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Can Music Influence Language and Cognition? Sylvain Moreno

Evidence has suggested that music can improve behavioural performance in several domains, including intelligence. Scientists have also discovered that music can modify the

brain at both functional and structural levels. Such neural changes can impact several domains, but one domain seems to be particularly influenced by music—namely,

language. Music and language seem to share special features that allow music to improve and shape language processing. This review will first discuss neuroimaging findings

related to music training or musical expertise. Then, the influence of music on language processing outcomes will be considered. Finally, we will look into several future directions

at the theoretical level, focusing on the relationship between music and language. Also, it will be argued that there are plausible applications for such findings, in particular when considering music as a rehabilitation tool.

Keywords: Music; Language; ERP; fMRI; Children; Training; Rehabilitation

Music and Language: A Review of Recent Neuroscience Research and Applied

Future Directions

The possibility of an influence of music on cognition is a relatively new notion in psychology and neuroscience. Researchers have explored this link and discovered that

musical expertise (e.g., studies with musicians versus non-musicians) or musical training (e.g., studies with non-musicians who learn music) can improve behavioural performance and modify brain substrates, not only in the musical domain but also in

other domains. This new understanding of the relationship between music and cognition is helping scientists understand the effects of environmental influences on

human cognition more broadly. By studying the effect of music on human cognition, scientists have begun to learn about the power of music. The general public has also

become interested: ‘Music makes you smarter’ or ‘Music helps you to learn other languages’—these are examples of common thoughts pertaining to questions about

the influence of music.

Contemporary Music Review Vol. 28, No. 3, June 2009, pp. 329–345

ISSN 0749-4467 (print)/ISSN 1477-2256 (online) ª 2009 Taylor & Francis DOI: 10.1080/07494460903404410

Rauscher et al. (1993) conducted a study that started a debate on the ‘side effects’

of musical exposure. They reported that brief exposure (10 minutes) to a Mozart sonata generated short-term increases in spatial-reasoning abilities (subsequently

dubbed ‘the Mozart effect’ by the media). This finding attracted considerable attention—it appeared in a highly prestigious journal, Nature, and the investigators

translated their findings into a spatial IQ-score improvement of approximately eight points (i.e., half a standard deviation). Indeed, the popular conclusion that ‘music makes you smarter’ was a direct product of this IQ translation. Questions were

subsequently raised pertaining to the validity of the findings (e.g., sitting in silence or listening to a relaxation tape for ten minutes is less arousing or interesting than

listening to Mozart), and several alternative hypotheses have been proposed, such as a mood or arousal effects (Thompson et al., 2001). Nonetheless, this study inspired

several other researchers to pursue research pertaining to this question using a variety of differently controlled experimental designs. Several studies have now reported

evidence indicating a positive transfer (e.g., improvements in performance) from musical experience to other cognitive domains such as language (Chan et al., 1998; see below for a development), mathematics (Costa-Giomi, 2004; Gardiner et al.,

1996; Graziano et al., 1999; but see Vaughn, 2000), symbolic and spatio-temporal reasoning (Hetland, 2000; Rauscher et al., 1995, 1997, but see Hassler et al., 1985),

visuo-spatial abilities (Brochard et al., 2004; Gromko & Poorman, 1998), verbal memory (Chan et al., 1998; Ho et al., 2003), self-esteem (Costa-Giomi, 2004) and

general intelligence (Schellenberg, 2004, 2006). All these studies have related musical experience of some kind to improvements in

cognitive skills. However, many of the studies are correlational, which means that causation cannot be inferred. This restricts the ability to provide definitive answers to

questions pertaining to the transfer of skills between music and other activities. These studies have also brought to mind another question: if musical expertise or training improves behaviour in cognitive skills, what are the consequences for the brain? The

following discussion will analyse and discuss a range of research related to this topic by reviewing the link between musical expertise or training and other areas of

cognitive ability. The discussion will begin with the relevant neuroimaging findings of music on cognition in order to introduce the central point of this article, which is the

link between music and language. Finally, we will end this review by looking at the possible outcomes of this type of research and by proposing several future directions.

Music and Neuroscience

The development of brain imaging techniques in neuroscience offers new possibilities of testing whether or not intensive musical training can modify the brain at the

anatomical and functional levels, and thereby affect other cognitive abilities. In this literature, two kinds of techniques are used: direct and indirect. Direct techniques

(i.e., direct studies of brain activity) are Event Related Brain Potentials (ERPs) and Magnetoencephalography (MEG), which capture the electrical and magnetic activity

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of the brain during cognitive activity. This differs from indirect brain techniques such

as functional Magnetic Resonance Imaging (fMRI), which records blood flow (e.g., indirect measure of brain activity). Using structural MRI to examine brain structure

(rather than activity), many studies have shown anatomical differences between the brains of musicians and non-musicians. For example, a study by Schlaug et al.

