The Musicians Brain
brain is considered as an ideal model for plasticity studies: they start playing
musical instrument usually in the early childhood and continue to improve their
skills by practicing even when they have reached a professional level. Practicing
to play involves accurate processing of temporal and spectral simple sounds
as well as complex sounds or sound patterns. The result of long-term active
and intensive music training does not affect only musical related skills and
also in non-musical related skills i.e., verbal memory, mathematic and spatial
ability. This review article cover music centre in the brain, musician brain
in anatomical and functional aspects, enhancing of musical and non-musical related
skills aspects, hypothesis of music and spatial ability and spatial mental imagery
Received: July 18, 2012;
Accepted: September 19, 2012;
Published: December 27, 2012
Brain area specialization for music does not entail that a musical centre
must exist in the brain. Rather brain area specialization for music may lie
in several distributed neural circuitries that are essential to the normal perception
of the musical component and normal function of music related activities. Although
the right hemisphere of the human brain has been traditionally viewed as the
"musical hemisphere," there are evidences that the right auditory cortex is
related for perceiving pitch and some aspects of pitch, melody, harmony, timbre
and rhythm (Tramo, 2001). Previous evidence from patients
who has focal brain excisions, they found that the right temporal damage has
greater deficit than left side (Peretz and Zatorre, 2005).
The brain lesion and neuroimaging studies, found that extraction mechanism of
the pattern of changes in pitch locate in the superior temporal gyrus and frontal
regions on the right hemisphere (Peretz, 2002). The
right temporal cortex plays a particularly important role in the computation
of pitch relations.
The brain areas relate to the harmonic component has been studied in several
techniques. The studies of harmonic expectancies elicit the event-related potentials
found the neural generators appear to be located in the inferior frontal areas
(the frontal operculum) on both sides of the brain. The fMRI studies of harmonic
expectancies also found the same areas; the inferior frontal areas (Peretz
and Zatorre, 2005). The PET study of the structure components of musical
perception in non-musician found that in the timbre discrimination task preponderate
of metabolic activity in a right hemisphere and recognize rhythm task show metabolic
activity in the insula area in left hemisphere (Baeck, 2002).
There is increasing evidence that musical functions recruit neural mechanisms
in both cerebral hemispheres and also relate to multiple brain regions in each
hemisphere. Patel and Balaban (2000) and Sittiprapaporn
(2010, 2011) suggested that music processing may
be distinguished by its characteristic dynamic activity and the pattern of brain
interactions it engenders rather than by the particular brain regions that respond
to it. The location of the music-specific neural networks may lie in the dynamic
characteristics of their functioning and interaction (Patel
and Balaban, 2000).
Since the experience can shape the structure of cortical networks and enhance
some brain areas depends on the level of structure of interest, there are evidences
of size differences in brain regions of the musicians brain and relevant
functions of the brain region, when compared to the brain of non-musician (Peretz
and Zatorre, 2005).
Development of musicians brain: The size and temporal organization
of brain representations of stimuli are continually shaped by experience. During
playing a musical instrument requires the simultaneous integration of multimodal
sensory and motor information with multimodal sensory feedback mechanisms to
monitor performance. Musicians must translate music notation (visual-spatial-temporal
information) into precisely timed sequential finger movements involving coordination
of both hands, recall long passages of song pieces, bring meaning to music through
the use of dynamics and articulation, transpose pieces to new keys and improvise
melodies and harmonics based on existing musical pieces. Such musicians
brain differences may well be due to musical training (Norton
et al., 2005). Previous study support effect of music on developing
brain (Shahin et al., 2003, 2004;
Trainor et al., 2003) used ERPs technique to
investigated the plasticity of auditory cortex. They found P2 component was
lager in both adult and children who have extensive musical training than non-musician.
The enhancing of P2-evoked response was observed in children as young as 4-5
years of age who have musical experience. Therefore, they concluded that the
P2 is particularly neuroplastic of cortical sound representation that affect
by auditory experience. This effect has been explained by Hebbian learning rules,
cells that fire together, wire together; that the brain is not as
a static but as a dynamic system, strengthening of synaptic between neurons
are formed depending on synchronous activation between pre-and post synapses.
