart, limbs, hands, and feet emerge. The embryo
attaches to the placenta, the structure that allows for the exchange of
oxygen and nutrients and the removal of wastes.
FETAL STAGE: 8 WEEKS TO BIRTH
Major Events
Brain development progresses as distinct regions take form. The
circulatory, respiratory, digestive, and other bodily systems develop. Sex
organs appear at around the third month of gestation.
Top: Doug Steley A/Alamy Stock Photo; centre: MedicalRF.com/Alamy Stock Photo; bottom: Claude Edelmann/Photo
Researchers, Inc./Science Source
The embryonic stage spans weeks two through eight, during which time the embryo begins developing major physical structures such as the heart and nervous system, as well as the beginnings of arms, legs, hands, and feet.
The fetal stage spans week eight through birth, during which time the skeletal, organ, and nervous systems become more developed and specialized. Muscles develop and the fetus begins to move. Sleeping and waking cycles start and the senses become fine-tuned—even to the point where the fetus is
responsive to external cues (these events are summarized in Table 10.1 ).
Fetal Brain Development
The beginnings of the human brain can be seen during the embryonic stage, between the second and third weeks of gestation, when some cells migrate to the appropriate locations and begin to differentiate into nerve cells. The first major development in the brain is the formation of the neural tube, which occurs only 2 weeks after conception. A layer of specialized cells begins to fold over onto itself, structurally differentiating between itself and the other cells. This tube-
shaped structure eventually develops into the brain and spinal cord (Lenroot & Gledd, 2007; O’Rahilly & Mueller, 2008). The first signs of the major divisions of the brain—the forebrain, the midbrain, and the hindbrain—are apparent at only
4 weeks (see Figure 10.2 ). Around 7 weeks, neurons and synapses develop in the spinal cord, giving rise to a new ability—movement; the fetus’s own movements then provide a new source of sensory information, which further stimulates the central nervous system’s development of increasingly coordinated
movements (Kurjak, Pooh, et al., 2005). By 11 weeks, differentiations between the cerebral hemisphere, the cerebellum, and the brain stem are apparent, and by the end of the second trimester, the outer surface of the cerebral cortex has started to fold into the distinctive gyri and sulci (ridges and folds) that give the outer cortex its wrinkled appearance. It is around the same time period that a fatty tissue called myelin begins to build up around developing nerve cells, a
process called myelination. Myelin is centrally important; by insulating nerve cells, it enables them to conduct messages more rapidly and efficiently (see Module 3.2 ; Giedd, 2008), thereby allowing for the large-scale functioning and integration of neural networks.
Figure 10.2 Fetal Brain Development The origins of the major regions of the brain are already detectable at four weeks’ gestation. Their differentiation progresses rapidly, with the major forebrain, midbrain, and hindbrain regions becoming increasingly specialized.
At birth, the newborn has an estimated 100 billion neurons and a brain that is approximately 25% the size and weight of an adult brain. Astonishingly, this means that at birth, the infant has created virtually all of the neurons that will
comprise the adult brain, growing up to 4000 new neurons per second in the womb (Brown et al., 2001). However, most of the connections between these
neurons have not yet been established in the brain of a newborn (Kolb, 1989, 1995). This gives us a key insight into one of our core human capacities—our ability to adapt to highly diverse environments. Although the basic shape and structure of our brains is guided by the human genome, the strength of the connections between brain regions is dependent upon experience.
The child’s brain has a vast number of synapses, far more than it will have as an adult in fact, which is why the child’s brain is so responsive to external input. The brain is learning, at a very basic level, what the world is like, and what it needs to be able to do in order to perceive and function effectively in the world. Children’s
brains have a very high amount of plasticity, so that whatever environments the child endures while growing up, her developing brain will be best able to learn to perceive and adapt to those environments. Our brains generally develop the patterns of biological organization that correspond to the world that we’ve experienced.
This means that in a deep and personal way, who we are depends on the environments that structure our brains. Ironically, this profound reliance upon the outside world is also the reason why human babies are so helpless (and make such bad Frisbee partners). We humans have relatively little pre-programmed into us and thus, we can do very little at birth relative to so many other animals. However, this seemingly profound weakness is offset by two huge, truly world- altering strengths: the incredible plasticity of our neurobiology, and the social support systems that keep us alive when we are very young. These advantages also give us the luxury of slowly developing over a long period of time. As a result, our increasingly complex neurobiological systems can learn to adapt and function effectively across a vast diversity of specific circumstances. The net result of this flexibility is that humans have been able to flourish in practically every ecosystem on the surface of the planet.
Nutrition, Teratogens, and Fetal Development
The rapidly developing fetal brain is highly vulnerable to environmental influences; for example, the quality of a pregnant woman’s diet can have a long- lasting impact on her child’s development. In fact, proper nutrition is the single
most important non-genetic factor affecting fetal development (aside from the
obvious need to avoid exposure to toxic substances; Phillips, 2006). The nutritional demands of a developing infant are such that women typically require an almost 20% increase in energy intake during pregnancy, including sufficient
quantities of protein (which affects neurological development; Morgane et al., 2002) and essential nutrients (especially omega-3 fatty acids, folic acid, zinc, calcium, and magnesium). Given that most people’s diets do not provide enough of these critical nutrients, supplements are generally considered to be a good
idea (Ramakrishnan et al., 1999).
Fetal malnutrition can have severe consequences, producing low-birth-weight babies who are more likely to suffer from a variety of diseases and illnesses, and are more likely to have cognitive deficits that can persist long after birth. Children who were malnourished in the womb are more likely to experience attention deficit disorders and difficulties controlling their emotions, due to underdeveloped
prefrontal cortices and other brain areas involved in self-control (Morgane et al., 2002). A wide variety of effects on mental health have been suggested; for example, one study showed that babies who were born in Holland during a
famine in World War II experienced a variety of physical problems (Stein et al., 1975) and had a much higher risk of developing psychological disorders, such as schizophrenia and antisocial personality disorder (Neugebauer et al., 1999; Susser et al., 1999).
Fetal development can also be disrupted through exposure to teratogens , substances, such as drugs or environmental toxins, that impair the process of development. One of the most famous and heartbreaking examples of teratogens was the use of thalidomide, a sedative that was hailed as a wonder drug for helping pregnant women deal with morning sickness during pregnancy. Available in Canada from 1959 to 1962, thalidomide was disastrous, causing miscarriages, severe birth defects such as blindness and deafness, plus its most
well-known effect, phocomelia, in which victims’ hands, feet, or both emerged directly from their shoulders or hips, functioning more like flippers than limbs;
indeed, phocomelia is taken from the Greek words phoke, which means “seal,” and melos, which means “limb” (www.thalidomide.ca/faq-en/#12). It is estimated that up to twenty thousand babies were born with disabilities as a
result of being exposed to thalidomide. In most countries, victims were able to secure financial support through class action lawsuits; however, in Canada, the government has steadfastly refused to provide much support to victims, who face ongoing severe challenges in their lives.
More common teratogens are alcohol and tobacco, although their effects differ widely depending on the volume consumed and the exact time when exposure
occurs during pregnancy. First described in the 1970s (Jones & Smith, 1973), fetal alcohol syndrome involves abnormalities in mental functioning, growth, and facial development in the offspring of women who use alcohol during pregnancy. This condition occurs in approximately 1 per 1000 births worldwide, but the specific rates likely vary greatly between regions, and little is known about specific regional variability. It also seems likely that FAS is underreported, and thus the effects of FAS may be far more widespread than is widely
recognized (Morleo et al., 2011).
This is particularly worrisome when one considers that research suggests there is no safe limit for alcohol consumption by a pregnant woman; even one drink
per day can be enough to cause impaired fetal development (O’Leary et al., 2010; Streissguth & Connor, 2001). Alcohol, like many other substances, readily passes through the placental membranes, leaving the developing fetus vulnerable to its effects, which include reduced mental functioning and
impulsivity (Olson et al., 1997; Streissguth et al., 1999). It is concerning, then, to acknowledge that about 1 in 10 pregnancies in Canada involve ingesting
alcohol (Walker et al., 2011), and in some communities, such as those in isolated Northern regions, more than 60% of pregnancies have been shown to
be alcohol-exposed (Muckle et al., 2011). Given that any amount of reduced drinking during pregnancy helps to reduce the risks of FAS, there is a clear role for public health and awareness campaigns, family and school efforts, and our own personal contributions to social norms, to tackle this together, and to eradicate, or at least minimize, alcohol consumption during pregnancy.
Victims of thalidomide; this sedative seemed like a miracle drug in the late 1950s, until its tragic effects on fetal development became apparent. Dpa picture alliance/Alamy Stock Photo
Fetal alcohol syndrome is diagnosed based on facial abnormalities, growth problems, and behavioural and cognitive deficits. Betty Udesen/KRT/Newscom
Smoking can also expose the developing fetus to teratogens, decreasing blood oxygen and raising concentrations of nicotine and carbon monoxide, as well as increasing the risk of miscarriage or death during infancy. Babies born to mothers who smoke are twice as likely to have low birth weight and have a 30% chance of premature birth—both factors that increase the newborn’s risk of illness or death. Evidence also suggests that smoking during pregnancy
increases the risk that the child will experience problems with emotional
development and impulse control (Brion et al., 2010; Wiebe et al., 2014), as well as attentional and other behavioural problems (Makin et al., 1991). These behavioural outcomes could be the outgrowth of impaired biological function; for example, there is evidence that prenatal exposure to nicotine interferes with the development of the serotonergic system, interfering with neurogenesis, and with
the expression of receptors that affect synaptic functioning (Hellström-Lindahl et al., 2001; Falk et al., 2005). Tobacco exposure may also interfere with the development of brain areas related to self-regulation (e.g., the prefrontal cortex), which then leads to poorer self-control and an increase in emotional and
behavioural problems over time (Marroun et al., 2014).
We must note, however, that there is an ongoing debate in the literature as to whether this is a causal relationship, or whether this is a third variable problem; in particular, there are a variety of familial risk factors (e.g., poverty, low parental education, etc.) that are related both to smoking during pregnancy and to the various developmental deficits that have been reported. Recent studies that attempted to statistically account for these third variable factors are somewhat inconclusive; some find very little direct relationship between maternal smoking during pregnancy and children’s development, whereas other report specific relationships that cannot be explained as being due to other variables. The jury is still out, but on the whole, researchers tentatively conclude that maternal smoking during pregnancy has a causal influence on various developmental
outcomes (Melchior et al., 2015; Palmer et al., 2016).
Smoking is implicated in other risk-factors for infants as well, perhaps most notably being the tragedy of sudden infant death syndrome (SIDS). Babies exposed to smoke are as much as three times more likely to die from SIDS
(Centers for Disease Control and Prevention [CDC], 2009a; Rogers, 2009). Even exposure to second-hand smoke during pregnancy carries similar risks
(Best, 2009). Thankfully, after major public health campaigns, the rate of SIDS has been declining substantially, dropping in Canada by 71% from 1981 to 2009
(Public Health Agency of Canada, 2014). These campaigns targeted three key behaviours: breastfeeding, putting infants to sleep on their backs (rather than their stomachs), and reducing smoking during pregnancy. To be fair, researchers
don’t know how much each of these individual behaviours have contributed to the reduction in SIDS. Researchers will continue trying to disentangle exactly what factors are related to reductions in rates of SIDS so that campaigns can even more effectively target the factors that make the biggest difference.
