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Maturation of Cognitive Control: Delineating Response Inhibition and Interference Suppression Christopher R. Brydges1*, Mike Anderson1,2, Corinne L. Reid1,2, Allison M. Fox1

1 Neurocognitive Development Unit, School of Psychology, University of Western Australia, Perth, Western Australia, Australia, 2 School of Psychology, Murdoch

University, Perth, Western Australia, Australia

Abstract

Cognitive control is integral to the ability to attend to a relevant task whilst suppressing distracting information or inhibiting prepotent responses. The current study examined the development of these two subprocesses by examining electrophysiological indices elicited during each process. Thirteen 18 year-old adults and thirteen children aged 8–11 years (mean = 9.77 years) completed a hybrid Go/Nogo flanker task while continuous EEG data were recorded. The N2 topography for both response inhibition and interference suppression changed with increasing age. The neural activation associated with response inhibition became increasingly frontally distributed with age, and showed decreases of both amplitude and peak latency from childhood to adulthood, possibly due to reduced cognitive demands and myelination respectively occurring during this period. Interestingly, a significant N2 effect was apparent in adults, but not observed in children during trials requiring interference suppression. This could be due to more diffuse activation in children, which would require smaller levels of activation over a larger region of the brain than is reported in adults. Overall, these results provide evidence of distinct maturational processes occurring throughout late childhood and adolescence, highlighting the separability of response inhibition and interference suppression.

Citation: Brydges CR, Anderson M, Reid CL, Fox AM (2013) Maturation of Cognitive Control: Delineating Response Inhibition and Interference Suppression. PLoS ONE 8(7): e69826. doi:10.1371/journal.pone.0069826

Editor: Francesco Di Russo, University of Rome, Italy

Received May 28, 2013; Accepted June 14, 2013; Published July 23, 2013

Copyright: � 2013 Brydges et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: Funding support was provided for by an Australian Postgraduate Award scholarship for Christopher Brydges. The child research was supported by grants from Princess Margaret Hospital grant EP1910 and the Channel 7-Telethon Trust. The adult research was funded by the School of Psychology at the University of Western Australia. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing Interests: The authors have declared that no competing interests exist.

* E-mail: [email protected]

Introduction

Cognitive control refers to the group of processes required to

resist interference from distracting stimuli or prepotent automatic

responses, whilst attending to task-relevant information [1,2].

These inhibitory processes are often considered to be important

components of intelligence [3–5], as well as affecting an

individual’s ability to function in everyday life [6]. In the past

10–15 years, interest in how inhibition is associated with other

executive functions (especially shifting and updating of working

memory) has been a particular area of focus [7–9]. However,

although several theorists have proposed that subprocesses of

inhibition should be considered as related yet separable, only a

minimal amount of research has examined the validity of these

claims (but see [10–12]).

The present study focuses on response inhibition (the suppres-

sion of a prepotent or automatic behavioural response) and

interference suppression (the ability to control for distracting

stimuli or information due to stimulus competition; 13). Nigg

proposed a taxonomy of inhibition, of which response inhibition

and interference suppression are two distinct yet related processes

[13]. Other prominent theories of inhibition [14–16] may use

different terminology for these constructs; however, each of these

theories converges upon the notion that inhibition refers to several

separate but interrelated processes, rather than a singular

construct.

A recent study by Brydges, Clunies-Ross et al. reported

electrophysiological evidence in support of the separability of

response inhibition and interference suppression in young adults

[10]. Participants completed a hybrid Go/Nogo flanker task whilst

having an electroencephalogram (EEG) recorded. The N2 event-

related potential (ERP), which is commonly associated with

inhibition on both Go/Nogo and flanker tasks [17–21], was

analysed between the incongruous condition (measuring interfer-

ence suppression) and the Nogo condition (measuring response

inhibition). Two major findings were reported: first, the N2 peak

associated with each process was maximal at different scalp sites,

and the peak latency differed significantly between conditions.