Hebbian learning rules: Since the psychologist Donald Hebb attempted
to account for learning and memory, in 1949, he wrote When an axon of
Cell A is near enough to excite Cell B and repeatedly or persistently takes
part in firing it. Some growth or metabolic change takes place in one or both
cells such that As efficacy, as one of tow cells firing B is increased
This assumed the structural changes that produced memory possible has received
much experimental support. Consequently, the result changes in the strength
of the synaptic efficacy which alters the properties of groups of interacting
neurons as a result of neural activity often are referred to as Hebbian plasticity
(Lamprecht and Joseph, 2004). Likewise, Long-term Potentiation
(LTP) is important as a leading candidate for a synaptic or cellular mechanism
or a rapid learning. LTP was first demonstrated in the hippocampus and more
in recently in the cerebral cortex. LTP is the long-term increase
in synaptic strength between two neuron or two groups of neurons that followed
high frequency stimulation of the first neurons or set of neurons, produces
a greater response in the second neurons or neurons and the potentiation of
the response can last at least hours and most typically during the duration
of the experiment. These synaptic changes are thought to be the same one that
occurs in learning (Lamprecht and Joseph, 2004). On
the whole, LTP, as Hebbian mechanism of use-dependent modification in the strengths
of pre-existing synaptic connection among neurons, therefore are seen as critically
important in learning and memory storage.
Anatomical differences: The brain imaging studies which allow study
anatomical detail in the human brain found the several brain areas shows difference
between musicians and non-musicians. Gaser and Schlang (2003)
via the method of voxel-based morphometry investigated the gray matter volume
in two musician groups (professional and amateur) and non-musician group. They
found an increase in of gray matter in primary motor and somatosensory areas,
premotor areas, anterior superior parietal areas and in the inferior temporal
gyrus bilaterally of musician groups when compare to non-musician group (Gaser
and Schlaug, 2003). The asymmetry of the brain study in the planum temporale
(the posterior superior temporal gyrus) of right-handed professional musicians
and non-musicians by high resolution in magnetic resonance morphometry found
the stronger leftward planum temporale asymmetry in musicians (Scheler
et al., 1995).
Music-related functional perspective: The evidences of anatomical changes
in the musician brains are observed and investigated by the behavioral difference
between musician and non training person in both perceptual and cognitive aspects.
In last decade, functional imaging and neuron-physiological studies on musical
ability and associated brain structure and functionality demonstrated that different
brain structure of musician corresponds with difference music-related data processing
when compare with non-musician (Kizkin et al., 2006).
While listening to music only the synchrony in the gamma band that show significantly
higher for musicians than non-musicians, while listening to the text has no
statistically significant different. This higher synchrony was found in many
cortical regions. The hemispheric dominance during musical tasks in musician
is clearly in left-hemisphere, while non-musicians show right-hemisphere dominance
(Bhattacharya et al., 2001). The event-related
potential study show P2 and N1c components had larger response to the violin
tones, piano tones and pure tones in highly skill musicians. The P2 and N1c
of the Auditory Evoked Potential (AEP) have been shown to be sensitive to remodelling
of the auditory cortex by training at pitch discrimination in non-musician subjects.
This result may suggest that the tuning properties of neurons are modified in
distributed regions of the auditory cortex in accordance with the acoustic training
history of the subject (Shahin et al., 2003).
The evoked potential studies of the ability to distinguish musical sounds pre-attentively
and automatically by auditory P50 and N100 components between professional musician
and non-musician. The result showed P50 wave but not the N100 wave is suppressed
less in musicians than non-musicians (Kizkin et al.,
The investigation of brain activity during listening to music in female musicians
and non-musicians by using fMRI technique found a significant higher signal
in the musician group was observed in the right superior and middle temporal
gyri, the right inferior frontal gyrus and the left supramarginal gyrus (Seung
et al., 2005). Pantev et al. (1989),
using MEG has shown that brain responses to piano tones were 25% larger in musicians
than in non-musicians (Peretz and Zatorre, 2005). The
recruitment of different neural networks for harmony and melody processing in
musician relative to controls using fMRI. In musical training person appears
result in recruitment of addition cortical area such as inferior parietal lobules
for both music processing (Schmithorst and Holland, 2003).
The accuracy and reaction time studies found that the musicians performed better
than the non-musicians in two timbre discrimination tasks (Chartrand
and Belin, 2006). Previous studies on brain response to harmonically inappropriate
chords between expert and novices musician by using event-related brain potentials.
They found musical experts have clearly larger than novices. The ERAN is an
ERP component that is elicited by violations of complex musical and the more
specific representations of these regularities in experts led to a higher degree
of violation in this musician group (Kizkin et al.,
2006). Music training also effect to musical imagery task i.e., in the musical
mental imagery and common sound imagery task, musician performs better than
non-musician in both tasks. The authors suggested that musical training may
improve musical and also non-musical auditory imagery task (Aleman
et al., 2000).