Clearly, teratogens exact a major cost on society, causing deficits that range from very specific (e.g., improperly formed limbs), to more general effects on development (e.g., premature birth causing overall low birth weight).
Working the Scientific Literacy Model The Long- Term Effects of Premature Birth
The human mother’s womb has evolved to be a close- to-ideal environment for a fetus’s delicate brain and body to prepare for life outside the womb. Premature birth thrusts the vulnerable baby into a much less congenial environment before she is ready; what effects does this have on development?
What do we know about premature birth? Typically, humans are born at a gestational age of around 40
weeks. Preterm infants are born earlier than 36 weeks. Premature babies often have underdeveloped brains and lungs, which present a host of immediate challenges, such as breathing on their own and maintaining an appropriate body temperature. With modern medical care, babies born at 30 weeks have a very good chance of surviving (approximately 95%), although for those born at 25 weeks, survival rates drop to only slightly above 50%
(Dani et al., 2009; Jones et al., 2005). Although babies born at less than 25 weeks often survive, they run a very high risk of damage to the brain and other major organs. To try to reduce these risks and improve outcomes as much as possible, medical science is continually seeking better procedures for nurturing preterm infants.
How can science be used to help preterm infants? Researchers and doctors have compared different methods for improving survival and normal development in preterm infants. One program, called the Newborn Individualized Developmental Care and Assessment Program (NIDCAP), is a behaviourally based intervention in which preterm infants are closely observed and given intensive care during early development. To keep the delicate brain protected against potentially harmful experiences, NIDCAP calls for minimal lights, sound levels, and stress.
Controlled studies suggest that this program works. Researchers randomly assigned 117 infants born at 29 weeks or less gestational age to receive either NIDCAP or standard care in a prenatal intensive care unit. Within 9 months of birth, the infants who received the NIDCAP care showed significantly improved motor skills, attention, and other behavioural skills, as well as
superior brain development (McAnulty et al., 2009). A longitudinal study indicates that these initial gains last for a long time. Even at eight years of age, those who were born preterm and given NIDCAP treatment scored higher on measures of thinking and problem solving, and also showed better frontal lobe functioning, than children who were born preterm but did not have
NIDCAP treatment (McAnulty et al., 2010).
Can we critically evaluate this research? The chief limitation of this longitudinal study is its small sample size (only 22 children across the two conditions). Such a small sample size presents problems from a statistical perspective, increasing the likelihood that random chance plays a substantial role in the results. Small samples also make it difficult to test the effects of interacting factors, such as whether the effectiveness of the program may depend on the child’s gender, on family socioeconomic status, ethnicity, or other factors. This study also
does not identify why the program works—what specific
mechanisms it affects that in turn improve development. It is not known which brain systems are beneficially affected by the program, or which aspects of the treatment itself are responsible for the effects. These remain questions for future research.
Kangaroo care—skin-to-skin contact between babies and caregivers— is now encouraged for promoting optimal infant development. Victoria Boland Photography/Flickr/ Getty Images
Why is this relevant? Worldwide, an estimated 9% of infants are born preterm (Villar et al., 2003). For these children, medical advances have increased the likelihood of survival, and behaviourally based interventions such as NIDCAP may reduce the chances of long-term negative effects of preterm birth. This fits with a growing literature on other behavioural interventions that have shown promise in improving outcomes for preterm infants. For example, massaging preterm infants for a mere 15 minutes per day can result in a 50% greater
daily weight gain (Field et al., 2006) and reduce stress-related behaviours (Hernandez-Reif et al., 2007). Another method called
kangaroo care focuses on promoting skin-to-skin contact between infants and caregivers, and encouraging breastfeeding. These practices have been shown to improve the physical and
psychological health of preterm infants (Conde-Agudelo et al., 2011), and are becoming widely adopted into mainstream medical practice.
The fact that teratogens can influence the development of the fetal brain—and in some cases lead to premature birth—has made (most) parents quite vigilant about these potential dangers. As you’ve read in this section, these concerns are well-founded. However, it is also important that parents examine the evidence for
each potential threat to see if it is credible. In Module 2.3 , we briefly discussed Andrew Wakefield, a British researcher who fabricated some of his data showing a link between vaccinations and autism. In that module, we focused on the ethical violations that he committed. The Myths in Mind box illustrates how this researcher’s lapse in ethics has had a profound effect on the health and safety of tens of thousands of innocent children.
Myths in Mind Vaccinations and Autism When you consider all the attention paid to developing better ways to promote healthy infant development, it is ironic and tragic that a surprising number of people actively avoid one of the key ways of preventing some of the most serious childhood illnesses—vaccination. A major controversy erupted in the late 1990s about a widely administered vaccine designed to prevent measles, mumps, and rubella (MMR). Research from one British lab linked the MMR vaccine to the development of autism, and even though the science was later discredited and the key researcher (Andrew Wakefield) lost his license to practise medicine, he continued to promote his views against vaccines through public speaking appearances and rallies, and the anti-vaccine movement remained convinced that vaccines were scarier than the diseases they prevented.
The net result has been a public health tragedy. For example, in Canada, measles was considered to have been eliminated as an endemic disease by 1997; any further cases would have to have been imported from other areas of the world. The United States followed shortly thereafter, eliminating measles by the year 2000, with less than 100 new cases imported into the country each year, which were easily dealt with because of large-scale immunity. However, as the anti-vaccine movement continued to proselytize its conspiracy theories about the medical establishment and pharmaceutical industries, these gains began to reverse. By 2011, more than 30 European countries, plus Canada and the U.S., saw huge spikes in measles cases, with worrying outbreaks
occurring in France, Quebec, and California (CDC 2015; Sherrard et al., 2015).
The take-home message? There is no evidence that vaccines cause autism. On the contrary, all the evidence suggests that vaccines prevent far more problems than they may cause.
Module 10.1b Quiz:
Zygotes to Infants: From One Cell to Billions
Know . . . 1. A developing human is called a(n) during the time between
weeks 2 and 8 of development.
A. embryo B. zygote C. fetus D. germinal
2. In which stage do the skeletal, organ, and nervous systems become more developed and specialized?
A. Embryonic stage B. Fetal stage
C. Germinal stage D. Gestational stage
Understand . . . 3. Which of the following would not qualify as a teratogen?
A. Cigarette smoke B. Alcohol C. Prescription drugs D. All of the above are possible teratogens
Analyze . . . 4. Which of the following statements best summarizes the effects of preterm
birth?
A. Preterm births are typically fatal. B. The worrisome effects of preterm birth are exaggerated. There is
little to worry about.
C. Preterm birth may cause physical and cognitive problems. D. Cohort effects make it impossible to answer this question.
Sensory and Motor Development in Infancy
Compared to the offspring of other species, healthy newborn humans have fairly limited abilities. Horses, snakes, deer, and many other organisms come into the world with a few basic skills, such as walking (or slithering), that enable them to move about the world, get food, and have at least a chance of evading predators. But human infants depend entirely on caregivers to keep them alive as they slowly develop their senses, strength, and coordination. In this section, we shift our focus to newborns to find out how movement and sensation develop in the first year of life.
It’s strange to think about what the world of an infant must be like. As adults, we Module 4.1
depend heavily on our top-down processes (see ) to help us label, categorize, perceive, and make sense of the world, but infants have developed very few top-down patterns when they are born. Their brains are pretty close to being “blank slates,” and life must be, as William James so aptly put it, a “blooming, buzzing confusion.”
However, babies aren’t quite as “blank” as we have historically assumed. In fact, they are even starting to perceive and make sense of their world while still in the womb. By month four of prenatal development, the brain starts receiving signals from the eyes and ears. By seven to eight months, not only can infants hear, they seem to be actually listening. This amazing finding comes from studies in which developing fetuses were exposed to certain stimuli, and then their preference for these stimuli was tested upon birth. In one study, mothers read
stories, including The Cat in the Hat, twice daily during the final six weeks of pregnancy. At birth, their babies were given a pacifier that controlled a tape recording of their mother’s voice reading different stories. Babies sucked the
pacifier much more to hear their mothers read The Cat in the Hat compared to hearing stories the moms had not read to them in the womb (DeCasper & Spence, 1986). Newborn babies also show a preference for their mother’s voice over other women’s voices. For example, a study involving researchers at Queen’s University showed that babies responded positively when they heard poems read by their mother, but not when the poems were read by a stranger
(Kisilevsky et al., 2003). (Unfortunately for fathers, babies up to at least 4 months old don’t prefer their dad’s voice over other men’s [DeCasper & Prescott, 1984; Ward & Cooper, 1999].)
The auditory patterning of babies’ brains is so significant that they have already started to internalize the sounds of their own native tongue, even before they are born. Recently, researchers analyzed the crying sounds of 60 babies born to either French or German parents and discovered that babies actually cry with an accent. The cries of French babies rose in intensity toward the end of their cry while German babies started at high intensity and then trailed off. This difference was apparent at only a few days of age and reflects the same sound patterns
characteristic of their respective languages (Mampe et al., 2009). So, babies are actively learning about their cultural environment even while in the womb.
The visual system is not as well developed at birth, however. Enthusiastic family members who stand around making goofy faces at a newborn baby are not really interacting with the child; newborns have only about 1/40th of the visual acuity of
adults (Sireteanu, 1999), and can only see about as far away as is necessary to see their mother’s face while breastfeeding (about 30 cm or less). It takes 6 months or more before they reach 20/20 visual acuity. Colour vision, depth perception, and shape discrimination all get a slow start as well. Colour discrimination happens at about 2 months of age, depth perception at 4 months, and it takes a full 8 months before infants can perceive shapes and objects about
as well as adults (Csibra et al., 2000; Fantz, 1961). Nevertheless, even newborns are highly responsive to visual cues if they’re close enough to see them. They will track moving objects, and will stare intently at objects they haven’t seen before, although after a while they habituate to an object and lose
interest in looking at it (Slater et al., 1988).
At just a few days of age, infants will imitate the facial expressions of others
(Meltzoff & Moore, 1977). From Meltzoff, A. N., & Moore, M. K. (1977). Imitation of facial and manual gestures by human neonates. Science, 198, 75–
78.
Babies’ visual responses to the world illustrate a major theme within psychology, which is that humans are fundamentally social creatures. By a few days of age,
newborns will imitate the facial expressions of others (Meltzoff & Moore, 1977). Newborns prefer to look at stimuli that look like faces, compared to stimuli that have all the same features but are scrambled so that they don’t look like faces
(see Figure 10.3 ). Infants also take longer to habituate to the face-like stimuli, suggesting that the human face holds particular importance even for newborns
(Johnson et al., 1991). This social attuning was dramatically illustrated in one study (Reissland, 1988), which showed that within one hour of birth, newborns begin to imitate facial expressions that they see!