(1995b) was one of the first to show a link between musical expertise and the brain. The study questioned whether the midsagital area of the corpus callosum, which is involved in the coordination of movement, is influenced by musical expertise (in this

case, in keyboard or string instrument players). Results showed a significantly larger anterior half of the corpus callosum in musicians than in non-musicians. From this

finding, Schlaug et al. (1995b) concluded that early and intensive training in keyboard and string players may facilitate increased and faster communication

between the brain’s hemispheres in order to perform complex bi-manual movements. Several further studies have also demonstrated structural differences between

musicians and non-musicians’ brains, finding significant differences in the planum temporale (related to verbal memory processing and absolute pitch; Keenan et al., 2001; Luders et al., 2004; Schlaug et al., 1995a; Zatorre et al., 1998), the posterior

band of the precentral gyrus (related to motor processing; Amunts et al., 1997), the corpus callosum (related to cross-hemisphere communication; Schmithorst & Wilke,

2002), the anterior-medial part of the Heschl gyrus (related to auditory processing; Schneider et al., 2002), the inferior frontal gyrus (related to executive functions such

as attention and language), the inferior lateral temporal lobe (related to auditory processing; Gaser & Schlaug, 2003; Luders et al., 2004) and parts of the cerebellum

(related to motor processing; Hutchinson et al., 2003) (for a review, see Schlaug, 2003). All the brain areas cited above are involved in behavioural skills related to

instrument use and music processing. These findings pose the question: What influences these brain areas—early and intensive training or biological brain predispositions?

Two findings support the interpretation of an influence of nurture. Schneider et al. (2002) showed a link between anatomical and functional modifications from

experience. They compared the processing of sinusoidal tones in the auditory cortex of 12 non-musicians, 12 professional musicians and 13 amateur musicians. In their

first task, participants listened passively to these sounds while watching a silent movie, and then had to detect deviant sounds while their brain magnetic activity was

being recorded. Results showed modifications in brain magnetic activity: the amplitudes of N19m and P30m components (i.e., early components of auditory brain waves) were 102% larger in professional musicians than in non-musicians, and 37%

larger in amateur musicians than in non-musicians (the professional musicians’ dipole amplitude was significantly greater in the right hemisphere than in the left

hemisphere, but these differences were not significant for non-musicians). In addition, the grey matter volume in the anterior-medial part of Heschl’s gyrus was

130% larger in professional musicians than in non-musicians. The crucial result was a strong correlation (r¼0.87) between neurophysiological data (the amplitude of early

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auditory evoked activity: N19m-P30m), anatomical data (gray matter volume in the

anterior-medial part of Heschl’s gyrus) and musical expertise. These results are crucial because they suggest that the functional differences reported in many studies

may be directly associated with anatomical differences, and that these functional differences are proportional to the amount of musical training. Furthermore, Hyde

et al. (2009) have reported structural brain changes after only 15 months of musical training in children, which were found to correlate with improvements in musically relevant motor and auditory skills. These findings extend the previous study

because they suggest that structural brain differences in adult musicians could be due to training-induced brain plasticity rather than to biological brain predisposi-

tions. The other approach to this question is by direct analysis of brain activity such as

ERPs and MEG. In this literature, musicians and non-musicians are often asked to perform various motor, perceptual or cognitive tasks, such as typing with their

fingers, or listening to or storing/memorising music, in order to discriminate between sounds, or to perceive harmonic, melodic or rhythmic changes (for a review, see Patel, 2008). This huge literature will not be described in detail but instead emphasis

will be placed on the studies which focused on the effects of music expertise or training. More specifically related to our music training theme, the results of several

studies have shown perceptual auditory processes (reflected by N1 and P2 ERP components) to be modified by musical expertise or training. In this field, cognitive

processes are observed through the product of neuronal activity: electricity. Electrical brain responses have positive (P) and negative (N) electric amplitudes occurring at

specific points in the processing time (e.g., at a designated time after processing begins). Therefore, the first negative waveform emitted after processing begins is

called an N1, the second one is called N2 and so on. Trainor et al. (2003) conducted studies with adults and children, in which they recorded ERPs and found modification in these waveforms after music training.