IMPACT OF MUSIC TO OTHER COGNITIVE FUNCTION
Music can lead to short-term and long-term effect to non-music related cognitive.
Music listening: Music listening can lead to enhanced performance on
variety of test of cognitive ability. The Mozart effect; refers
to an enhancement of performance or change in neurophysiological activity associated
with listening to Mozarts music (Jausovec and Habe,
2004). Rauscher et al. (1993) found after
listening to 10 min of classic music, the spatial IQ score of music condition
group were higher 8-9 point from the silent and relaxation group. There have
been several studies that replicated the Mozart effect, however the Mozart effect
is very controversial and many studies have failed to replicate it. The meta-analysis
study of Chabris (1999) motivated speculation that the
Mozart effect could be explained as an artifact of arousal. Next two years,
Thompson et al. (2001) propose the arousal-and-mood
hypothesis that listening to Mozart is one example of a stimulus that influences
the perceivers arousal level and mood which can affect performance on
a variety of cognitive tasks.
Music training: Music lessons have collateral benefits that extend from
musical benefits to cognitive functions that are not related to musical. Music
lessons involve a multiplicity of experiences that could generate improvement
in a wide range of abilities. During music training involve long periods of
focused attention, daily practice, reading musical notation, memorization of
extended musical passages, learning about a variety of musical structures and
progressive mastery of technical skills and the conventions governing the expression
of emotions in performance. This combination of experiences could have a positive
impact on cognition, particularly during the childhood years, when brain development
is highly plastic and sensitive to environmental influence. Many findings have
been show music lessons have positive associations in intellectual ability such
as verbal memory, spatial ability, visuospatial performance and mathematics
achievement (Brochard et al., 2004; Schellenberg,
2005). Previous study show improvement effect of music training in full
scale IQ, the Wechsler Intelligence Scale scores (WISC-III) was measured before
and after the music lesson in children who received music lesson, drama lessons
and no lessons. Comparison with children in the drama lesson and no lesson groups,
children in the music groups exhibited increases in full-scale IQ of the WISC-III
Music training and verbal memory: Chan and Colleagues assessed the verbal
memory between musician who received music training before 12 years old (at
least six years) and no music training colleges. The music training group learned
significantly more word of verbal memory than non-musicians. This evidence shows
that music training may have a long-term effect on the improvement of verbal
memory (Chan et al., 1998).
Music training and mathematics achievement: Eighth grade student who
had private music lessons for 2 or more years performed significantly better
on the composite mathematics portion of the Iowa Tests of Basic Skills (ITBS)
than did students who did not have private lessons. It was found that students
with 2 or more years of private lessons had a significantly higher mean mathematics
score than did students with no private lessons. The students who received lessons
on the keyboard had significantly higher ITBS score than did the students who
had music lessons but not on the keyboard (Cheek and Smith,
MUSIC AND SPATIAL ABILITY
Psychological relationship: The relationship between music and spatial
ability was investigated by Barrett and Barker Jr. (1973),
the group of children aged 8 to 12 years were assessed with a musical performance
test and with various tests of pattern recognition. The result indicated a positive
significant correlation between music performance and the Hidden pattern test.
Series studies of Hassler et al. (1985) demonstrated
that acoustic structuring ability and spatial ability are analogous construction.
Several versions of an Acoustic Structuring Test were assessed in subjects 6
years to adult. He found higher correlations of musical/spatial ability (0.33)
than of musical/verbal ability (0.09). After he also found the different correlation
of musical/spatial and musical/verbal according to the amount of their musical
training; subjects with less than two years of training have higher musical/verbal
correction, subjects with more than two years have higher correlation between
musical/spatial ability (Hassler et al., 1985).