Figure 10.3 Experimental Stimuli for Studying Visual Habituation in Infants Infants were shown three types of stimuli, a face-like stimulus, a neutral stimulus, and a scrambled-face stimulus.
Interestingly, the proper development of the visual system is not guaranteed to happen; it’s not hardwired into our genes. Instead, the visual system develops in response to the infant experiencing a world of diverse visual input. Research at McMaster University has shown that even though babies possess the necessary “equipment” for proper vision, this equipment needs to be exposed to a diverse
visual world in order to learn how to function effectively (Maurer et al., 1999); it is the patterns in the world which develop the appropriate neural pathways in the
visual cortex (see Module 4.2 ).
Although being exposed to a complex world is essential for the development of
the human visual system, interacting with this world is also necessary for the visual system to properly develop. This was illustrated by research involving an
ingenious device—the visual cliff. Originally, researchers in 1960 (Gibson & Walk, 1960) found that infants would be reluctant to crawl over the deep side, seeming to understand depth and danger right from birth. However, researchers eventually discovered that only babies who had some experience crawling
showed fear of the deep end (Campos et al., 1992).
In contrast to vision, the taste and olfactory systems are relatively well developed at birth. Similar to adults, newborns cringe when they smell something rotten or pungent (such as ammonia), and they show a strong preference for the taste of sweets. Odours are strong memory cues for infants as well. For example, infants can learn that a toy will work in the presence of one odour but not others, and
they can retain this memory over several days (Schroers et al., 2007). Newborn infants can also smell the difference between their mother’s breastmilk and that of a stranger. Infants even turn their heads toward the scent of breastmilk, which
helps to initiate nursing (Porter & Winberg, 1999).
The visual cliff. Mark Richard/PhotoEdit, Inc.
Motor Development in The First Year
Although the motor system takes many years to develop a high degree of coordination (good luck getting an infant to wield a steak knife), the beginnings of the motor system develop very early. A mere five months after conception, the fetus begins to have control of voluntary motor movements. In the last months of gestation, the muscles and nervous system are developed enough to
demonstrate basic reflexes —involuntary muscular reactions to specific types of stimulation. These reflexes provide newborns and infants with a set of innate responses for feeding and interacting with their caregivers (see Table 10.2 for a partial list of important infant reflexes). We evolved these reflexes because they help the infant survive (e.g., the rooting reflex helps the infant find and latch onto the breast; the grasping reflex helps the infant hold onto the caregiver, which was probably pretty important especially for our tree-dwelling ancestors), and they often begin the motor learning process that leads to the development of more complex motor skills (e.g., there is a stepping reflex that may help the infant learn to better sense and control her legs in order to support eventual walking behaviour).
Table 10.2 A Few Key Infant Reflexes
THE ROOTING REFLEX
Cathy Melloan
Resources/PhotoEdit,
Inc.
The rooting reflex is elicited by stimulation to the corners of the
mouth, which causes infants to orient themselves toward the
stimulation and make sucking motions. The rooting reflex helps the
infant begin feeding immediately after birth.
THE MORO REFLEX
The Moro reflex, also known as the “startle” reflex, occurs when
infants lose support of their head. Infants grimace and reach their
arms outward and then inward in a hugging motion. This may be a
Petit Format/Photo
Researchers,
Inc./Science Source
protective reflex that allows the infant to hold on to the mother when
support is suddenly lost.
THE GRASPING REFLEX
Denise
Hager/Catchlight
Visual
Services/Alamy Stock
Photo
The grasping reflex is elicited by stimulating the infant’s palm. The
infant’s grasp is remarkably strong and facilitates safely holding on
to one’s caregiver.
Interestingly, reflexes also provide important diagnostic information concerning the infant’s development. If the infant is developing normally, most of the primary, basic reflexes should disappear by the time the infant is about 6 months old, as the motor processes involved in these reflexes become integrated into the child’s developing neurology, in particular, the sensorimotor systems. The outcome of this integration is a pretty big deal—voluntary control over the body. Thus, if these reflexes persist longer than about six months, this may indicate
neural issues that may interfere with developing proper motor control (Volpe, 2008).
Over the first 12 to 18 months after birth, infants’ motor abilities progress through
fairly reliable stages—from crawling, to standing, to walking (see Figure 10.4 ). Although the majority of infants develop this way, there is still some variability; for example, some infants largely bypass the crawling stage, developing a kind of bum-sliding movement instead, and then proceed directly to standing and walking. The age at which infants can perform each of these movements differs from one individual to the next. In contrast to reflexes, the
development of motor skills seems to rely more on practice and deliberate effort, which in turn is related to environmental influences, such as cultural practices. For example, Jamaican mothers typically expect their babies to walk earlier than British or Indian mothers, and sure enough, Jamaican babies do walk earlier, likely because they are given more encouragement and opportunities to learn
(Hopkins & Westra, 1989; Zelazo et al., 1993).
Figure 10.4 Motor Skills Develop in Stages This series shows infants in different stages of development: (a) raising the head, (b) rolling over, (c) propping up, (d) sitting up, (e) crawling, and (f) walking. Top, left: bendao/Shutterstock; top, right: Bubbles Photolibrary/Alamy Stock Photo; bottom, left: imageBROKER/Glow
Images; bottom, centre left: OLJ Studio/Shutterstock; bottom, centre right: Corbis Bridge/Alamy Stock Photo; bottom, right:
Eric Gevaert/Shutterstock
One area of the body that undergoes astonishing development during infancy is the brain. Although the major brain structures are all present at birth, they continue developing right into adulthood. One key change is the myelination of
axons (see Module 3.2 ), which begins prenatally, accelerates through infancy and childhood, and then continues gradually for many years. Myelination is
centrally important for the proper development of the infant, and occurs in a reliable sequence, starting with tactile and kinesthetic systems (involving sensory and motor pathways), then moving to the vestibular, visual, and auditory systems
(Espenschade & Eckert, 1980;Deoni et al., 2011). Myelination of sensorimotor systems allows for the emergence of voluntary motor control (Espenschade & Eckert, 1980). By 12 months of age, the myelination of motoric pathways can be seen in the infant’s newfound abilities to stand and balance, begin walking, and gain voluntary control over the pincer grasp (pressing the forefinger and thumb together).
Two other neural processes, synaptogenesis and synaptic pruning, further help
to coordinate the functioning of the developing brain. Synaptogenesis
describes the forming of new synaptic connections, which occurs at blinding speed through infancy and childhood and continues through the lifespan. Synaptic pruning , the loss of weak nerve cell connections, accelerates during brain development through infancy and childhood (Figure 10.5 ), then tapers off until adolescence (see Module 10.3 ). Synaptogenesis and synaptic pruning serve to increase neural efficiency by strengthening needed connections between nerve cells and weeding out unnecessary ones.
Figure 10.5 The Processes of Synaptic Pruning
In summary, the journey from zygote to you begins dramatically, with biological
pathways being formed at a breakneck pace both prenatally and after birth, giving rise to sensory and motor abilities that allow infants to become competent perceivers and actors in the external world. Most motor abilities require substantial time for infants to learn to coordinate the many different muscles involved, which depends heavily on infants’ interactions with the environment. From the very beginnings of our lives, nature and nurture are inextricably intertwined.
Module 10.1c Quiz:
Sensory and Motor Development in Infancy
Know . . . 1. Three processes account for the main ways in which the brain develops
after birth. These three processes are
A. myelination, synaptogenesis, and synaptic pruning. B. myelination, synaptic reorganization, and increased
neurotransmitter production.
C. synaptogenesis, synaptic pruning, and increased neurotransmitter production.
D. cell growth, myelination, and synaptic organization.
Understand . . . 2. The development of infant motor skills is best described as
A. a genetic process with no environmental influence. B. completely due to the effects of encouragement. C. a mixture of biological maturation and learning. D. progressing in continuous, rather than stage, fashion.
Module 10.1 Summary
cohort effect
Know . . . the key terminology related to prenatal and infant physical development.
10.1a
cross-sectional design
developmental psychology
embryonic stage
fetal alcohol syndrome
fetal stage
germinal stage
longitudinal design
preterm infant
reflexes
synaptic pruning
synaptogenesis
teratogen
zygote
Cross-sectional designs, in which a researcher studies a sample of people at one time, have the advantage of being faster, and generally cheaper, allowing research to be completed quickly; however, they may suffer from cohort effects because people of different ages in the sample are also from somewhat different historical time periods and, thus, any differences between them could reflect a historical process and not a developmental one. Longitudinal designs, in which a researcher follows a sample of people over a span of time, have the advantage of being able to track changes in the same people, thus giving more direct insight into developmental processes. However, such studies take longer to complete, thus slowing down the research process, and they can suffer from attrition, in which people drop out of the study over time.
Understand . . . the pros and cons to different research designs in developmental psychology.
10.1b
The key to healthy fetal development is ensuring a chemically ideal environment. The most important factors are adequate nutrition and avoiding teratogens. Best nutritional practices include approximately a 20% increase in the mother’s caloric intake, additional protein, and ensuring sufficient quantities of essential nutrients (which usually involves taking nutritional supplements). Avoiding teratogens involves giving up smoking and drinking alcohol, and getting good medical advice concerning any medications that the expectant mother may be taking.
Health risks increase considerably with very premature births (e.g., those occurring at just 25 weeks’ gestation). Use of proper caregiving procedures, especially personalized care that emphasizes mother–infant contact, breastfeeding, and minimal sensory stimulation for the underdeveloped brain, increases the chances that preterm infants will remain healthy.
Apply . . . your understanding to identify the best ways expectant parents can ensure the health of their developing fetus.
10.1c
Analyze . . . the effects of preterm birth.10.1d
Module 10.2 Infancy and Childhood: Cognitive and Emotional Development
Getty Images
Learning Objectives
Know . . . the terminology associated with infancy and childhood. Understand . . . the cognitive changes that occur during infancy and childhood.
10.2a 10.2b
Many parents have turned to Disney’s Baby Einstein line of books, toys, and DVDs in hopes of entertaining and enriching their children. These materials certainly are entertaining enough that children watch them. But do they work? Do these products actually increase cognitive skills? The advertising pitch is certainly persuasive, arguing that these products were designed to help babies explore music, art, language, science, poetry, and nature through engaging images, characters, and music. How could that be bad? However, the American Academy of Pediatrics recommends that children younger than two years should not watch television at all, based on research showing that memory and language skills are slower
to develop in infants who regularly watch television (Christakis, 2009). Further, research specifically on Baby Einstein videos has shown that
they have no effect on vocabulary development (Richert et al., 2010; Robb et al., 2009). Instead of watching commercial programs on electronic screens, reading with caregivers turns out to be related to greater vocabulary comprehension and production. Thus, using the “electronic babysitter” might be justifiable in order to give parents a break or let them get some things done, but caregivers shouldn’t fool themselves into thinking that it’s actually promoting their children’s development.