It has also been shown that the amplitude of the P2 component increases when non-musicians are trained to make an auditory discrimination (Tremblay et al.,

2001). Shahin et al. (2003) compared the amplitude of these components among professional musicians, violinists and pianists, and among non-musicians who

listened passively (while reading the newspaper) to the sounds of violin, piano or pure tones. The results showed that the amplitude of P2 and N1 components

(in response to three different timbres) was higher among musicians than among non-musicians. Moreover, it is important to note that the spatial source analysis of these components showed that they were located at different places in the secondary

auditory cortex and in the superior temporal gyrus. These results suggested that musical expertise modifies the auditory processing at both functional and structural

levels. Another experiment by the Trainor group studied the same components with

children. Trainor et al. (2003) compared children aged 4–5 years who were or were not trained with the Suzuki method of music teaching. The results of this study

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showed that the P1, N1 and P2 components were enhanced in children who had

musical experience and the amplitude of the P2 component increased according to the musical instrument (piano) played by the children. Finally, Fujioka et al.

(2006) tested 4–6-year-old children having Suzuki music lessons, four times over a one-year period using the MEG method. They found that a magnetic component,

the N250m, elicited by violin tones was enhanced in musically trained children as compared to untrained children. This study suggests that music training can modify auditory brain processing very quickly, over a one-year period. However,

because some factors were not controlled for in this experiment, the authors concluded that pre-existing differences between children, as well as differences in

cognitive stimulation and motivation between groups, might still account for this finding.

Other studies have found additional aspects of auditory processing to be modified by music expertise or training (Shahin et al., 2007). Notably, Lappe et al. (2008)

extended these findings by showing that music training can influence the simultaneous perception of several sensory modalities: auditory, visual, somatosen- sory, as well as the motor system. They tested the hypothesis that music training

involves multimodal brain plasticity by using musically elicited mismatch negativity (MMN) from magnetoencephalographic measurements before and after music

training. The mismatch negativity is a brain process that occurs after an infrequent change in a sequence of identical sounds (e.g., an oddball sequence). For example, a

rare deviant (BOP) sound can be interspersed among a series of frequent standard (beep) sounds (e.g., beep BOP beep beep beep beep BOP beep beep beep beep beep

beep BOP beep beep BOP). The deviant sound can differ from the standards in one or more perceptual features such as pitch, duration or loudness. Lappe et al. (2008)

trained two groups of non-musicians over a two-week period. One group— sensorimotor-auditory (SA)—learned to play a musical sequence on the piano, whereas the other group—auditory (A)—listened to and made judgments about the

music that had been played by participants of the SA group. Results showed significantly different cortical responses after training in SA and A groups.

Specifically, the SA group showed significant enlargement of MMNm after training compared with the A group. This reflects greater enhancement of musical

representations in the auditory cortex after sensorimotor-auditory training compared with the effects of mere auditory training. In summary, this study

showed that sensorimotor-auditory training involves brain plasticity in the auditory cortex.

Another new method has emerged in this field to observe the influence of musical

expertise and training on the brain. Gamma frequency band (30–100 Hz) studies yield evidence that brain plasticity (training) is reflected by Gamma-band activation.

A Gamma frequency band (30–100 Hz) is an oscillatory brain response that is elicited by a stimulus. Oscillatory Gamma Band Activity (GBA, 30–100 Hz) has been shown

to correlate with perceptual and cognitive phenomena including feature binding, template matching, and learning and memory formation.

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In a very elegant study, Schulz et al. (2003) examined the plasticity of the auditory

cortex. They composed a melody of complex sounds whose fundamental frequency was absent, and which could only be perceived on the basis of either the actual

frequency or the virtual height of the missing fundamentals. Before training, participants were unable to perceive the virtual melody but this perception became

possible after training. The ERPs magnetic recording showed an increase of Gamma activity after training that reflected the process of integration (i.e., coupling or ‘binding’ at the cognitive level). The cortical sources that generated these effects were

also slightly displaced after training. These results are important because they demonstrate strong correlations between the degree of musical expertise and the

amplitude of the electromagnetic responses, as well as the neuronal network of the primary auditory cortex.

