Contemporary Music Review
Vol. 28, No. 3, June 2009, pp. 329–345
Can Music Inﬂuence Language and
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
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.
ISSN 0749-4467 (print)/ISSN 1477-2256 (online) ª 2009 Taylor & Francis
330 S. Moreno
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
Contemporary Music Review 331
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
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 (r ¼ 0.87) between neurophysiological data (the amplitude of early
332 S. Moreno
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-
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
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
Contemporary Music Review 333
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
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
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.
334 S. Moreno
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
Contemporary Music Review 335
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; Schon 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,
336 S. Moreno
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)
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 foret’/‘ 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
Contemporary Music Review 337
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
338 S. Moreno
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
Contemporary Music Review 339
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.
This review has attempted to bring together the behavioural and neuroscientiﬁc
results and conclusions found in current literature pertaining to the inﬂuence of
340 S. Moreno
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
Contemporary Music Review 341
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
342 S. Moreno
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-Eerikainen 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.
Contemporary Music Review 343
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.
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
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