Focus Questions
1. Which types of activities do infants and young children need for their psychological development?
2. Why are social interactions so important for healthy
Understand . . . the importance of attachment and the different styles of attachment. Apply . . . the concept of scaffolding and the zone of proximal development to understand how to best promote learning. Analyze . . . how to effectively discipline children in order to promote moral behaviour.
10.2c
10.2d
10.2e
development?
The transition from baby to toddler is perhaps the most biologically and behaviourally dramatic time in people’s lives. It is a mere year or two during which we grow from highly incapable, drooling babies, to highly coordinated and capable children. The physical, cognitive, and social transitions that occur between infancy and childhood are remarkably ordered, yet are also influenced by individual genetic and sociocultural factors. In this module, we integrate some important stage perspectives to explain psychological development through childhood.
One key insight to emerge from several lines of research is that for many systems, certain periods of development seem to be exceptionally important for
long-term functioning. A sensitive period is a window of time during which exposure to a specific type of environmental stimulation is needed for normal development of a specific ability. For example, to become fluent in language, infants need to be exposed to speech during their first few years of life. Long- term deficits can emerge if the needed stimulation, such as language, is missing during a sensitive period. Sensitive periods of development are a widespread phenomenon. They have been found in humans and other species for abilities such as depth perception, balance, recognition of parents and, in humans at
least, identifying with a particular culture (Cheung et al., 2011). However, although sensitive periods can explain the emergence of many perceptual (and some cognitive) abilities, they are only one of many mechanisms underlying human development.
Over the past century, many psychologists have attempted to explain how children’s mental abilities develop and expand. One of the most influential figures in this search was a Swiss psychologist named Jean Piaget (1896–1980).
Cognitive Changes: Piaget’s Cognitive Development Theory
Jean Piaget developed many of his theories in an unorthodox manner: he studied his own family. However, this was not done in a casual manner. Piaget actively studied, made copious notes of his observations, and even ran specific tests and measurements on his own children as they were growing up. The theories that resulted from this extensive personal project laid much of the
groundwork for the modern science of cognitive development —the study of changes in memory, thought, and reasoning processes that occur throughout the lifespan. In his own work, Piaget focused on cognitive development from infancy through early adolescence.
Piaget’s central interest was in explaining how children learn to think and reason. According to Piaget, learning is all about accumulating and modifying knowledge, which involves two central processes that he called assimilation and
accommodation. Assimilation is fitting new information into the belief system one already possesses. For example, young children may think that all girls have long hair and, as they encounter more examples of this pattern, they will assimilate them into their current understanding. Of course, eventually they will to run into girls with short hair or boys with long hair, and their beliefs will be challenged by this information. They may, at first, misunderstand, assuming a short-haired girl is actually a boy and a long-haired boy is actually a girl. But over time they will learn that their rigid categories of long-haired girl and short-haired
boy need to be altered. This is called accommodation , a creative process whereby people modify their belief structures based on experience. Our belief systems help us make sense of the world (assimilation), but as we encounter information that challenges our beliefs, we develop a more complex understanding of the world (accommodation). Deeply understanding assimilation and accommodation gets right to the heart of how to help people learn new things, as well as why people so often resist new information and may vigorously hold on to their beliefs.
Based on his observations of his children, Piaget concluded that cognitive
development passes through four distinct stages from birth through early adolescence: the sensorimotor, preoperational, concrete operational, and formal operational stages. Passing out of one stage and into the next occurs when the
child achieves the important developmental milestone of that stage (see Table 10.3 ).
Table 10.3 Piaget’s Stages of Cognitive Development
Stage Description
Sensorimotor
(0–2 years)
Cognitive experience is based on direct sensory experience with the
world, as well as motor movements that allow infants to interact with
the world. Object permanence is the significant developmental
milestone of this stage.
Preoperational
(2–7 years)
Thinking moves beyond the immediate appearance of objects. The
child understands physical conservation and that symbols, language,
and drawings can be used to represent ideas.
Concrete
operational
(7–11 years)
The ability to perform mental transformations on objects that are
physically present emerges. Thinking becomes logical and
organized.
Formal
operational
(11 years–
adulthood)
The capacity for abstract and hypothetical thinking develops.
Scientific reasoning becomes possible.
The Sensorimotor Stage: Living in The Material
World
The earliest period of cognitive development is known as the sensorimotor stage ; this stage spans from birth to two years, during which infants’ thinking about and exploration of the world are based on immediate sensory (e.g., seeing, feeling) and motor (e.g., grabbing, mouthing) experiences. During this time, infants are completely immersed in the present moment, responding
exclusively to direct sensory input. As soon as an object is out of sight and out of reach, it will cease to exist (at least in the minds of young infants): Out of sight, out of mind.
This is obviously not how the world works. Thus, the first major milestone of
cognitive development proposed by Piaget is object permanence , the ability to understand that objects exist even when they cannot be directly perceived. To test for object permanence, Piaget would allow an infant to reach for a toy, and then place a screen or a barrier between the infant and the toy so that the toy was no longer visible to the infant. If the reaching or looking stopped, it would suggest that the infant did not have a mental representation of the object when it was not visible. This would indicate that the infant had not yet developed object permanence.
Object permanence is tested by examining reactions that infants have to objects when they cannot be seen. Children who have object permanence will attempt to reach around the barrier or will continue looking in the direction of the desired object. Doug Goodman/Photo Researchers, Inc./ Science Source
Notice that this is not a problem for a two-year-old child. He can be very aware that his favourite toy awaits him in another room while he has to sit at the dinner table; in fact, he might not be able to get the toy out of his mind, and may take revenge on the evil tyrants who won’t get it for him by screaming throughout the meal.
The Preoperational Stage: Quantity and Numbers
According to Piaget, once children have mastered sensorimotor tasks, they have
progressed to the preoperational stage (ages two to seven). This stage is devoted to language development, the use of symbols, pretend play, and mastering the concept of conservation (discussed below). During this stage, children can think about physical objects, although they have not quite attained abstract thinking abilities. They may count objects and use numbers, yet they cannot mentally manipulate information or see things from other points of view.
This inability to manipulate abstract information is shown by testing a child’s
understanding of conservation , the knowledge that the quantity or amount of an object is not the same as the physical arrangement and appearance of that object. Conservation can be tested in a number of ways (see Figure 10.6 ). For example, in a conservation of liquid task, a child is shown two identical glasses, each containing the same amount of liquid. The researcher then pours the liquid from one glass into a differently shaped container, typically one that is taller and narrower. Although the amount of liquid is still the same, many children believe that the tall, thin glass contains more fluid because it looks “bigger” (i.e.,
taller). The conservation of number task produces similar effects. In this task, a child is presented with two identical rows of seven pennies each (see the bottom
part of Figure 10.6 ). The experimenter then spreads out one of the rows so that it is longer, but still has the same number of coins. If you ask the child, “Which row has more?” a three-year-old would likely point to the row that was spread out because a child in the preoperational stage focuses on the simpler method of answering based on immediate perception, instead of applying more sophisticated mental operations (such as counting the pennies).
Figure 10.6 Testing Conservation A child views two equal amounts of fluid, one of which is then poured into a taller, narrower container. Children who do not yet understand conservation believe that there is more fluid in the tall container compared to the shorter one. A similar version of this task can be tested using equal arrays of separate objects. Source: Lilienfeld, Scott O.; Lynn, Steven J; Namy, Laura L.; Woolf, Nancy J., Psychology: From Inquiry To Understanding,
2nd Ed., ©2011. Reprinted and Electronically reproduced by permission of Pearson Education, Inc., New York, NY.
Although tests of conservation provide compelling demonstrations of the limits of children’s cognitive abilities, Piaget’s conclusions were not universally accepted. Some researchers have challenged Piaget’s pessimism about the abilities of young children, arguing that their inability to perform certain tasks was a function of the child’s interpretation of the task, not their underlying cognitive limitations (see the Working the Scientific Literacy Model feature). For example, when three-year-old children are presented with the pennies conservation task described above, but M&Ms are substituted for the pennies, everything changes.
All of a sudden, children exhibit much more sophisticated thinking. If you put more M&Ms tightly packed together so they take up less space than a line of M&Ms that is more spread out, children will pick the more tightly packed but “smaller” row, understanding that it contains more candy—especially if they get
to eat the candy from the row they choose (Mehler & Bever, 1967).
In fact, even before children start to use and understand numbers, they acquire a basic understanding of quantity. Very soon after they are born, infants appear to
understand what it means to have less or more of something. This suggests that the infants who chose the longer row of pennies in the example above may simply have misunderstood the question, not the underlying rule of conservation.
To them, more could simply have meant longer.
Although Piaget clearly underestimated the cognitive abilities of young children,
researchers have identified common errors that very young children make but older children typically do not make. The children in Figure 10.7 are committing scale errors in the sense that they appear to interact with a doll-sized slide and a toy car as if they were the real thing, rather than miniatures
(DeLoache et al., 2004). By 2 to 2½ years of age, scale errors decline as children begin to understand properties of objects and how they are related. This understanding is one of many advances children make as they progress toward more abstract thinking.
Figure 10.7 Scale Errors and Testing for Scale Model Comprehension The children in photos (a) and (b) are making scale errors. One child is attempting to slide down a toy slide and another is attempting to enter a toy car. Three-year-olds understand that a scale model represents an actual room (c). The adult pictured is using a scale model to indicate the location of a hidden object in an actual room of this type. At around 3 years of age, children understand that the scale model symbolizes an actual room and will go directly to the hidden object after viewing the scale model. Courtesy of Judy DeLoache
At around 3 years of age children begin to understand symbolic information. For example, 3-year-olds understand that a scale model of a room can symbolize an
actual room (Figure 10.7 ). Children who view an experimenter placing a
miniature toy within the scale model will quickly locate the actual toy when
allowed to enter the room symbolized by the scale model (DeLoache, 1995). Abilities such as this are precursors to more advanced abilities of mental abstraction.
The Concrete Operational Stage: Using Logical
Thought
Conservation is one of the main skills marking the transition from the
preoperational stage to the concrete operational stage (ages 7 to 11 years), when children develop skills in logical thinking and manipulating numbers. Children in the concrete operational stage are able to classify objects according to properties such as size, value, shape, or some other physical characteristic. Their thinking becomes increasingly logical and organized. For example, a child in the concrete operational stage recognizes that if X is more than Y, and Y is
more than Z, then X is more than Z (a property called transitivity). This ability to think logically about physical objects sets the stage for them to think logically about abstractions in the fourth and final stage of cognitive development.
The Formal Operational Stage: Abstract and
Hypothetical Thought
The formal operational stage (ages 11 to adulthood) involves the development of advanced cognitive processes such as abstract reasoning and hypothetical thinking. Scientific thinking, such as gathering evidence and systematically testing possibilities, is characteristic of this stage.
Working the Scientific Literacy Model Evaluating Piaget
Piaget was immensely successful in opening our eyes to the
cognitive development of infants and children. Nevertheless, advances in testing methods have shown that he may have underestimated some aspects of infant cognitive abilities. In fact, infants appear to understand some basic principles of their physical and social worlds very shortly after birth.