Specifically, the N2 elicited in the incongruous condition was

maximal at the central midline site, and had a significantly longer

latency than the N2 elicited in the Nogo condition, which was

maximal at the frontal midline site. From this, it was suggested that

these topographical differences were due to these two processes

originating from different neural regions or that a common set of

generators differentially contribute to each process. Additionally,

the latency difference suggests that interference suppression may

require additional cognitive processing over and above that

required for successful response inhibition [16,22], providing

further evidence for the separability of the proposed subprocesses

of inhibition.

The maturation of inhibitory processes and other executive

functions is of critical importance in children, particularly in

educational settings [23]. Previous research has found marked

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improvements on behavioural measures of inhibition throughout

childhood and, in some cases, into mid-adolescence [24–26].

Huizinga et al. reported improved performance on both a stop-

signal task and a flanker task between groups of children aged 7,

11, and 15 years respectively, suggesting that there may be some

common developmental process that leads to the improvement of

both response inhibition and interference suppression.

From a neuroimaging perspective, Bunge et al. [11] examined

the maturation of these two processes by using functional magnetic

resonance imaging (fMRI) to record neural activity whilst adults

and children aged 8–12 years completed a hybrid Go/Nogo

flanker task. It was reported that children displayed activation of

posterior regions of the brain during successful response inhibition,

whereas prefrontal regions were activated in adults. During

successful interference suppression, prefrontal regions were acti-

vated for both groups; however, only the left hemisphere was

activated in children, whilst only the right hemisphere was

activated in adults. Hence, it is apparent that neural development

of cognitive control occurs at a significant rate through late

childhood and adolescence [27,28]. One possible drawback of the

task used by Bunge et al., however, is that the flanker stimuli acted

as cues to inhibit responses in the Nogo condition of their task.

That is, in the conditions that required a response, the flanker

stimuli were meant to be ignored, but participants were required

to actively attend to them in the Nogo condition. This could have

changed the manner in which participants processed the

incongruous stimuli, supported by the low error rates in this

condition.

No previous research has used ERPs to simultaneously examine

the maturation of response inhibition and interference suppres-

sion. When examining response inhibition, Johnstone et al. [29]

recorded EEG data whilst groups of children, and young and older

adults completed a Go/Nogo task, and found that N2 peak latency

significantly decreased from childhood to adulthood, perhaps due

to myelinisation occurring during this period of childhood, hence

increasing neural speed [30]. N2 peak amplitude also significantly

decreased with age, due to greater activation of regions of the

prefrontal cortex in children than in adults [31]. Additionally,

Jonkman et al. [32] reported that the medial frontal cortex (near

the anterior cingulate cortex) is activated during response

inhibition and associated with the N2 in both children and adults.

There is a scarcity of literature examining the electrophysiological

development of interference suppression through childhood;

however, Rueda et al. [33] found a significant decrease of N2

peak latency between four year-old children and adults during

completion of a child-friendly flanker task. However, the

amplitude of the N2 was very small in the group of children,

and became larger in the adult group. It was claimed that these

differences are neural evidence of the incomplete development of

interference suppression processes in children.

The aim of this study was to examine the maturation of

response inhibition and interference suppression simultaneously

from an electrophysiological perspective. It was hypothesised that

the results observed by Brydges et al. [10] would be replicated in

the adult sample. Specifically, the N2 associated with response

inhibition have a shorter latency and be more frontally distributed

than that of the N2 associated with interference suppression.

Additionally, it was hypothesised that the site of maximal

amplitude of the N2 ERP associated with response inhibition

would become increasingly frontal between childhood and

adulthood [11,28], and that the N2 amplitude and peak latency

would both significantly decrease with age [29]. Furthermore, it

was hypothesised that there would be no change in the site of

maximal amplitude of the N2 ERP associated with interference

suppression between children and adults. However, based on the

results of Rueda et al. [33] there would be a significant increase in

the amplitude of the N2, and a significant decrease of peak latency,

with age. In addition to ERP analyses, source localisation was

conducted on each group and condition, and was expected to

display further evidence of different neural generators between

conditions.