Recently, Shahin et al. (2008) studied the link between Oscillatory Gamma Band Activity (GBA, 30–100 Hz), musical expertise and training. This group of researchers

hypothesised that if GBA reflects highly learned perceptual template matching, they should be able to observe its development in musicians specific to the timbre of their instrument of practice. EEG was recorded in adult professional violinists and amateur

pianists as well as in 4- and 5-year-old children studying piano using the Suzuki method, before they began music lessons and one year after. The adult musicians

showed robust enhancements of induced (non-time-locked) GBA, specific to their instrument of practice, with the strongest effect in professional violinists. Consistent

with this result, children receiving piano lessons exhibited increased power of induced GBA for piano tones with one year of training, while children without

lessons showed no effect. In comparison to induced GBA, evoked (time-locked) Gamma Band Activity (30–90 Hz, * 80 ms latency) was present only in adult groups. Evoked GBA was more pronounced in musicians than in non-musicians, with synchronisation equally exhibited for violin and piano tones, but enhanced for these tones in comparison to pure tones. Evoked Gamma activity may index the

physical properties of a sound and is modulated by acoustical training, while induced GBA may reflect higher perceptual learning and is shaped by specific auditory

experiences. This study helps us to dissociate the induced and evoked GBA influences and their relationship with musical training. The results of musical expertise are

interesting but the lack of a control group constrains the interpretation. Therefore, GBA seems to be a powerful training marker and it will certainly be a major factor in

our future understanding of music training effects. In conclusion, music training influences behaviour, brain and, more specifically,

auditory cortex and sound processing. Brain modifications are reported at both

functional and structural levels and are linked to behavioural improvements. After this description of music’s influences on auditory processing, some new questions

arise: Are music effects limited to the auditory cortex or processing? Can music be an agent in accessing other brain functions and cognitive skills? Could musical training,

through its special link with the auditory cortex, influence other auditory-related brain activity?

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Music and Language

This section will present evidence that implies a link between music and language

skills—two of the most complex, uniquely human abilities. Research on this link has recently received increased interest within psychology and neuroscience. The Bangert

et al. (2006) study on musicians and non-musicians, using neuroimaging, is a perfect way to introduce this topic. The results of this study showed that musicians exhibit stronger activation than non-musicians in areas of the brain associated with language

processing (Broca’s and Wernicke’s areas). This finding points out the overlapping network between music and language. Music and language share many features and

elements, with one obvious example being that they are both auditory systems. Both music and language rely on the same four acoustic parameters: fundamental

frequency (F0), spectral characteristics, intensity and duration. These shared acoustic parameters give the opportunity to develop studies whose conclusions can help us

understand the connection between language and music. Several studies in the literature have explored the ‘prosody-melody’ (fundamental

frequency-pitch) relationship. The main hypothesis in these studies is that musical

expertise, by increasing sensitivity to pitch, enhances pitch detection not only in music, but also in speech. For example, in a study by Thompson et al. (2004),

participants were asked to listen to semantically neutral utterances spoken with emotional (i.e., happy, sad, fearful or angry) prosody, or to tone sequences that

mimicked the utterances’ prosody, and then identify the emotion conveyed. Results showed that musically trained adults performed better than untrained adults,

specifically on identification of sadness, fear or neutral emotion. In their last experiment, the effect of different types of training on emotion identification was

studied. Six-year-old children followed one year of keyboard, vocal, drama or no lessons. Results showed that the keyboard group performed equivalently to the drama group and better than the no-lessons group at identifying anger or fear. These

experiments revealed that music expertise and training promote sensitivity to emotional speech prosody, and thus emphasised the possibility of a connection

between music and language. A few years ago, two experiments (Magne et al., 2006; Schön et al., 2004)

investigated the specificity of perceptual and cognitive processing required to perceive and understand language in adults and children, respectively. These

experiments were designed to compare the prosodic level of processing in language directly with the melodic level of processing in music. Short musical and linguistic phrases were presented to listeners, and the final words or notes were made

prosodically or melodically congruous or incongruous (weak or strong incongruity). Results showed that musicians perceived pitch deviations better than non-musicians,

not only in music, but also in language. Moreover, F0 manipulations within both music and language elicited different variations in brain electrical potentials between

musicians and non-musicians. However, most of the behavioural and neural data supporting an association between music and language are from correlational studies,

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such as the Magne et al. (2006) study described above. These data, therefore, are

unclear as to whether behavioural and anatomo-functional differences between musicians and non-musicians reflect predispositions for musical ability, or the effects

of extended musical practice. On the basis of the Magne et al. (2006) findings, we designed a research

programme that included two longitudinal studies aimed at specifying causality of the influences of musical training on language processing. This research programme asked three main questions: Does musical training influence behavioural perfor-

mance in language processing? Does musical training influence neural processing of language (ERP)? And finally, what are the influences of short (eight weeks) and

mid-term (six months) training on behavioural performance and ERP in language processing? We predicted that mid-term training, compared to short-term training,

would result in behavioural performance patterns and electrophysiological patterns that more closely look like the findings of the musicians in the Magne et al. (2006)

study. The aim of the first experiment was to determine whether short-term (eight weeks)

musical training would help 8-year-old children to detect pitch changes in language