Rauscher et al. (1997), after 6 months of private
keyboard instruction and singing preschool children have higher score of an
object assembly test of spatial-temporal reasoning than control groups. The
control groups did only singing, computer instruction and no instruction. Early
keyboard instruction, coupled with exposure to group singing enrichments, enhance
on specific form of intelligence-spatial-temporal reasoning abilities. This
study suggests that music training, unlike listening, produces long-term modifications
in underlying neural circuitry in regions not primarily concerned with music
(Rauscher et al., 1997). Previous study in children
4-6 years old who participate in a 30 week parent-involved music curriculum
had shown score significantly higher control on the Bead Memory subset of Stanford-Binet
Intelligence scale. The Bead memory subtest measures both visual imagery and
sequencing strategies, mental process (Bilhartz et al.,
1999). Early musical instruction has been advantage to the 2 subtest of
spatial ability. The musicians who began music instruction before 5 years old
obtained significantly higher scores in the hidden figure test and the object
assembly subtest than did those who began later or never received formal music
training (Costa-Giomi et al., 2001). The study
of visuospatial perception and their imagery ability in adult musician and non-musician
found that musician has significantly shorter reaction time in both perception
and imagery condition of vertical discrimination task. Moreover, in imagery
condition of discrimination on the vertical dimension task seems to be greatly
improved on the musical expertise (Brochard et al.,
Physiological relationship: The positive effect of music listening to
spatial ability also has been study by the neurophysiological investigation
i.e., electroencephalogram and fMRI. When use the EEG coherence technique investigated
the effect of music listening on spatial-temporal task. The EEG was recorded
during solved the spatial-temporal ability; paper folding and cutting task from
Stanford-Binet battery after listening to text either Mozart K.448. The main
cortical areas that increase degree of synchrony were right fronto-temporal,
right temporo-parietal and centro-parietal in the both Mozart and text listening
conditions. Addition more cortical synchrony activity of Mozart than text condition
were appear in parietal, left occipital and left temporal. This mean some cortical
area activity bilaterally during task after listening to music when compare
to after listening to text (Sarnthein et al., 1997;
The combination of EEG with a functional brain mapping technique to localize
neural activates that are correlated with EEG power spectrum. Beta power was
significantly higher during listening to music than rest. There was a positive
correlation of regional Cerebral Blood Flow (rCBF) with beta power in both music
listening and rest condition in the premotor cortex and adjacent prefrontal
cortices bilaterally, the anterior portion of the precuneus and the anterior
cingulate cortex. An additional area for the music listening is the posterior
portion of the precuneus bilaterally. Beta power spectrum during music listening
may indicate the interaction of music with cognitive processes. The functional
neuroimaging studies in humans suggest that the premotor posterior parietal
connections are not only for motor control but also for cognitive processes.
A mental object-construction task activated the bilateral premotor and parieto-occipital
regions. The posterior portion of the precuneus (show in the blue area) is close
to the parietooccipital sulcus. These positive correlation areas can be interpreted
as premotor-posterior parietal connections. There may be an overlap of the neural
networks for musical and spatial processing.
The previous fMRI study investigated the transferable benefit of music training
to visuospatial task between professional orchestral musicians and non-musician.
The results indicated that orchestral musicians showed enhancing of activation
in Brocas area when performing a three-dimensional mental rotation (Sluming
et al., 2007). The Brocas area as know as related in visuospatial
network which researcher suggested during music practice may be an interaction
between brain development and acquisition and maintenance of musical visuospatial
skills which shape cortical tissue in Brocas brain area. These underlie
mechanism in musician mediates faster mental representation and better accuracy
of decision making of a three-dimensional mental rotation task (Sluming
et al., 2007). The studies in both behavioural and physiological
fields also caught attention in the relationship between music training and
spatial ability, therefore researchers try to explain the hypothesis underling
RELATIONSHIP OF THE MUSICAL TRAINING AND SPATIAL ABILITY
Although, the relationship between musical and cognition skills has received
some research attention, the music investigation and other cognitive skills
are largely correlated in nature. In general, it appears that spatial and musical
abilities are related.
Hemisphere lateralization: A possible explanation for the relationship
between music and spatial abilities refers to the right-hemispheric dominance
in both musical and spatial information processing. Barrett
and Barker Jr. (1973) study a music performance test and various test of
pattern perception. The results indicated the significant correlation between
music talent and spatial visualization and positive correlation with spatial
orientation. The Hausslers longitudinal study in 1985 investigated the
relationship between music talent and visual-spatial ability. The Hausslers
lab is one of the first groups that studied the relationship between music talent
and visual-spatial. Hassler and his group design a longitudinal study in 2 stages;
at beginning of puberty and one year later. The first stage, they demonstrated
that children age 9-14 year old (beginning of puberty) has significant relationship
between musical talent and spatial visualisation. One year later, they tested
the same group of participant and found that musical talent remains significant
related to spatial ability (Hassler et al., 1985).