Methods

Ethics Statement Approval for the study was provided by the Human Research

Ethics Office of The University of Western Australia (both groups)

and by the Princess Margaret Hospital Ethics Committee (child

group). All adult participants and parents/guardians of the child

participants provided written informed consent.

Participants Twenty six participants were recruited and split into two groups

of thirteen. The group of typically developing children were aged

8–11 years (M = 9.77 years; 9 females and 4 males), and the adults

(8 females and 5 males) were all aged 18 years. Children were

recruited through Project K.I.D.S. (Kids’ Intellectual Develop-

ment Study), a research program examining the cognitive, social,

and emotional development of children run by the Neurocognitive

Development Unit of the School of Psychology of the University of

Western Australia. The young adults were first-year undergrad-

uate psychology students who participated in order to partially

fulfil course requirements. Both groups completed the task as part

of a larger test battery.

Materials The same hybrid Go/Nogo flanker task used by Brydges et al.

[10] was used in this study. Each stimulus consisted of five fish

presented on a blue background. An arrow on the body of the fish

specified direction and the target was the central fish. Participants

were instructed to press a response button on a keyboard (red felt

patches on the ‘Z’ and ‘/’ keys) analogous to the direction of the

central fish. The task had three conditions: in the congruent

condition (.5 probability), the fish were green and all facing the

same direction. In the incongruent condition (.25 probability), the

fish were also green, however the flankers faced the opposite

direction to the central target. In the Nogo condition (.25

probability), the fish were congruent but were all red, the

participant was required to not respond. Each fish subtended.9u horizontally and.6u vertically, with.2u separating each fish (see Figure 1). Stimuli were presented in random order for 300 ms with

a 2,000 ms inter-stimulus interval. The task was presented to the

children as a game in which the participants had to feed the

hungry central fish. Speed and accuracy were equally emphasized.

Eight practice trials were administered to ensure the participants

understood the task requirements. A total of 176 trials were

subsequently presented in one block.

Electrophysiological Acquisition The EEG was continuously recorded using an Easy-Cap

TM .

Electrodes were placed at 33 sites based on Easy-Cap montage 24

(see http://www.easycap.de/easycap/e/products/products.htm

for more details). Eye movements were measured with bipolar

leads placed above and below the left eye. The EEG was amplified

with a NuAmps 40-channel amplifier, and digitized at a sampling

rate of 250 Hz. Impedances were below 5 kV prior to recording. During recording, the ground lead was located at AFz and the

right mastoid was set as reference, and a common averaged

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reference was calculated offline. Scan 4.3 was used to conduct the

ERP processing. Offline, the EEG recording was digitally filtered

with a 1–30 Hz zero phase shift band-pass filter (12 dB down).

The vertical ocular electrodes enabled offline blink reduction

according to the standard algorithm proposed by Semlitsch et al.

[34].

Data Analysis Epochs encompassing an interval from 100 ms prior to the

onset of the stimulus and extending to 1000 ms post-stimulus were

extracted and baseline corrected around the pre-stimulus interval.

Epochs containing artifacts larger than 150 mV or where an incorrect behavioural response was committed were excluded

from the ERP average. Difference waveforms were then calculated

by subtracting the individual ERP average elicited following

presentation of the congruent stimuli from the ERP average

elicited following presentation of the incongruent stimuli and the

Nogo stimuli. We calculated the interval over which the N2

inhibition effect was significant by comparing the amplitude of the

difference waveforms at each time point from 100–550 ms against

a mean value of zero. To control for the number of comparisons

conducted, we required a successive sequence of 11 statistically

significant values based on an autocorrelation of 0.9 and graphical

threshold of 0.05, as detailed by Guthrie and Buchwald [35]. In

the group of children, the incongruous N2 effect was not

significant at Fz, FCz, or Cz. In the Nogo condition, the N2

effect was significant at Cz between 388–464 ms only. In the adult

group, the incongruous waveform was significant at Fz, FCz, and

Cz, during respective latencies of 312–360, 304–380, and 296–

388 ms. These latency windows were averaged to 304–376 ms for

analyses. In the Nogo condition, the N2 waveform was significant

at Fz (128–180 ms and 224–264 ms) and FCz (136–180 ms).