(Moreno & Besson, 2006). We first tested twenty non-musician children in a pitch discrimination task (Magne et al., 2006) involving three conditions: prosodically

congruous, weakly incongruous (35% F0 increased) or strongly incongruous (120% F0 increased). The stimuli were comprised of 72 French spoken declarative sentences

taken from children’s books, and ending with bi-syllabic words (e.g., ‘Un loup solitaire se faufile entre les troncs de la grande forêt’/‘ A lonely wolf walked his way

through the trees of the large forest’). The experiment was divided into three phases: Test 1, Training and Test 2. We recorded Reaction Times (RTs), error rates and the

neural Event-Related Potential (ERP) to the responses of the final words of a sentence. Following this, one group of ten children received musical training and the other group of ten children received painting training, both for eight weeks. Finally,

all twenty children were tested again with the same task. Our purpose was to test if eight weeks of musical training could enhance and facilitate pitch processing in

language (Magne et al. 2006). After eight weeks of training, our results showed no difference between groups at the behavioural level: for both groups of children,

results showed that the level of performance increased after training and the weak incongruity was the most difficult to detect. Most importantly though, analysis of the

ERP waveforms showed that while music training influenced the amplitude of the late positive component to strong incongruities, no such effect was found in the painting group. Thus, a relatively short exposure to music training modified the brain

processing involved in language. Following this first experiment, we conducted a longitudinal study (Moreno et al.,

2009) in which the training lasted six months (mid-term). We analysed the effects of musical and painting lessons on pitch discrimination in language and recorded

behavioural results and ERPs in 8-year-old children. Pitch processing abilities were also measured before and after training. We investigated the same question as in the

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previous experiment—namely, whether musical training enhances and facilitates

pitch processing in language—but with a longer period of musical training. We hypothesised that children with music lessons would be able to detect the weak pitch

violation in language better than the children with painting lessons. Moreover, at the electrophysiological level, weak incongruity stimuli should elicit larger positive

components than congruous words, but only in the musically trained group. Thirty- two children from two elementary schools in Northern Portugal participated in this study. On the basis of their results in the neuropsychological tests, they were divided

into two matched groups. One group received music training; the other received painting training. The experiment was also divided into three phases. In Phase 1,

children were tested individually in two sessions (separated by 4–5 days) that lasted for about two hours each. In the first session, they completed the neuropsychological

assessments, and in the second session, the behavioral and ERP testing. In Phase 2, Training, they received either music or painting training for 24 weeks. Finally, in

Phase 3, children were again tested individually in their school, in two sessions that lasted also for around two hours each (neuropsychological testing and ERPs).

A subset of the Portuguese sentences used by Marques et al. (2007) was used, similar

to those of Magne et al. (2006). The main aim of this longitudinal study was to determine whether six months of musical training in 8-year-old children influences

pitch perception in language. The results clearly showed positive transfer effects in the music group, but not in the painting group. These effects were found both on

behavioural measures (pitch detection performance) and on electrophysiological measures. Results showed enhancement of reading and pitch discrimination skills after

musical training, but not after painting. Six months of musical training thus appears to be enough to modify behaviour and to influence brain function: there was a causal link

between musical training and language processing modifications at both the behavioural and brain levels. These studies suggest a positive transfer from music to language and highlight the plasticity of the human brain by showing that relatively short periods of

training have strong consequences on the functional organisation of a child’s brain. This is strong evidence for the effect of nurture on human behaviour and the brain.

Other findings support this association between musical expertise and linguistic pitch discrimination at the cognitive level (Schellenberg & Moreno, forthcoming)

and at the subcortical level (Wong et al., 2007). Schellenberg and Moreno (forthcoming) studied pitch processing with musicians and non-musicians. Results

showed that musical training was more strongly associated with cognitive aspects of pitch processing than with sensory aspects. At the subcortical level, Wong et al. (2007) used EEG to study an oscillatory neural response to sound, the Frequency-

Following Response (FFR), which is generated in the inferior colliculus of the brainstem. Mandarin Chinese linguistic pitch patterns (syllables) were presented

aurally to musicians and non-musicians (participants had no knowledge of Mandarin). The task was to listen to the syllables during a silent movie projection.