The meta-analysis of medical and psychological studies suggests that spatial
information processing is also advantage functionally in the right hemisphere
of the brain (Vogel et al., 2003). Previous studies
concluded that high musical ability should be positively associated with better
performance on cognitive tasks mediated by the right hemisphere (Brandler
and Rammsayer, 2003; Sittiprapaporn et al., 2003,
2004a, b, 2005).
Trion model: Relationship of music and spatial-temporal reasoning can
predicate by a structured neural model of cortex. Dr. Gordon Shaw and his group
constructed the Trion model. The Trion model is a highly structure mathematics
realization of the Mountcastle organization principle with the column as the
basic neuronal network in mammalian cortex. The inherent spatial-temporal firing
patterns of interconnected groups of neurons have the built-in ability to recognize,
compare and find relationship among patterns (Sarnthein
et al., 1997). Musical acts as an exercise for exciting and priming
strengthen of neural firing pattern that has same firing patterns are used in
spatial-temporal reasoning task (Jausovec and Habe, 2004).
Multiple skills during musical training: The association stems from
the constellation of abilities that music lessons train and improve abilities
including focused attention and concentration, memorization, reading music,
fine-motor skills, expressing emotions and spatial ability (Schellenberg
and Hallam, 2005). During play musical instrument, musicians use multiple
modalities such as visual, auditory and motor to produce the music. That involves
reconstructing a pattern in which the elements, the notes, are organized in
a highly specialized spatial-temporal code. The encoding of music, musicians
encode both position of notes and their temporal sequence of musical events
that related to pitches, melody and rhythm (Gromko and Poorman,
1998). Musical training may affect the development of neural pathway relevant
to abilities that are influenced by environmental stimulation, such as certain
spatial abilities. The overlap of skills required for music and spatial cognition
may form the basis for refers to as cross-sensory perception and response which
involves relating information entering through one sense mode to analogous
information in another mode (Rauscher and Zupan, 2000).
Cross-modal interactions: Mini review of Zatorre
and Halpern (2005) proposed the cross-modal interactions processing
in one sensory modality can affect processing in another, either by increasing
or suppressing activity. Similar interactions also appear to occur if one or
both tasks are based not on perceptual but on imagined information. Also, Lotze
et al. (2003) investigated actual and imagined performance of Mozart's
violin concerto in G major (KV216) tasks in amateurs and professional violinists.
They found professionals exhibited higher activity of the right primary auditory
cortex during execution may reflect an increased strength of audio-motor associative
connectivity. The authors also suggested about development aspects of musical
skill acquisition which have observed cross-modality functional coupling with
musical training. During music training, the combined auditory feedback and
motor training on the musical instrument results in the co-activation of cortical
auditory and sensory-motor hand regions (Bangert et al.,
2006). It might be that such cross-modal coactivations will be strengthened
with increased musical training (Lotze et al., 2003;
Sittiprapaporn et al., 2005, 2006;
Sittiprapaporn, 2010, 2011,
2012a, b). This hypothesis was
supported by many present studies i.e. the study in preschool children who have
4 months of music training, students demonstrated improvement of their overall
score on the music task over time. The authors offer that music lesson seemed
to have a specific transfer effect on one particular type of spatial skill,
visual-motor integration. Also, they propose that the practice of fine movement/visual
perception in music practice association involves similar skills use in copying
geometric form. They suggested that music playing and practice likely strengthens
this co-ordination of visual and auditory sensory input and motor output. A
cross-modal theory of early music experience, music seems to be a medium that
strengthens the integration of auditory, visual and motor co-ordination (Orsmond
and Miller, 1999).
A cross modality hypothesis of relationship between music and spatial ability
was supported by another 2 neurophysiologic studies. The ERPs result of musician
when judge whether the last note of a five-note auditory musical sequence match
or mismatched the information simultaneously provided on a visual score show
that mismatch conditions differed from matching conditions. The ERPs amplitude
of early and late negative and positive component was larger for the unstable
than the stable ending condition. Moreover, electrophysiological data showed
that the auditory mismatch effect found in modulated by the expectations built
from the score. The authors gave explanation about these results of musician
that it seem to exist between visual and auditory musical code, so that the
representation built from the visual score interfere with the auditory perception
of the musical sequence (Schon and Besson, 2003). The
study of brain responses to the violations of visually induced auditory expectation.
Subjects were performing the symbol-to-sound matching paradigm.