However, upon examination of the difference waveforms, it was

apparent that the two early waveforms at these sites were N1

peaks, and were excluded from analyses.

Source localisation analyses were conducted on each condition

in the adult group using BESA 5.1. The same analyses were

attempted on the group of children; however, the observed results

were inadmissible. Instantaneous dipole models were computed on

grand average ERP difference waveforms of each condition within

the latency windows mentioned previously. A four-shell ellipsoidal

head model with default values of bone thickness (7.0 mm) and

conductivity (0.0042) was used for analyses. Dipole pairs were

fitted with locations and orientations constrained to be mirror-

symmetrical. Source models were computed in a 12 ms window

around the N2 difference peak latency at the site of maximal

amplitude for each of the conditions (276 ms at Fz for the Nogo –

congruous difference waveform, and 352 ms at FCz for the

incongruous – congruous difference waveform). Source models

were considered acceptable if they explained at least 95% of the

variance, and were stable across different starting points. The

reported solutions were stable across different starting positions.

A mixed design ANOVA with scalp site (Fz, FCz, Cz) as a

repeated measures factor was conducted on the mean amplitudes

extracted. Latency and amplitude of the N2 effect were quantified

for peaks within a 212–464 ms latency interval at the site of

maximal amplitude only. This window was chosen to capture the

intervals identified in difference waveform analyses for both

conditions in each age group, and to ensure the maximum point

was identified in each participant’s waveform.

Results

Behavioral Results Descriptive statistics of behavioural results are presented in

Table 1. A 262 mixed design ANOVA with reaction time (congruous and incongruous) as a repeated measures factor found

that performance was impaired in the incongruous condition in

comparison to the congruous condition (F(1, 24) = 57.22, p,.001,

gp 2 = .70). Additionally, performance significantly improved with

age (F(1, 24) = 28.23, p,.001, gp 2 = .54). However, the interaction

between age group and condition was not significant (F(1,

24) = 0.38, p = .54, gp 2 = .02).

ERP Results The mean N2 amplitude of the incongruous – congruous

difference waveform of one adult participant was considered an

extreme value (greater than 3 SDs from the mean), and was

replaced with a value 3 SDs from the mean for statistical analyses.

Figure 2 shows the stimulus-locked grand averaged waveforms for

each condition between age groups, and Figure 3 shows the

difference waveforms computed by subtracting the ERPs elicited

to the congruous stimuli from each of the other two waveforms.

The amplitudes and latencies of the N2 peak identified in the

difference waveforms are summarised in Table 2.

The results of Brydges et al. [10] were generally replicated: the

negativity observed in the Nogo – congruous difference waveform

was more frontally distributed (Fz.FCz.Cz) than that observed

in the incongruous – congruous difference waveform

(FCz.Cz.Fz), as evidenced by a significant interaction between

scalp site and condition (F(2, 24) = 3.96, p = .033, gp 2 = .25).

Figure 1. The six stimuli used in the present experiment (taken from Brydges, Clunies-Ross, et al., 2012). doi:10.1371/journal.pone.0069826.g001

Table 1. Descriptive statistics of behavioural measures between groups (means, with standard deviations in parentheses).

Age group Congruous Incongruous Nogo

Reaction Time % correct

Reaction Time

% correct

% correct

Children 637 (184) .91 (.06) 705 (167) .79 (.05) .88 (.10)

Adults 379 (35) .97 (.04) 437 (51) .85 (.10) .98 (.03)

doi:10.1371/journal.pone.0069826.t001

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Additionally, the peak latency of the incongruous – congruous

difference waveform was significantly longer than that of the Nogo

– congruous difference waveform (F(1, 12) = 8.24, p = .014,

gp 2 = .41).