Results showed that musicians had a better representation of the stimulus F0 contours and more robust neural phase-locking (relation between F0 contour of the

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stimulus and the subject’s response contour) than non-musicians. These findings are

particularly interesting as they suggest that musical expertise influences language processing at both the sensory and at the cognitive level. The results provide evidence

for an interconnection between language and music, and an explanation for the often reported higher-language learning ability of musicians. This could be directly relevant

to policies concerning the funding of music and foreign language education. We explored this hypothesis in another study (Marques et al., 2007). The aim was

to determine whether musical expertise influences the detection of pitch variations in

a foreign language (participants did not speak or understand the foreign language). Could music expertise improve perception skills and/or processing of a second

language? To this end, sentences spoken in Portuguese were presented to French adults, musicians and non-musicians. The final words of the sentences were

prosodically congruous or incongruous. Results showed that when the pitch deviations were small and difficult to detect, the level of performance was higher

for musicians than for non-musicians. Moreover, analysis of the time course of pitch processing (ERP) suggested that musicians were 300 msec faster than non-musicians to categorise prosodically congruous and incongruous endings. These results are in

line with previous research showing that musical expertise, by increasing discrimination of pitch—a basic acoustic parameter, equally important for music

and speech prosody—does facilitate the processing of pitch variations not only in music, but also in a foreign language. These types of findings support the idea that

music can facilitate second language acquisition and language acquisition in general. Music and language share many characteristics; one obvious link is that both

activities take place at the auditory level, but many studies show a relationship at other levels as well, such as at the level of syntax and harmony or semantics and

melody (for a review, see Patel, 2008). For example, a recent finding suggests a connection between language and music at the semantic and syntactic levels. Steinbeis and Koelsch (2008) studied harmonic tension-resolution patterns. These

kinds of patterns have long been hypothesised to be meaningful to listeners familiar with Western music. Even though it has been shown that specifically chosen musical

pieces can prime meaningful concepts, the empirical evidence in favour of such a highly specific semantic pathway has been lacking. Results showed that two event-

related potentials in response to harmonic expectancy violations—the early right anterior negativity (ERAN) and the N500—could be systematically modulated by

simultaneously presented language material containing either a syntactic or a semantic violation. Whereas the ERAN was reduced only when presented concurrently with a syntactic language violation and not with a semantic language

violation, this pattern was reversed for the N500. These findings show a specific link between language and music through semantic

and syntactic processing, but other studies also emphasise different links such as working memory. In an article published in Nature, Chan et al. (1998) tested a

specific hypothesis regarding the transfer of learning between music and verbal memory. Based on results showing that the planum temporale is larger in musicians

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than in non-musicians (Schlaug et al., 1995a), and given the association between this

brain region and verbal memory, these authors hypothesised that musicians would have a better verbal memory than non-musicians, whereas their visual memory,

which does not require the same brain areas, would not be different. The results of this study, with sixty students (30 musicians and 30 non-musicians) confirmed this

hypothesis. Thus changes in the organisation of cortical areas in the left temporal cortex of musicians might improve the level of performance in tasks such as verbal memory. However, these results did not demonstrate unequivocally that music

training is the only factor responsible for improving the level of performance in verbal memory. The socio-cultural development of students with and without music

training, for example, was not controlled for in this study, and the number of years of education was not equivalent in both groups (Schellenberg, 2001).

Even if these studies have methodological issues, it seems reasonable to think that they open the door to a very interesting path in research—namely, the memory link

between music and language or global shared processing between music and language. Koelsch and Jentschke (2008) recently showed a relationship between music and memory processing. They studied working memory for verbal and tonal

information during rehearsal and articulatory suppression, using functional neuroimaging (fMRI). Strings of four sung syllables were presented to non-musicians

with the task of remembering either the pitches (tonal information) or the syllables (verbal information). Results showed activation in the ventrolateral premotor cortex

(encroaching Broca’s area), dorsal premotor cortex, the planum temporale, inferior parietal lobe, the anterior insula, subcortical structures (basal ganglia and thalamus),

as well as the cerebellum for rehearsal of verbal, as well as of tonal information. These findings suggest that both the rehearsal of verbal and tonal information, as well as

storage of verbal and tonal information, relies strongly on overlapping neuronal networks. These networks appear partly to consist of sensorimotor-related circuits, which provide resources for the representation and maintenance of information, and

are remarkably similar for the production of speech and song. In summary, these findings suggest a close relationship between music and language

at the sensory and cognitive levels. Music and language seem to be unique in terms of resource sharing. A reasonable explanation for this is that ‘resources provide a

particular processing function needed in both domains’ (Patel, forthcoming). More- over, they also show the influence of music on language processing and on the brain

structures involved in language processing. These effects also allow us to qualify nurture influences. This type of influence could have direct impact on the same cognitive skill, but could also have indirect impact by modifying processing in other cognitive skills. However,

further studies are needed to shed light on nurture influences.