What do we know about cognitive abilities in infants?
The core knowledge hypothesis proposes that infants have inborn abilities for understanding some key aspects of their environment (Spelke & Kinzler, 2007). It is a bold claim to say that babies know something about the world before they have even experienced it, so we should closely examine the evidence for this hypothesis.
How can we know what infants know or what they perceive? One frequently used method for answering this question relies on the
habituation–dishabituation response. Habituation refers to a decrease in responding with repeated exposure to an event. For example, if an infant is shown the same stimulus over and over, she will stop looking at it. Conversely, infants are quite responsive to novelty or changes in their environment. Thus, if the stimulus suddenly changes, the infant will display dishabituation , an increase in responsiveness with the presentation of a new stimulus. In other words, the infant will return her gaze to the location that she previously found boring. Research on habituation and dishabituation in infants led to the development of measurement techniques based on what infants will look at and for how long. These techniques now allow researchers to test infants even younger than Piaget was able to.
A popular method for testing infant cognitive abilities is to measure the amount of time infants look at stimuli. Researchers measure habituation and dishabituation to infer what infants understand. Lawrence Migdale/ Photo Researchers, Inc./Science Source
How can science help explain infant cognitive abilities? Measurement techniques based on what infants look at have been used to measure whether infants understand many different concepts, including abstract numbers—an ability that most people imagine appears much later in development. For example, Elizabeth Spelke and colleagues conducted a study in which 16
infants just two days old were shown sets of either 4 or 12 identical small shapes (e.g., yellow triangles, purple circles) on a video screen. The researchers also made a sound 4 or 12 times (e.g., tu-tu-tu-tu or ra-ra-ra-ra-ra-ra-ra-ra-ra-ra-ra-ra) at the same
time they showed the shapes (see Figure 10.8 ). Researchers varied whether the number of shapes the infants saw matched the number of tones they heard (e.g., 4 yellow triangles and 4 “ra” tones), or not (e.g., 4 purple circles and 12 “ra” tones). The infants were most attentive when what they saw and heard matched. In other words, they looked longer at the shapes when the number of shapes matched the number of sounds, compared to when they did not match; this is taken as evidence that even very young infants have a rudimentary appreciation for abstract
numbers (Izard et al., 2009).
Figure 10.8 Testing Infants’ Understanding of Quantity
In this study, infants listened to tones that were repeated either 4 or 12 times while they looked at objects that had either 4 or 12 components. Infants spent more time looking at visual arrays when the number of items they saw matched the number of tones they heard. Source: Figure 1 from “Newborn Infants Perceive Abstract Numbers” by V. Izard, C. Spann, E. S.
Spelke, & A. Streri (2009), Proceedings of the National Academy of Sciences, 106, 10382–10385.
Copyright © 2009. Reprinted by permission of PNAS.
Can we critically evaluate this research? Many of the studies of early cognitive development discussed in this module used the “looking time” procedure, although not all psychologists agree that it is an ideal way of determining what
infants understand or perceive (Aslin, 2007; Rivera et al., 1999). We cannot know exactly what infants are thinking, and perhaps they look longer at events and stimuli simply because these are more interesting rather than because they understand anything in particular about them. Inferring mental states that participants cannot themselves validate certainly leaves room for alternative explanations.
Also, the sample sizes in these studies are often fairly small, due to the cost and complexity of researching infants. In the study of shapes and tones just described, only 16 infants managed to complete the study. Forty-five others were too fussy or sleepy to successfully finish the task.
Why is this relevant? The key insight provided by this research is that cognitive development in young infants is much more sophisticated than psychologists previously assumed. With each study that examines the cognitive capacities of infants, we learn that infants are not just slobbery blobs that need to be fed and diapered— though it certainly can feel that way when you are a new parent. Now we are learning that infants can understand more than we might expect, and can reason in more complex ways than we had believed.
One thing that parents and caregivers can learn from this research is to see their children as complex learners who use sensation and movement to develop their emerging cognitive abilities. Caregivers can encourage this process by talking to them using diverse vocabulary, exploring rhythm and music, allowing them to feel different objects, and exposing them to different textures and sensations.
Piaget’s theories have had a lasting impact on modern developmental psychology. In addition to providing insights into the minds of young children, Piaget’s work inspired numerous other researchers to study cognitive development. Many of these new discoveries complement, rather than entirely contradict, Piaget’s foundational work.
Complementary Approaches to Piaget
In the many decades since Piaget’s work, psychologists have explored how children’s social contexts affect their cognitive development. For example, in a learning context, other people can support and facilitate children’s learning, or can make it more difficult. Children who try to master a skill by themselves may run into obstacles that would be easier to overcome with a little assistance or guidance from another person, or they may give up on a task when a little encouragement could have given them the boost needed to persevere and succeed. At the opposite extreme, children who have everything done for them and who are not allowed to work through problems themselves may become relatively incapable of finding solutions on their own, and may not develop feelings of competence that support striving for goals and overcoming challenges. Therefore, it seems reasonable to expect that optimal development will occur somewhere between the extremes of children doing everything on their own without any support, versus having others over-involved in their activities.
Russian psychologist Lev Vygotsky (1978) proposed that development is ideal when children attempt skills and activities that are just beyond what they can do alone, but they have guidance from adults who are attentive to their progress; this concept is termed the zone of proximal development (Singer & Goldin-Meadow, 2005). Teaching in order to keep children in the zone of proximal development is called scaffolding , a highly attentive approach to teaching in which the teacher matches guidance to the learner’s needs.
Cross-cultural research on parent–infant interactions shows that scaffolding is
exercised in different ways (Rogoff et al., 1993). For example, in one study, 12- to 24-month-old children were offered a toy that required pulling a string to make it move. Parents from Turkey, Guatemala, and the United States were observed interacting with their infants as they attempted to figure out how the toy worked. All parents used scaffolding when they spoke and gestured to their children to encourage them to pull the string, but mother–child pairs from Guatemala were much more communicative with each other, both verbally and through gestures such as touching and using the direction of their gaze to encourage the behaviour. Over time, this kind of sensitive scaffolding should result in children
who are more seamlessly integrated into the daily life of the family and community, rather than merely relegated to “play” activities in specialized “kid- friendly” environments. This means that children who are appropriately scaffolded are able to be useful and self-sufficient at much earlier ages than is normal in contemporary North American society. This kind of scaffolding approach to everyday life tasks is one of the foundational practices in many alternative education systems, such as the Montessori system.
Caregivers who are attentive to the learning and abilities of a developing child provide scaffolding for cognitive development. Nolte Lourens/Shutterstock
Module 10.2a Quiz:
Cognitive Changes: Piaget’s Cognitive Development Theory
Know . . . 1. Recognizing that the quantity of an object does not change despite
changes in its physical arrangement or appearance is referred to as
. A. object permanence B. scale comprehension
C. conservation D. number sense
2. Parents who attend to their children’s psychological abilities and guide them through the learning process are using .
A. scaffolding B. tutoring C. core knowledge D. the zone of proximal development
3. What is the correct order of Piaget’s stages of cognitive development? A. Preoperational, sensorimotor, concrete operational, formal
operational
B. Sensorimotor, preoperational, formal operational, concrete operational
C. Sensorimotor, preoperational, concrete operational, formal operational
D. Preoperational, concrete operational, sensorimotor, formal operational
Apply . . . 4. A child in the sensorimotor stage may quit looking or reaching for a toy if
you move it out of sight. This behaviour reflects the fact that the child has
not developed . A. core knowledge B. object permanence C. conservation D. to the preoperational stage
Analyze . . . 5. Research on newborns indicates that they have a sense of number and
quantity. What does this finding suggest about Piaget’s theory of cognitive development?
A. It confirms what Piaget claimed about infants in the sensorimotor phase.
B. Some infants are born with superior intelligence. C. Piaget may have underestimated some cognitive abilities of
infants and children.
D. Culture determines what infants are capable of doing.
Social Development, Attachment, and Self-Awareness
It seems rather obvious to point out that human infants are profoundly dependent on their caregivers for pretty much everything, from food and relief from dirty diapers, to being held and soothed when they are upset. Based on Piaget’s insight that the infant’s experiential world is largely comprised of physical sensation and movement, one might expect that physical interactions with caregivers make up a huge part of an infant’s reality. As a result, the infant’s emerging feelings of safety and security, or conversely, fear and distress, may be highly affected by the basic, physical connection with caregivers.
Nowadays, it is perhaps not a stunning insight to realize that being touched and held, seeing facial expressions that are responsive to one’s own, and hearing soothing vocalizations, are important for helping infants to feel secure in what is otherwise a pretty big, unknown and potentially scary world. However, in the mid- 20th century, it was a major insight to realize how sensitively attuned infants are to their social world, and how deeply they are affected by how they are treated by those they depend upon. Whether caregivers are loving and responsive, or perhaps neglectful or cruel, in the first months of life, can affect the developing child in ways that last for the rest of their lives.
Understanding the intense social bonding that occurs between humans revolves
around the central concept of attachment , the enduring emotional bond formed between individuals, initially between infants and caregivers. Attachment motivations are deeply rooted in our psychology, compelling us to seek out others for physical and psychological comfort, particularly when we feel stressed
or insecure (Bowlby, 1951). Infants draw upon a remarkable repertoire of behaviours that are geared towards seeking attachment, such as crying, cooing, gurgling, and smiling, and adults are generally responsive to these rudimentary but effective communications.
What is Attachment? In the early decades of modern psychology, dominant theories of motivation emphasized biological drives, such as hunger and thirst, that motivated people to satisfy their basic needs. From this perspective, the motivation that drove infants to connect with caregivers, like their mother, was simple; mom fed them, reducing their hunger, and thus, they developed a behavioural interdependence with mom, and through basic conditioning processes (i.e., associating mom with the pleasure and comfort of food), formed an emotional attachment with mom as well. Such a description of love is never going to fill a book of poetry, but it seemed to scientifically and objectively account for the infant–caregiver bond.
However, in the 1950s, a psychologist by the name of Harry Harlow made an extremely interesting observation, although one so seemingly innocuous that most of us likely would have overlooked it. Harlow was conducting research on infant rhesus monkeys, and was raising these monkeys in cages without any contact with their mothers. In the course of this research, he noticed that the baby monkeys seemed to cling passionately to the cloth pads that lined their cages, and they would become very distressed when these pads were removed for cleaning. This simple observation made Harlow start to wonder what function the pads served for the monkeys. The monkeys didn’t eat the pads, obviously, so why should they be so attached to them?