The negativity observed in the Nogo – congruous difference

waveform did not produce a significant main effect of electrode

site (F(2, 48) = 0.47, p = .63, gp 2 = .02) or of age group (F(1,

24) = 0.18, p = .90). However, a significant interaction between site

and age group was observed (quadratic trend; F(1, 24) = 19.30,

p,.001, gp 2 = .45). Specifically, the N2 peak was centrally

distributed in children (Cz.FCz.Fz), but was frontally distribut-

ed in adults (Fz.FCz.Cz). The peak latency of the negativity

observed in the Nogo – congruous difference waveform signifi-

cantly decreased with age (F(1, 24) = 7.18, p = .013, gp 2 = .23).

Additionally, peak amplitude also decreased with age, although

this effect was marginally significant (F(1, 24) = 3.93, p = .059,

gp 2 = .14). As no significant N2 effect was observed for the

incongruous – congruous difference ERP in the group of children,

no analyses were conducted.

Source Localization Results Source localization analyses were conducted on grand average

ERP difference waveforms of each condition in the adult group

(see Figure 4). In the Nogo condition, two symmetrical dipoles at

Talairach coordinates (11.7, 27.1, 26.8) and (211.7, 27.1, 26.8)

accounted for 95.47% of the variance, mapping onto a more

anterior region of the cingulate gyrus in each hemisphere [36,37].

In the incongruous condition, two symmetrical dipoles at (8.1,

210.5, 28.8) and (28.1, 210.5, 28.8) accounted for 95.17% of the

Figure 2. Stimulus-locked grand average ERP waveforms in response to congruous (blue), incongruous (green), and Nogo (red) stimuli with the amplitude (mV) as the y-axis and time (ms) as the x-axis. Time 0 represents stimulus onset. doi:10.1371/journal.pone.0069826.g002

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variance in the ERP, mapping onto the cingulate gyrus in each

hemisphere.

Discussion

The results of this study showed that the N2 ERP changed in

latency and topography between childhood and adulthood, and

that the N2 effect was different following presentation of

incongruous and Nogo stimuli in the two groups. The differences

of amplitude, latency, and topography between conditions during

development (as evidenced by the significant main effects and

interactions of ANOVAs), as well as differences observed in the

source localisation analyses conducted on the adult group, provide

evidence of the separability of response inhibition and interference

suppression [10,13].

In the Nogo condition, the N2 effect was maximal at central

scalp sites in children, but was maximal at frontal sites in adults.

Additionally, source localisation found that the dipoles observed in

adults are in frontal regions (see Figure 4). Previous research has

found that neural activation associated with response inhibition

becomes increasingly frontal with age through childhood devel-

opment [11]. Frontal regions, including the anterior cingulate

cortex, are commonly associated with behavioural performance on

Go/Nogo tasks in adults [38,39], and are one of the last regions of

the brain to complete development [28,40]. It appears that in the

early stages of development of this region, children are more

reliant upon more posterior regions of the brain in order to

successfully inhibit responses [11,41]. Additionally, a significant

main effect of latency was observed. This may be explained by the

large-scale myelination occurring throughout childhood and

Figure 3. Grand-averaged difference waveforms computed as the incongruous – congruous waveform (green) and Nogo – congruous (green) with the amplitude (mV) as the y-axis and time (ms) as the x-axis. Time 0 represents stimulus onset. doi:10.1371/journal.pone.0069826.g003

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adolescence [30,42], which is commonly thought to decrease ERP

latency [43,44]. A marginally significant decrease in amplitude

was also observed between the two age groups, providing some

support for previous research by Johnstone et al. [29], who found

that N2 amplitude decreased with age, thought to be caused by

fewer cognitive demands and increasingly efficient recruitment of

relevant brain regions as individuals develop through childhood

[31].

In the incongruous condition, there was no significant N2 effect

in the group of children, whereas the effect was maximal at fronto-

central sites in adults. Although an increase in the size of the effect

from childhood to adulthood was hypothesised, it is somewhat

surprising that no N2 effect at all was observed in children. It is

possible that this lack of significant neural activation in children is

caused by differences in the propagation of neural activation

between childhood and adulthood. Previous neuroimaging

research has reported that children display more diffuse activation

of frontal regions, whereas the neural activation observed in adults

is more focalised due to a gradual decrease in the number of

synapses through childhood and adolescence, and an increase in

the strength of connections between the remaining synapses

during this time [45,46]. Due to these weaker, more inefficient

connections between synapses in children, it may be plausible that

children ‘spread the load’ across a larger region of the brain, which

results in less dense neural activation.