In the symbol-to-sound matching paradigm, subjects indicated whether the visual
and auditory sequences were congruent or not by pressing the button. The comparison
of the ERPs data of to incongruent and to congruent auditory events showed a
bilateral frontal negativity and a mastoidal positively of the incongruent events
at about 110-120 msec after the onset of the sounds. This incongruence response
was followed by an N2b-like and a P3a-like deflection. Their results showed
that the brain reacts very quickly, after around 100 msec, to a violation of
an expectation induced by visually presented information by input received through
the auditory modality (Widmann et al., 2004).
The term spatial cognition is broadly defined as a specific type
of mental processing involving objects that exist in space. Neurologists examining
spatial deficits in adults have shown that the spatial factor is not a unidimensional
concept but includes spatial perception, memory, operations (e.g., rotation
or reflection of spatial representations) and construction (putting the parts
of an object together to create a whole) (Rauscher and Zupan,
2000). In filed of music, one type of spatial ability (spatial-temporal
reasoning) plays important role. One has to be able to create, maintain, transform
and relate complex mental images when playing music. From a meta-analysis the
over all result, the right hemisphere most involve in spatial tasks. When focus
on the handedness variable and spatial task. The right-hander shows the strongest
advantage in the right-hemisphere. The spatial visualization tasks showed no
hemispheric preference. On the other hand, the spatial orientation and the manual
manipulation tasks show advantage on Right hemisphere. This suggests that not
all spatial abilities are located in the right hemisphere (Vogel
et al., 2003). Within the field of mathematics, it has been argued
that mathematics and spatial ability are highly correlated with success in mathematics
education by using visual images to help for all sorts of mathematic problems
(Van Garderen, 2006). Hegarty and
Kozhevnikov (1999) have suggested that two different types of visual images
exist, visual imagery and spatial imagery. The visual imagery (pictorial) refers
to the representation of the visual appearance of an object, such as its shape,
colour or brightness, whereas the spatial imagery refers to the representation
of the spatial relationships between the parts of an object and the location
of objects in space or their movement. It has been suggested that all mathematical
tasks require spatial thinking (Hegarty and Kozhevnikov,
Higher level of visual processing: The higher level of visual processing
composes of two main cortical visual-spatial pathways; ventral pathway and dorsal
pathway. The ventral pathway carries information what an object is; static object
properties such as shape and colour. This pathway compose of the inferior longitudinal
fasciculus of axon that run out from the primary visual cortex and terminating
in the inferior temporal. The dorsal pathway carries information regarding where
an object is dynamic object properties such as motion and spatial relationships.
This pathway composes of the superior longitudinal fasciculus of axon that runs
out from primary visual cortex and terminating in the posterior parietal cortex.
Gender and spatial ability: Visual-spatial ability show fairly well
proven sex difference in favour of male. Previous studies supported these phenomena.
Study in the students of Ghana and Norway Universities by using 4 visual spatial
ability tests, one spatial perception and spatial visualization and 2 mental
rotation tasks. The result demonstrated significant sex difference in superiority
of males were found in both Ghana and Norway sample on spatial perception and
2 mental rotation visual-spatial ability categories (Amponsah
and Krekling, 1997). Previous study of three spatial memory tasks in 61
undergraduate students, researchers found that males perform significantly better
than females on the mental rotation task and in finding a hidden platform in
the virtual Morris water task (Astur et al., 2004).
This has been explained with reference to differences between the sexes in hemisphere
functioning, with males performing better than females on typical right hemisphere
processing tasks (Hugdahl et al., 2006).
Spatial mental imagery task: The experiment of Mellet
et al. (1996) spatial mental imagery task was image construction
task from both picture and propositional. That was designed for subject to do
the constructing mental imagery of object in form three-dimension cube assemblies
from verbal commands. The generation of visual images does not result from the
reactivation of previously stored memories but does result from on-line construction
of internal representations in the basis of the processing of verbal instructions
and their encoding in a visuospatial format. This method was designed to call
strongly on visual imagery. The results of the paradigm elicit activation of
posterior regions clearly distribution along an occipitoparietal axis. These
brain activated area; superior occipital and partial regions represent the dorsal
route which has role in the spatial processing of external visual stimuli.
Brain area specialization for music lie in several distributed neural circuitries
that are essential to the normal perception of the musical component and normal
function of music related activities. Musical functions recruit neural mechanisms
in both cerebral hemispheres and relate to multiple brain regions in each hemisphere.
Music processing may be distinguished by its characteristic dynamic activity
and the pattern of brain interactions it engenders rather than by the particular
brain regions that respond to it.
Aleman, A., M.R. Nieuwenstein, K.B. Bocker and E.H.F. de Haan, 2000. Music training and mental imagery ability. Neuropsychologia, 38: 1664-1668.