A baby monkey clings to a cloth-covered object—Harlow called this object the
cloth mother—even though in this case the wire “mother” provided food. Nina Leen/The LIFE Picture Collection/Getty Images
Harlow designed an ingenious set of studies, testing whether it was physical comfort or primary drive reduction that drove the formation of attachment. He placed rhesus monkeys in cages, right from birth, and gave them two pseudo- mothers: one was a cylinder of mesh wire wrapped with soft terry-cloth, loosely resembling an adult monkey; the other was an identical cylinder but without the cloth covering. To then test whether reducing the monkeys’ hunger was important for the formation of attachment, Harlow simply varied which of the “mothers” was the food source. For some monkeys, the terry-cloth mother had a bottle affixed to it and thus was the infant’s food source, whereas for other monkeys, the bottle was affixed to the wire mother. The question was, who would the monkeys bond with? Did their emotional attachment actually depend on which of the “mothers” fed them?
The contest between mothers wasn’t even close. No matter who had the bottle, the baby monkeys spent almost all their time with the cloth mother, pretty much ignoring the wire mother except for the small amount of time they spent actually
feeding, when she had the bottle (see Figure 10.9 ). Furthermore, the monkeys seemed emotionally attached to the cloth mother, depending on her to meet their emotional needs. For example, researchers devised experiments in which the baby monkeys would be frightened (e.g., surprising them with a metallic contraption that looked like a vicious monster), and they would watch which mother the infants would run to for comfort and security. Over and over again, they ran to the cloth mother (the videos from this experiment are heart- breaking). The implications were clear—attachment is not about reducing fundamental biological drives; it’s about feeling secure, which has a strong basis in feeling physically comforted.
Figure 10.9 Harlow’s Monkeys: Time Spent on Wire and Cloth Mother Surrogates Source: Harlow, H. F. (1958). The nature of love. American Psychologist, 13(12), 673–685. From the American Psychological
Association.
Types of Attachment
In order to measure attachment bonds in human infants, obviously it is unethical to raise babies in cages with fake mothers and then scare them half to death to see who they crawl to. Instead, psychologists have developed methods of
studying infant attachment that are only mildly stressful and mimic natural
situations. One method capitalizes on stranger anxiety—signs of distress that infants begin to show toward strangers at about eight months of age. Mary Ainsworth developed a measurement system, based on the belief that different characteristic patterns of responding to stranger anxiety indicated different types of emotional security, or attachment style.
Ainsworth (1978) developed a procedure called the strange situation , a way of measuring infant attachment by observing how infants behave when exposed to different experiences that involve anxiety and comfort. The procedure involves a sequence of scripted experiences that expose children to some mild anxiety (e.g., the presence of a stranger, being left alone with the stranger), and the potential to receive some comfort from their caregiver. For example, the child and caregiver spend a few minutes in a room with some toys; a stranger enters, the caregiver leaves, and then the caregiver returns. In each segment of the procedure, the child’s behaviour is carefully observed. Ainsworth noted three broad patterns of behaviour that she believed reflected three different attachment
styles (see Figure 10.10 ):
Figure 10.10 The Strange Situation Studies of attachment by Mary Ainsworth involved a mother leaving her infant with a stranger. Ainsworth believed that the infants’ attachment styles could be categorized according to their behavioural responses to the mother leaving and returning. Source: Lilienfeld, Scott O.; Lynn, Steven J; Namy, Laura L.; Woolf, Nancy J., Psychology: From Inquiry To Understanding,
2nd Ed., © 2011. Reprinted and Electronically reproduced by permission of Pearson Education, Inc., New York, NY.
1. Secure attachment. The caregiver is a secure base that the child turns toward occasionally, “checking in” for reassurance as she explores the room. The child shows some distress when the caregiver leaves, and avoids the stranger. When the caregiver returns, the child seeks comfort and her distress is relieved.
2. Insecure attachment. Two subtypes were distinguished: Anxious/Ambivalent. The caregiver is a base of security, but the child depends too strongly on the caregiver, exhibiting “clingy” behaviours rather than being comfortable exploring the room on his own. The child is very upset when the caregiver leaves, and is quite fearful toward the stranger. When the caregiver returns, the child seeks comfort, but then also resists it and pushes the caregiver away, not allowing his distress to be easily alleviated.
Avoidant. The child behaves as though she does not need the caregiver at all, and plays in the room as though she is oblivious to the caregiver. The child is not upset when the caregiver leaves, and is unconcerned about the stranger. When the caregiver returns, the child does not seek contact.
3. Subsequent research identified a fourth attachment style, disorganized (Main & Solomon, 1990), which is best characterized by instability; the child has learned (typically through inconsistent and often abusive experiences) that caregivers are sources of both fear and comfort, leaving the child oscillating between wanting to get away and wanting to be reassured. The child experiences a strong ambivalence, and reinforces this through his own inconsistent behaviour, seeking closeness
and then pulling away, or often simply “freezing,” paralyzed with indecision.
Attachment is important not only in infancy, but throughout one’s life. Even in adult romantic relationships, attachment styles (gained during infancy!) are still at
work (Hofer, 2006). The specific patterns of behaviour that characterize different attachment styles can be seen, albeit in somewhat more complex forms, in adult
relationships (Hazan & Shaver, 1987; Mikulincer & Shaver, 2007). Attachment styles predict many different relationship behaviours, including how we form and dissolve relationships, specific issues and insecurities that arise in relationships, and likely patterns of communication and conflict. For example, in one large, longitudinal study spanning more than 20 years, people who were securely attached as infants were better able to recover from interpersonal conflict with
their romantic partners (Salvatore et al., 2011). It appears that the father described at the beginning of Module 10.1 was correct; we really are similar to “giant babies.”
Development of Attachment
Given that attachment styles are so important, how do they form in the first place? Research consistently has shown that one’s attachment style largely reflects one’s early attachment experiences (e.g., whether caregivers tend to be loving, accepting, and responsive, or critical, rejecting, and unresponsive, or simply inconsistent and unpredictable). This makes sense; after all, attachment styles are understood to be learned patterns of behaviour that the developing child adopts in order to adapt to the key relationships in her life. This is a major insight for parents to take seriously, because the consequences of one’s own behaviour as a parent can resonate throughout the rest of the child’s life. Most important, perhaps, is parental responsiveness. For example, Ainsworth’s
research (Ainsworth, 1978) showed that maternal sensitivity (i.e., being highly attuned to the infant’s signals and communication, and responding appropriately) is key to developing a secure attachment style. More contemporary research has expanded this to included non-maternal caregivers; yes Dads, you’re important too.
At this point, especially if you feel you have somewhat of a less-than-secure attachment style, you might be wondering whether you are doomed to remain this way forever. After all, we have been emphasizing the long-term stability of attachment styles that are formed early in life. Nevertheless, it is important to
note that attachment styles can change. Insecurely attached people can certainly find their attachment style becoming more secure through having supportive relationship experiences, whether they are intimate/romantic relationships or other sorts of supportive relationships such as one may establish with a therapist
(Bowlby, 1988). The reason that attachment styles tend to be relatively consistent over time is that they tend to condition the same types of behaviour patterns and relationship outcomes that led to their formation in the first place. Just think about how much more difficult it would be for a highly avoidant or highly insecure and “needy” person to develop the sorts of patterns in relationships that would help them to feel loved and accepted, compared to somebody who is already secure. Nevertheless, if a person is able to establish healthy relationship patterns in adulthood, they can undo the effects of less-than- ideal early attachment experiences.
While it was initially believed that ideal parenting called for parents to be highly sensitive to the child, leading to closely coordinated emotional interactions between them, recent studies have shown that highly sensitive caregivers
actually demonstrate moderate coordination with their children (Hane et al., 2003). Both under-responsiveness and over-involvement/hypersensitivity to an infant’s needs and emotions are correlated with the development of insecure
attachment styles (Beebe et al., 2010). The ideal parent does not reflexively respond to all the child’s needs, but is sensitive to how much responsiveness the child needs. In the next section we will learn how this type of parental sensitivity is connected to the development of self-awareness, as well as to the ability to take other people’s perspectives.
Self Awareness
Between 18–24 months of age, toddlers begin to gain self-awareness , the ability to recognize one’s individuality. Becoming aware of one’s self goes hand- in-hand with becoming aware of others as separate beings, and thus, self-
awareness and the development of pro-social and moral motivations are intricately intertwined, as we discuss below.
The presence of self-awareness is typically tested by observing infants’ reactions
to their reflection in a mirror or on video (Bahrick & Watson, 1985; Bard et al., 2006). Self-awareness becomes increasingly sophisticated over the course of development, progressing from the ability to recognize oneself in a mirror to the ability to reflect on one’s own feelings, decisions, and appearance. By the time children reach their fifth birthday, they become self-reflective, show concern for others, and are intensely interested in the causes of other people’s behaviour.
Young children are often described as egocentric , meaning that they only consider their own perspective (Piaget & Inhelder, 1956). This does not imply that children are selfish or inconsiderate, but that they merely lack the cognitive ability to understand the perspective of others. For example, a two-year-old may
attempt to hide by simply covering her own eyes. From her perspective, she is hidden. Piaget believed that children were predominantly egocentric until the end of the preoperational phase (ending around age seven). He tested for egocentrism by sitting a child in front of an object, and then presenting pictures of that object from four angles. While sitting opposite the child, Piaget would ask him or her to identify which image represented the object from Piaget’s own perspective. Children’s egocentricity was demonstrated by selecting the image corresponding to their own perspective, rather than being able to imagine what
Piaget would be seeing (Figure 10.11 ).
Figure 10.11 Piaget’s Test for Egocentric Perspective in Children Piaget used the three-mountain task to test whether children can take someone else’s perspective. The child would view the object from one perspective while another person viewed it from a different point of view. According to Piaget, children are no longer exclusively egocentric if they understand that the other person sees the object differently. Source: Lilienfeld, Scott O.; Lynn, Steven J; Namy, Laura L.; Woolf, Nancy J., Psychology: From Inquiry To Understanding,
2nd Ed., © 2011. Reprinted and Electronically reproduced by permission of Pearson Education, Inc., New York, NY.
By two years of age, toddlers can recognize themselves in mirrors. Ruth Jenkinson/Dorling Kindersley Ltd
Modern research indicates that children take the perspective of others long before the preoperational phase is complete. Perspective taking in young
children has been demonstrated in studies of theory of mind —the ability to understand that other people have thoughts, beliefs, and perspectives that may be different from one’s own. Consider the following scenario:
An experimenter offers three-year-old Andrea a box of chocolates. Upon opening the
box, Andrea discovers not candy, but rather pencils. Joseph enters the room and she
watches as Joseph is offered the same box. The researcher asks Andrea, “What does
Joseph expect to find in the box?”
If Andrea answers “pencils,” this indicates that she believes Joseph knows the same thing she does. However, if Andrea tells the experimenter that Joseph expects to see chocolates, it demonstrates that she is taking Joseph’s mental perspective, understanding that he does not possess her knowledge that the
“chocolate box” actually contains pencils (Lillard, 1998; Wimmer & Perner, 1983). Children typically pass this test at ages four to five, although younger children may pass it if they are told that Joseph is about to be tricked (Figure 10.12 ). Of course, the shift away from egocentric thought does not occur overnight. Older children may still have difficulty taking the perspective of others; in fact, even adults aren’t that great at it much of the time. Maintaining a healthy awareness of the distinction between self and other, and accepting the uniqueness of the other person’s perspective is a continual process.