Conclusion

This review has attempted to bring together the behavioural and neuroscientific results and conclusions found in current literature pertaining to the influence of

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musical training or expertise on cognition. As we saw in the introduction, music

seems to improve several cognitive skills, but most of the results to date have not shown a clear causal link. However, our review of the neuroimaging literature

suggests that music expertise or musical training involves important brain modification at the functional and structural levels. For example, our review showed

major modifications on several brain areas involved in different brain functions such as auditory processing (e.g., Heschl’s gyrus, planum temporale; Keenan et al., 2001; Luders et al., 2004) but also the frontal lobe (e.g., inferior frontal gyrus; Gaser &

Schlaug, 2003), the corpus callosum (Schlaug et al., 1995b) and parts of the cortex that are related to motor function (e.g., primary motor cortex and cerebellum;

Amunts et al., 1997; Hutchinson et al., 2003). Again, it must be kept in mind that most of the studies in this literature are correlational; however, some of them show a

clear causal influence of musical training on auditory processing skills. These finding are strengthening arguments about the effect of nurture on musical ability and the

powerful potential of this art to transfer skills to other cognitive domains. Finally, these findings introduced the music-language relationship. The results of Bangert et al. (2006) show that music stimulates brain areas associated with language

processing. I elaborated upon several findings clearly showing the bond between music and language and notably demonstrating the causality of this connection

(Moreno & Besson, 2006; Moreno et al., 2009). From these findings emerge many different questions as well as possible directions for future research. Below, there will

be a discussion of future research directions and consideration of applied possibilities for rehabilitation or training.

There are three theoretical directions that seem interesting. One of the obvious directions is the continuation of research on the link between music and language.

Patel’s (2008) book presents several pieces of evidence for relationships between music and language, and encourages further exploration by addressing clear hypotheses. One side of this relationship remains unfairly forgotten: it would be

interesting to study the ‘double direction’ of the link between music and language. Currently, most studies examine how music expertise or music training can influence

or modify language processing. However, it would be interesting to study how language expertise or training can modify music processing. For example, Patel and

Daniele (2003) studied the hypothesis that the prosody of a culture’s spoken language can influence the structure of its instrumental music when comparing English and

French composers. Results showed that composers were influenced by their spoken language: the prosody of a composer’s native language had an influence on the structure of his or her music.

Another interesting direction to take would be to try to gain a deeper understanding of the reason the link exists: is it the shared specific neuronal

resources, common general brain processing between activities (e.g., executive functions) or both? Recently, an interesting experimental design was introduced by

Bialystok and Depape (2009) in which there was a comparison between musicians, bilinguals and non-musician monolinguals. By comparing bilingualism and musical

340 S. Moreno

life experiences, this design offers us the possibility to compare the effect of language

and music stimulation on behaviour and the brain as well as to identify specific and common influences of these life experiences. Bialystok and Depape (2009) studied the

effect of musical expertise and bilingualism on executive function processing. Participants completed three cognitive measures and two executive function tasks

(a Simon task and an auditory Stroop task) that were based on conflict. All participants performed equivalently for both the cognitive measures and the control conditions of the executive function tasks. However, performance diverged in the

conflict conditions. In a version of the Simon task involving spatial conflict between a target cue and its position, both bilinguals and musicians outperformed

monolinguals. In a version of the Stroop task involving auditory and linguistic conflict between a word (high or low) and its pitch (high or low), musicians

performed better than the other participants. The results suggest that both ‘life experience-training’, music and language (bilingualism) improve executive functions

such as control. For musicians, these findings are attributed to their training requirements that involve high levels of control (Miyake & Shad, 1999). It can definitively be said that these kind of general processes such as executive functions are

a plausible candidate for the explanation of the link between music expertise or training and other cognitive activity. Further studies will help to understand specific

and common influences of music and language. The third theoretical/applied direction is the increasing interest in studies on the

impact of musical training as a rehabilitation tool. Scientific findings have taught us the incredible ability of music to access and to improve other cognitive areas such as

language, but also motor skills (Gaser & Schlaug, 2003), reading (Moreno et al., 2009), intelligence (Schellenberg, 2004) and executive functions (Bialystok & Depape,

2009). The cognitive areas influenced by musical training are involved in a number of pathologies. If musical training could improve performance and modify the brain processing of these activities, the adaptation of features of musical training to

pathologies could be used as a remediation tool. Due to the novelty of this finding and its potentially great positive effects, several laboratories in the world are now

exploring this new direction. As we noted previously, scientific studies have provided evidence for a strong

interrelation between music and language neural networks at functional and anatomical levels, thereby setting the ground for possible effects of musical training in

Speech and Language Impairment (SLI) therapy. Dyslexic children have been found to exhibit timing difficulties in the domains of language, music, perception and cognition, as well as in motor control. A research programme was able to test

practically the hypothesis of the positive effects of classroom music lessons on the timing skills and literacy skill of dyslexic children (Overy, 2003), with results

suggesting a positive effect of musical training on both phonologic and spelling skills, but not on reading skills.