Amponsah, B. and S. Krekling, 1997. Sex differences in Visual-spatial performance among ghanaian and norwegian adults. J. Cross-Cult. Psychol., 28: 81-92.
CrossRef | Direct Link |
Astur, R.S., J. Tropp, S. Sava, R.T. Constable and E.J. Markus, 2004. Sex differences and correlations in a virtual Morris water task, a virtual radial arm maze and mental rotation. Behav. Brain Res., 151: 103-115.
Baeck, E., 2002. The neural networks of music. Eur. J. Neurol., 9: 449-456.
Bangert, M., T. Peschel, G. Schlaug, M. Rotte and D. Drescher et al., 2006. Shared networks for auditory and motor processing in professional pianists: Evidence from fMRI conjunction. Neuroimage, 30: 917-926.
Barrett, H.C. and H.R. Barker Jr., 1973. Cognitive pattern perception and musical performance. Percept Mot Skills, 36: 1187-1193.
Bhattacharya, J., H. Petsche and E. Pereda, 2001. Interdependencies in the spontaneous EEG while listening to music. Int. J. Psychophysiol., 42: 287-301.
Bilhartz, T.D., R.A. Bruhn and J.E. Olson, 1999. The effect of early music training on child cognitive development. J. Applied Dev. Psychol., 20: 615-636.
Brandler, S. and T.H. Rammsayer, 2003. Differences in mental abilities between musicians and Non-musicians. Psychol. Music, 31: 123-138.
CrossRef | Direct Link |
Brochard, R., A. Dufour and O. Despres, 2004. Effect of musical expertise on visuospatial abilities: Evidence from reaction times and mental imagery. Brain Cognit., 54: 103-109.
Chabris, C.F., 1999. Prelude or requiem for the Mozart effect? Nature, 400: 826-827.
Chan, A.S., Y.C. Ho and M.C. Cheung, 1998. Music training improves verbal memory. Nature, 396: 128-128.
Chartrand, J.P. and P. Belin, 2006. Superior voice timbre processing in musicians. Neurosci. Lett., 405: 164-167.
Cheek, J.M. and L.R. Smith, 1999. Music training and mathematics achievement. Adolescence, 34: 759-761.
PubMed | Direct Link |
Costa-Giomi, E., R. Gilmour, J. Siddell and E. Lefebvre, 2001. Absolute pitch, early musical instruction and spatial abilities. Annals NY Acad. Sci., 930: 394-396.
Gaser, C. and G. Schlaug, 2003. Brain structures differ between musicians and Non-musicians. J. Neurosci., 23: 9240-9245.
Direct Link |
Gromko, J.E. and A.S. Poorman, 1998. The effect of music training on preschoolers' Spatial-temporal task performance. J. Res. Music Educ., 46: 173-181.
Direct Link |
Hassler, M., N. Birbaumer and A. Feil, 1985. Musical talent and Visual-spatial abilities: A longitudinal study. Psychol. Music, 13: 99-113.
Hegarty, M. and M. Kozhevnikov, 1999. Types of Visual-spatial representations and mathematical problem solving. J. Educ. Psychol., 91: 684-689.
CrossRef | Direct Link |
Hugdahl, K., T. Thomsen and L. Ersland, 2006. Sex differences in Visuo-spatial processing: An fMRI study of mental rotation. Neuropsychologia, 44: 1575-1583.
Jausovec, N. and K. Habe, 2004. The influence of auditory background stimulation (Mozart's sonata K. 448) on visual brain activity. Int. J. Psychophysiol., 51: 261-271.
Kizkin, S., R. Karlidag, C. Ozcan and H.I. Ozisik, 2006. Reduced P50 auditory sensory gating response in professional musicians. Brain Cognit., 61: 249-254.
Lamprecht, R. and L. Joseph, 2004. Structural plasticity and memory. Nat. Rev., Neurosci., 5: 45-54.
Lotze, M., G. Scheler, H.R. Tan, C. Braun and N. Birbaumer, 2003. The musician's brain: Functional imaging of amateurs and professionals during performance and imagery. NeuroImage, 20: 1817-1829.
Mellet, E., N. Tzourio, F. Crivello, M. Joliot, M. Denis and B. Mazoyer, 1996. Functional anatomy of spatial mental imagery generated from verbal instructions. J. Neurosci., 16: 6504-6512.