Figure 10.12 A Theory-of-Mind Task There are different methods of testing false beliefs. In this example, Andrea is asked what she thinks Joseph expects to find in the “chocolate box.” If she has developed theory-of-mind skills, she will be able to differentiate between her knowledge of the box’s contents (pencils) and what Joseph would expect to find (chocolates).
Psychological research now indicates that self-awareness and theory of mind are in constant development right from birth. Early in children’s lives, emotions are often experienced as chaotic, overwhelming, and unintegrated combinations of physical sensations, non-verbal representations, and ideas. As caregivers respond to children’s emotions, the children learn how to interpret and organize their emotions; this helps them become more aware of their own feelings
(Fonagy & Target, 1997). As children gain the ability to understand their internal states with greater clarity, it enhances their ability to represent the mental states of others.
This process helps to explain why it is important that caregivers not over-identify with a child’s emotions. If their emotional exchange is completely synchronized (e.g., the child experiences fear and the adult also experiences fear) then the
child simply gets her fear reinforced, rather than gaining the ability to understand that she is feeling fear. In a study of how mothers behave after their infants
received an injection, Fonagy et al. (1995) observed that the mothers who most effectively soothed their child reflected their child’s emotions, but also included other emotional displays in their mirroring, such as smiling or questioning. The mother’s complex representation of the child’s experience ensured that the child recognized it as related to, but not identical to his own emotion. This serves to alter the child’s negative emotions by helping him to implicitly build coping
responses into the experience (Fonagy & Target, 1997). Therefore, in the early stages of life, these face-to-face exchanges of emotional signals help the child’s
brain learn how to understand and deal with emotions (Beebe et al., 1997).
Module 10.2b Quiz:
Social Development, Attachment, and Self-Awareness
Know . . . 1. The emotional bond that forms between a caregiver and a child is
referred to as . A. a love–hate relationship
B. dependence C. attachment D. egocentrism
Understand . . . 2. Infants who are insecurely attached may do which of the following when
a parent leaves and then returns during the strange situation procedure?
A. Show anger when the parent leaves but happiness when they return
B. Show anger when the parent leaves and show little reaction when they return
C. Refuse to engage with the stranger in the room D. Show happiness when the parent leaves and anger when they
return
Apply . . . 3. Oliver and his dad read a book several times. In that book, the main
character expects to receive a hockey sweater for his birthday. However, due to a mix-up at the store, the gift box instead contains a pair of shoes. Because Oliver had read the book several times, he remembered that the box contained shoes. If Oliver was seven years old, what do you think he
would say if he was asked, “What does the main character think is in the box?” What would his two-year-old sister say if asked the same question?
A. Oliver would say that the character thought the box contained a hockey sweater; his sister would say that the character would expect to find shoes.
B. Oliver would say that the character thought the box contained a shoes; his sister would say that the character would expect to find a hockey sweater.
C. Both children would say that the main character would expect to find a hockey sweater in the gift box.
D. Both children would say that the main character would expect to find a pair of shoes in the gift box.
4. A child who you know seems to behave inconsistently towards his parents; sometimes, he is quite “clingy” and dependent, but other times is very independent and rejects the parents’ affection. This is descriptive of
a(n) attachment style. A. secure B. anxious/ambivalent C. avoidant D. disorganized
Psychosocial Development
In the previous section, we saw the powerful effect that attachment can have on a child’s behaviour. Importantly, we also saw that attachment-related behaviours that are observed in infants and young children can sometimes predict how those individuals will behave as adults. This shows us that our development is actually a life-long process rather than a series of isolated stages.
A pioneer in the study of development across the lifespan was Erik Erikson, a German-American psychologist (who married a Canadian dancer). He proposed a theory of development consisting of overlapping stages that extend from infancy to old age. In this module, we will examine the stages of development that relate to infancy and childhood. We will return to Erikson’s work again in Modules 10.3 (Adolescence) and 10.4 (Adulthood), each time discussing the parts of his theory that apply to those stages of development. Curious
readers can look ahead to Table 10.5 in Module 10.4 to see a depiction of Erikson’s model in its entirety.
Table 10.5 Erikson’s Stages of Psychosocial Development
Infancy: trust vs. mistrust: Developing a
sense of trust and security toward
caregivers.
ClickPop/Shutterstock
Adolescence: identity vs. role confusion:
Achieving a sense of self and future
direction.
Tracy Whiteside/Shutterstock
Toddlerhood: autonomy vs. shame and
doubt: Seeking independence and gaining
self-sufficiency.
Picture Partners/Alamy Stock Photo
Young adulthood: intimacy vs. isolation:
Developing the ability to initiate and
maintain intimate relationships.
OLJ Studio/Shutterstock
Preschool/early childhood: initiative vs.
guilt: Active exploration of the environment
and taking personal initiative.
Monkey Business Images/Shutterstock
Adulthood: generativity vs. stagnation:
The focus is on satisfying personal and
family needs, as well as contributing to
society.
Belinda Pretorius/Shutterstock
Childhood: industry vs. inferiority: Striving
to master tasks and challenges of
childhood, particularly those faced in
school. Child begins pursuing unique
interests.
keith morris/Alamy Stock Photo
Aging: ego integrity vs. despair: Coping
with the prospect of death while looking
back on life with a sense of contentment
and integrity for accomplishments.
Digital Vision/Photodisc/ Getty Images
Development Across The Lifespan
Erikson’s theory of development across the lifespan included elements of both cognitive and social development. Erikson’s theory centred around the notion
that at different ages, people face particular developmental crises, or challenges, based on emotional needs that are most relevant to them at that stage of life. If people are able to successfully rise to the challenge and get their emotional needs met, then they develop in a healthy way. But, if this process is disrupted for some reason and people are not able to successfully navigate a stage, the rest of the person’s personality and development could be impacted by certain deficits in their psychosocial functioning. For example, people could struggle with feeling worthless or useless, feeling insecure in relationships, feeling motivated, and so on. Understanding fully how Erikson’s insights apply to specific problems people face lies beyond our discussion here, but you can make some reasonable inferences based on a general understanding of his theory.
The first stage, Infancy, focuses on the issue of trust vs. mistrust. The infant’s key challenge in life is developing a basic sense of security, of feeling comfortable (or at least not terrified) in a strange and often indifferent world. Infants just want to know that everything is okay, and this starts with being held —being physically connected through touch and affectionate contact. As the infant develops more complex social relationships, their basic emotional security (or insecurity) grows out of the trust vs. mistrust that develops out of this stage.
The second stage, Toddlerhood, focuses on the challenge of autonomy vs. shame. The toddler, able to move herself about increasingly independently, is poised to discover a whole new world. The toddler discovers that she is a separate creature from others and from the environment; thus, exploring her
feelings of autonomy—exercising her will as an individual in the world—becomes very important. (If you’ve ever hung out with a toddler for extended periods of time, you have probably experienced their stubborn resistance, like emphatically stating “No!” to whatever you have suggested, for no clear reason.)
By the end of the first two stages, the person is, ideally, secure, and they feel a basic sense of themselves as having separate needs from others. On the other hand, if these stages were not successfully navigated, the person may struggle with feelings of inadequacy or low self-worth, and these will play out in their subsequent development.
The third stage, Early childhood, is characterized as the challenge of initiative vs. guilt. Building on the emotional security and sense of self-assurance that comes from the first two stages, here the growing child learns to take responsibility for herself while feeling like she has the ability to influence parts of her physical and social world. These preschool-years involve children pushing their boundaries and experimenting with what they can do with their rapidly developing bodies, and then experiencing guilt when they are scolded or otherwise encounter the disapproval of others, such as their parents. If this stage is navigated successfully, the child develops increased confidence and a sense of personal control and responsibility.
The fourth stage, Childhood, is all about industry vs. inferiority. Here the child is focused on the tasks of life, particularly school and the various skill development activities that take place for that big chunk of childhood. This is an important part of the child’s increasing feeling of being in control of her actions, leading her to be able to regulate herself to achieve long-term goals, develop productive habits, and gain a sense of herself as actively engaged in her own life.
Taking Erikson’s first four stages together, you can see how childhood ties together emotional development with the feeling of being a competent individual. You can also see how the challenges associated with these stages are tied together with the quality of one’s key relationships and the many complex ways in which others (e.g., parents) help or hinder the child’s ability to meet their emotional needs.
Parenting and Prosocial Behaviour
One of the central questions of development that every parent faces when raising their own children is “How can I help this child become ‘good’?” The
capacity to be a moral person is often considered to begin around the time a child develops theory of mind (the sense of themselves and others as separate beings with separate thoughts). Certainly, being aware of one’s emotions, and understanding the emotions of others, are important parts of prosocial motivations and behaviours. However, recent research seems to indicate that the basic capacity for morality is built right into us and manifests long before we
develop the cognitive sophistication to recognize self and others. Children show a natural predisposition toward prosocial behaviour very early in their
development (Hamlin et al., 2007; Warneken & Tomasello, 2013). Even one- day-old infants experience distress when they hear other infants cry, exhibiting a basic sense of empathy.
However, it is important to distinguish exactly what is meant by empathy. Surely, the one-day-old babies aren’t actually lying there, aware of the perspectives of the other infants, recognizing that when an infant cries, he is sad, and then feeling sadness in response to that awareness. One-day-old infants don’t have that much cognitive processing going on; there’s no way they can engage in very complex perspective taking. Rather, they simply feel what is going on around them; they mirror the world around them in their own actual feelings, virtually without any filter at all.
What this means is that when children are very young, they experience others’ distress directly as their own personal distress or discomfort. This makes them motivated primarily to reduce their own distress, not necessarily to help the other
person (Eisenberg, 2005). Helping the other person might be one way to alleviate one’s distress, but there might be easier ways, like ignoring them, or even shouting at them! For example, watching a parent cry is upsetting to a young child, and sometimes the child may seek to comfort the parent, such as by offering his teddy bear; other times, however, children might just close their eyes and plug their ears, or leave and go to a different room where they don’t have to see the parent, thereby alleviating their own distress. Many developmental psychologists believe that in order for explicitly prosocial motives to develop,
children must learn to attribute their negative feelings to the other person’s distress, thereby becoming motivated to reduce the other person’s suffering, not
just their own reaction to it (Mascolo & Fischer, 2007; Zahn-Waxler & Radke-
Yarrow, 1990).
Recently, researchers at the University of British Columbia and other universities demonstrated that the roots of moral motivation go back much further than we once believed, all the way to very early infancy. Studies using puppets engaging in kind and helpful, or nasty and selfish behaviours show that even very young infants (as young as three months old!) seem to know the difference between
good and bad, and prefer others who are helpful (Hamlin et al., 2007, 2010). By eight months of age, infants make complex moral discriminations, preferring others who are kind to someone who is prosocial, but reversing this and
preferring others who are unkind to someone who is antisocial (Hamlin et al., 2011). Thus, from the first months of our lives, long before we have been “taught right from wrong,” we are able to recognize, and prefer, the good.