Two studies recently supported the potential for using music as a rehabilitation tool. Forgeard et al. (2008) conducted a longitudinal study with normal-reading

Contemporary Music Review 341

children and a pilot study with dyslexic children. Their results suggested a strong

relationship between musical discrimination abilities and language-related skills. In normal-reading children, musical discrimination predicted phonological and reading

skills. In children with dyslexia, musical discrimination predicted phonological skills, which in turn predicted reading abilities. Taken together, these findings reflect the

results of a meta-analysis conducted by Butzlaff (2000). This meta-analysis shows a correlation between learning music and reading skills and suggests that a music intervention that strengthens the basic auditory music perception skills of children

with dyslexia may also remediate some of their language deficits. Another example of music as a cognitive rehabilitation tool is the research

programme based on Melodic Intonation Therapy (MIT) investigated by Schlaug and colleagues (Overy et al., 2004, Schlaug et al., 2008). The technique was inspired by the

common clinical observation that some severely aphasic patients are better at singing the lyrics of songs than they are at speaking the same words. MIT emphasises the

prosody of speech by using slow, pitched vocalisation (singing), and has been shown to lead to significant improvements in naming and propositional language beyond the actual treatment period. In the Schlaug et al. (2008) study, post-treatment outcomes

revealed significant improvement in propositional speech that generalised to unpracticed words and phrases. However, the MIT-treated patients’ gains surpassed

those of the control-treated patients. Treatment-associated imaging changes indicated that MIT’s unique engagement of the right hemisphere, both through singing and

tapping with the left hand to prime the sensorimotor and premotor cortices for articulation, accounts for its effect over non-intoned speech therapy.

Finally, our last example on this topic is the Music Training Project (MTP) in which we are developing a training/rehabilitation tool based on two technologies: the

Virtual Musical Instrument (VMI; http://www.prismlab.org/research_page/research_ ve.html) and Smarter Kids Training (SKT; http://www.musiqkids.com). This project brings together several competencies based on music, teaching, engineering,

psychology and neuroscience. The VMITM Virtual Music Instrument is a non- contact, computer vision-based interface that allows individuals with varying levels of

mobility to create pleasing musical sounds in response to movement of any part of the body. Through several years of technology development, usability tests with

children and families (Ahonen-Eerikäinen et al., 2008; Chau et al., 2006; Tam et al., 2007) and beta-tests in rehabilitation centres in eight different countries (Canada,

United States, Australia, Taiwan, Philippines, Brazil, Netherlands and the United Kingdom), the VMITM has evolved into a general physical rehabilitation tool with wide-reaching appeal. The Smarterkids training (SKT) is a musical training software

that is based on recent scientific studies in which music is used to develop cognitive functions such as attention, working memory, language, reading and intelligence.

Both technologies allow us to offer unique educational training and an assessment tool that can help persons with disabilities that are entered into rehabilitation

programmes. The goal of this project is to deliver a music rehabilitation tool for therapists, families and children.

342 S. Moreno

This review has shown the influence of music on behaviour and on the brain, and

its potential to modify brain functions and structures. Both psychology and neuroscience findings on the influences of music are ready to play a role in applied

research. As seen through the above examples, different directions emerge from this literature. Some of these directions are theoretical and some of them more applied.

However, without a doubt, psychology and neuroscience will help us to understand the powerful potential of music. One of the potentially most successful future directions will be the exploration of the rehabilitation potential of this art. Our

community now has the responsibility to diffuse these results through technologies and devices within our societies.

Acknowledgements

This work was supported by grant R01HD052523 from the United States National

Institutes of Health to Ellen Bialystok. I would like to thank specifically Dr Bialystok for her support and her mentorship. I also thank Kornelia Hawrylewicz, Lorinda Mak, Tashua Case, Dr Kathleen Peets, Dr Glenn E. Schellenberg and Dr Mireille

Besson for their precious help, as well as all the children who participated in the studies.

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