The results of this study could contribute to several avenues of

future research, particularly in clinical settings. For example,

examining the effects of traumatic brain injury (TBI) on response

inhibition and interference suppression would provide further

insight into the underlying neural generators of the two processes.

Whilst some previous research [47,48] has examined the effects of

TBI on various cognitive tasks, no study has attempted to

determine whether a differential deficit exists between these

inhibitory subprocesses. Considering that previous research has

highlighted clear differences in white matter integrity between TBI

patients and control groups [48], it would be of particular interest

to examine the latency of the N2 ERP, as an increased latency in

TBI patients would provide a new perspective on the link between

brain and behaviour in atypical groups.

Alternatively, examining differences between typically and

atypically developing groups of children may be of benefit.

Children born preterm, for instance, have been shown to be at

increased risk of various cognitive deficits, including executive

dysfunction [49], in addition to neurophysiological differences

such as decreased brain volume [50,51]. Research into differences

between typically and atypically developing children can poten-

tially provide further evidence of the separability of inhibitory

subprocesses from a new perspective, strengthening theories of

inhibition and its development [13].

In conclusion, the present study has added evidence from an

electrophysiological perspective to the predominantly behavioural-

based knowledge of the development of inhibitory processes

[12,13,24]. Results from ERP analyses have reported topograph-

ical changes in both response inhibition and interference

suppression, and latency and amplitude reductions in response

inhibition. Additionally, source localisation analysis has provided

evidence that the neural generators of response inhibition and

interference suppression are distinct. Consistent with previous

research, the current study suggests that the cingulate cortex is

involved in, and highly important to, response inhibition and

interference suppression respectively [52–56]. Furthermore, there

Table 2. N2 amplitude and latency summary statistics between groups (means, with standard deviations in parentheses).

Group Condition Site N2 MA N2 PkA N2 PkL

Children IS – CS Fz – – –

FCz – – –

Cz – – –

NG – CS Fz 0.00 (1.16)

FCz 20.93 (1.78)

Cz 21.86 (1.93) 24.08 (1.79) 352.00 (64.06)

Adults IS – CS Fz 21.04 (1.19)

FCz 22.37 (2.11) 23.35 (2.00) 350.46 (36.90)

Cz 21.80 (0.94)

NG – CS Fz 21.70 (1.80) 22.66 (1.86) 275.69 (80.22)

FCz 20.90 (2.07)

Cz 20.41 (1.43)

doi:10.1371/journal.pone.0069826.t002

Figure 4. Source localisation analyses for (a) Nogo – congruous and (b) incongruous – congruous N2 effects in the adult group. doi:10.1371/journal.pone.0069826.g004

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are marked differences between age groups within each condition,

providing neurophysiological evidence of different developmental

trajectories of the two constructs. Theories of the development of

inhibition and other higher-order cognitive functions (such as

working memory) would greatly benefit from the integration of

neuroscience with behavioural evidence.

Acknowledgments

This research was presented in an earlier form at the forty-first annual

meeting of the International Neuropsychological Society. Our gratitude

extends to Kaitrin McNamara and Catherine Campbell for their help with

coordination of Project K.I.D.S., and to Karen Clunies-Ross, An Nguyen,

David Thompson and Jesse Bruggler for assistance with adult data

collection.

Author Contributions

Conceived and designed the experiments: CB AF. Performed the

experiments: CB AF. Analyzed the data: CB AF. Wrote the paper: CB.

Reviewed final manuscript: MA CR AF. Trained and supervised ERP

testers: AF. Conceived and designed the methodology for mass testing of

children in a holiday programme: MA CR. Supervised the research group:

MA. Trained and supervised testers in child assessment and recruited

participants: CR.

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