As children move into the toddler years, prosocial behaviours increase in scope
and complexity. Around their first birthday, children demonstrate instrumental helping, providing practical assistance such as helping to retrieve an object that is out of reach (Liszkowski et al., 2006; Warneken & Tomasello, 2007). By their second birthday, they begin to exhibit empathic helping, providing help in order to make someone feel better (Zahn-Waxler et al., 1992). In one study, children younger than two were observed to be happier when giving to others over receiving treats themselves, even when the giving occurred at a cost to their
own resources (Aknin et al., 2012).
Parenting and Attachment
In humans, the tension between helping others versus being concerned for oneself reflects a kind of tug-of-war between two psychobiological systems, the attachment behavioural system , which is focused on meeting our own needs for security, and the caregiving behavioural system , which is focused on meeting the needs of others. Each system guides our behaviour when it is activated; however, the attachment system is primary, and if it is activated, it tends to shut down the caregiving system. What this means in everyday experience is that if a person feels insecure herself, it will be hard for her to take others’ needs into consideration. However, if attachment needs are
fulfilled, then the caregiving system responds to others’ distress, motivating the
person to care for others (Mikulincer & Shaver, 2005). Thus, raising kind, moral children is about helping them feel loved and secure, not just teaching them right from wrong.
This changes the emphasis in parenting, a lot! Consider the classic problems faced by all parents—they need kids to do certain things—get up, eat breakfast, get dressed, brush teeth, brush hair, pack a backpack for school, get lunch, leave the house on time, stop interrupting, be nice to siblings. . . . It’s no wonder many parenting books promise a simple, step-by-step method for getting children to behave the way parents want.
Faced with the constant challenge of managing their kids’ behaviour, parents commonly turn to the principles of operant conditioning, using rewards (e.g., Smarties, physical affection, loving words) and punishments (e.g., angry tone of voice, time-outs, criticism) as necessary. Indeed, this is so pervasive that most of us don’t think twice about it; how could rewarding good behaviour and punishing bad behaviour be a problem? However, children are not merely stimulus-
response machines, and this pervasive use of conditional approaches (i.e., rewards and punishments that are conditionally applied based on the child’s behaviour) can have significant unintended and even destructive consequences. One oft-overlooked problem is that even if conditional approaches do successfully produce the desired behaviours, these behaviours don’t tend to
persist over the long term (Deci at al., 1999). When rewards or punishments are not available to guide behaviour, children may find it difficult to motivate themselves to “do the right thing.”
Another downside to the conditional parenting approach is the impact it may have on children’s self-esteem and emotional security. Because children learn to associate feeling good about themselves with the experience of receiving rewards and avoiding punishment, their self-esteem becomes more dependent
upon external sources of validation. Instead of helping to nurture a truly secure child, parents may unwittingly be encouraging a sense of conditional self-worth, that is, the feeling that you are a good and valuable person only when you are behaving the “right” way.
Although these conditional approaches may seem fairly normal when it comes to raising children, think about it for a moment in a different context, such as your romantic relationship. Imagine that you and your partner decide to go to a couple’s counsellor, and you are told that every time your partner behaves in ways you don’t like, you should respond with negativity, such as withdrawing affection, speaking sharply and angrily, physically forcing him to sit in a corner for a certain amount of time, or taking away one of his favourite possessions. You also should use rewards as a way of getting your partner to do things you want—promise him pie, or physical intimacy, or buy him something nice. Our guess is that you would conclude it’s time to get a different counsellor. Yet, this is often how we raise children.
A mountain of research has revealed the downside of taking this kind of conditional approach to parenting. Children who experience their parents’ regard for them as conditional report more negativity and resentment toward their parents; they also feel greater internal pressure to do well, which is called introjection , the internalization of the conditional regard of significant others (Assor et al., 2004). Unfortunately, the more that people motivate themselves through introjection, the more unstable their self-esteem (Kernis et al., 2000), and the worse they tend to cope with failure (Grolnick & Ryan, 1989).
So what works better? Research clearly shows that moral development and
healthy attachment is associated with more frequent use of inductive discipline , which involves explaining the consequences of a child’s actions on other people, activating empathy for others’ feelings (Hoffman & Saltzsein, 1967). Providing a rationale for a parent’s decisions, showing empathy and understanding of the child’s emotions, supporting her autonomy, and allowing her choice whenever possible all promote positive outcomes such as greater mastery of skills, increased emotional and behavioural self-control, better ability
to persist at difficult tasks, and a deeper internalization of moral values (Deci et al., 1994; Frodi et al., 1985). When it comes to raising moral children, the “golden rule” seems to apply just as well—do unto your children as you would have someone do unto you.
Module 10.2c Quiz:
Psychosocial Development
Know . . . 1. The primary challenge in Eriksen’s “Childhood” stage of development is
. A. trust vs. mistrust B. industry vs. inferiority C. initiative vs. guilt D. autonomy vs. shame and doubt
Understand . . . 2. Marcus is very careful to teach his daughter about morality, using stories
like Aesop’s Fables, because he wants her to be a good person when she grows up. However, you notice that he often seems emotionally unavailable, and frequently criticizes her (presumably in order to improve her behaviour). Marcus seems to underappreciate the role of
in moral development. A. Piaget’s theory of cognitive development B. emotional security C. behaviourism D. theory of mind
3. If parents excessively reward and praise their children, particularly based on the children’s performance, they risk their children developing a high degree of
A. attachment anxiety. B. introjection. C. inductive discipline. D. extrojection.
Analyze . . . 4. One very common behavioural problem is when a person is too upset or
emotionally triggered to be open to listening to another person’s
perspective. This is the same basic dynamic as the
A. relationship between inductive discipline and introjected motivation.
B. relationship between the threat object and the terry-cloth mother (for rhesus monkeys).
C. relationship between the attachment behavioural system and the caregiving behavioural system.
D. parent–child relationship.
Module 10.2 Summary
accommodation
assimilation
attachment
attachment behavioural system
caregiving behavioural system
cognitive development
concrete operational stage
conservation
core knowledge hypothesis
dishabituation
egocentric
formal operational stage
habituation
inductive discipline
Know . . . the key terminology associated with infancy and childhood.
10.2a
introjection
object permanence
preoperational stage
scaffolding
self-awareness
sensitive period
sensorimotor stage
strange situation
theory of mind
zone of proximal development
According to Piaget’s theory of cognitive development, infants mature through childhood via orderly transitions across the sensorimotor, preoperational, concrete operational, and formal operational stages. This progression reflects a general transition from engaging in the world through purely concrete, sensory experiences, to an increasing ability to hold and manipulate abstract representations in one’s mind.
In developmental psychology, attachment refers to the enduring social bond between child and caregiver. Based on the quality of this bond, which is dependent upon appropriately responsive parenting, individuals develop an attachment style, which is their internalized feeling of security and self-worth. Children are either securely or insecurely attached, and insecure attachments can be further divided into disorganized, anxious/ambivalent, and avoidant
Understand . . . the cognitive changes that occur during infancy and childhood.
10.2b
Understand . . . the importance of attachment and the different styles of attachment.
10.2c
- Cover
- An Introduction to Psychological Science
- An Introduction to Psychological Science
- Business Statistics, Third Canadian Edition, 3/e
- Business Statistics, Third Canadian Edition, 3/e
- Brief Contents
- Contents
- About the Authors
- About the Canadian Authors
- From the Authors
- What’s New in the Second Canadian Edition?
- Content and Features
- For Instructors
- Acknowledgments
- Chapter 1 Introducing Psychological Science
- Module 1.1 The Science of Psychology
- Module 1.2 How Psychology Became a Science
- Chapter 2 Reading and Evaluating Scientific Research
- Module 2.1 Principles of Scientific Research
- Module 2.2 Scientific Research Designs
- Module 2.3 Ethics in Psychological Research
- Module 2.4 A Statistical Primer
- Chapter 3 Biological Psychology
- Module 3.1 Genetic and Evolutionary Perspectives on Behaviour
- Module 3.2 How the Nervous System Works: Cells and Neurotransmitters
- Module 3.3 Structure and Organization of the Nervous System
- Module 3.4 Windows to the Brain: Measuring and Observing Brain Activity
- Chapter 4 Sensation and Perception
- Module 4.1 Sensation and Perception at a Glance
- Module 4.2 The Visual System
- Module 4.3 The Auditory and Vestibular Systems
- Module 4.4 Touch and the Chemical Senses
- Chapter 5 Consciousness
- Module 5.1 Biological Rhythms of Consciousness: Wakefulness and Sleep
- Module 5.2 Altered States of Consciousness: Hypnosis, Mind-Wandering, and Disorders of Consciousness
- Module 5.3 Drugs and Conscious Experience
- Chapter 6 Learning
- Module 6.1 Classical Conditioning: Learning by Association
- Module 6.2 Operant Conditioning: Learning through Consequences
- Module 6.3 Cognitive and Observational Learning
- Chapter 7 Memory
- Module 7.1 Memory Systems
- Module 7.2 Encoding and Retrieving Memories
- Module 7.3 Constructing and Reconstructing Memories
- Chapter 8 Thought and Language
- Module 8.1 The Organization of Knowledge
- Module 8.2 Problem Solving, Judgment, and Decision Making
- Module 8.3 Language and Communication
- Chapter 9 Intelligence Testing
- Module 9.1 Measuring Intelligence
- Module 9.2 Understanding Intelligence
- Module 9.3 Biological, Environmental, and Behavioural Influences on Intelligence
- Chapter 10 Lifespan Development
- Module 10.1 Physical Development from Conception through Infancy
- Module 10.2 Infancy and Childhood: Cognitive and Emotional Development
- Module 10.3 Adolescence
- Module 10.4 Adulthood and Aging
- Chapter 11 Motivation and Emotion
- Module 11.1 Hunger and Eating
- Module 11.2 Sex
- Module 11.3 Social and Achievement Motivation
- Module 11.4 Emotion
- Chapter 12 Personality
- Module 12.1 Contemporary Approaches to Personality
- Module 12.2 Cultural and Biological Approaches to Personality
- Module 12.3 Psychodynamic and Humanistic Approaches to Personality
- Chapter 13 Social Psychology
- Module 13.1 The Power of the Situation: Social Influences on Behaviour
- Module 13.2 Social Cognition
- Module 13.3 Attitudes, Behaviour, and Effective Communication
- Chapter 14 Health, Stress, and Coping
- Module 14.1 Behaviour and Health
- Module 14.2 Stress and Illness
- Module 14.3 Coping and Well-Being
- Chapter 15 Psychological Disorders
- Module 15.1 Defining and Classifying Psychological Disorders
- Module 15.2 Personality and Dissociative Disorders
- Module 15.3 Anxiety, Obsessive–Compulsive, and Depressive Disorders
- Module 15.4 Schizophrenia
- Chapter 16 Therapies
- Module 16.1 Treating Psychological Disorders
- Module 16.2 Psychological Therapies
- Module 16.3 Biomedical Therapies
- Glossary
- References
- Name Index
- Subject Index