Direct Link |
Norton, A., E. Winner, K. Cronin, K. Overy, D.J. Lee and G. Schlaug, 2005. Are there pre-existing neural, cognitive, or motoric markers for musical ability? Brain Cognition, 59: 124-134.
Orsmond, G.I. and L.K. Miller, 1999. Cognitive, musical and environmental correlates of early music instruction. Psychol. Music, 27: 18-37.
Pantev, C., M. Hoke, B. Lutkenhoner and K. Lehnertz, 1989. Tonotopic organization of the auditory cortex: Pitch versus frequency representation. Science, 246: 486-488.
Patel, A.D. and E. Balaban, 2000. Temporal patterns of human cortical activity reflect tone sequence structure. Nature, 404: 80-84.
Peretz, I. and R.J. Zatorre, 2005. Brain organization for music processing. Ann. Rev. Psychol., 56: 89-114.
Peretz, I., 2002. Brain specialization for music. Neuroscientist, 8: 372-380.
Direct Link |
Rauscher, F.H. and M.A. Zupan, 2000. Classroom keyboard instruction improves kindergarten children's spatial-temporal performance: A field experiment. Early Childhood Res. Q., 15: 215-228.
Rauscher, F.H., G.L. Shaw and C.N. Ky, 1993. Music and spatial task performance. Nature, 365: 611-611.
Rauscher, F.H., G.L. Shaw, L.J. Levine, E.L. Wright, W.R. Dennis and R.L. Newcomb, 1997. Music training causes long-term enhancement of preschool children's spatial-temporal reasoning. Neurol. Res., 19: 2-8.
Direct Link |
Sarnthein, J., A. von Stein, P. Rappelsberger, H. Petsche, F.H. Rauscher and G.L. Shaw, 1997. Persistent patterns of brain activity: An EEG coherence study of the positive effect of music on spatial-temporal reasoning. Neurol. Res., 19: 107-116.
Direct Link |
Scheler, G., L. Jancke, Y. Huang and H. Steinmetz, 1995. In vivo evidence of structural brain asymmetry in musicians. Science, 267: 699-701.
Schellenberg, E.G. and S. Hallam, 2005. Music listening and cognitive abilities in 10- and 11-year-olds: The blur effect. Ann. N. Y. Acad. Sci., 1060: 202-209.
CrossRef | Direct Link |
Schellenberg, E.G., 2004. Music lessons enhance IQ. Psychol. Sci., 15: 511-514.
Schellenberg, E.G., 2005. Music and cognitive abilities. Curr. Directions Psychol. Sci., 14: 317-320.
Schmithorst, V.J. and S.K. Holland, 2003. The effect of musical training on music processing: A functional magnetic resonance imaging study in humans. Neurosci. Lett., 348: 65-68.
Schon, D. and M. Besson, 2003. Audiovisual interactions in music reading. A reaction times and event-related potentials study. Ann. N. Y. Acad. Sci., 999: 193-198.
CrossRef | PubMed |
Seung, Y., J.S. Kyong, S.H. Woo, B.T. Lee and K.M. Lee, 2005. Brain activation during music listening in individuals with or without prior music training. Neurosci. Res., 52: 323-329.
Shahin, A., D.J. Bosnyak, L.J. Trainor and L.E. Roberts, 2003. Enhancement of neuroplastic P2 and N1c auditory evoked potentials in musicians. J. Neurosci., 23: 5545-5552.
Direct Link |
Shahin, A., L.E. Roberts and L.J. Trainor, 2004. Enhancement of auditory cortical development by musical experience in children. Neuroreport, 15: 1917-1921.
Sittiprapaporn, W., 2010. Music sound and picture perception: Topography of the human brain electrical activity. Int. J. Comput. Sci., 7: 1-9.
Direct Link |
Sittiprapaporn, W., 2011. P300 topography maps of tone perception in the tonal speaker brain. Aust. J. Basic Applied Sci., 5: 1982-1987.
Direct Link |
Sittiprapaporn, W., 2012. Source localization of preattentive processing for different vowel duration changes with contour tones in monosyllabic thai words. J. Applied Sci., 12: 1580-1587.
CrossRef | Direct Link |
Sittiprapaporn, W., 2012. Cortical activation of level-to-contour tone changes in different vowel duration indexed by mismatch negativity. J. Applied Sci., 12: 1588-1595.
CrossRef | Direct Link |
Sittiprapaporn, W., C. Chindaduangratn and N. Kotchabhakdi, 2004. Brain electrical activity during the pre-attentive perception of speech sounds in tonal languages. Songklanakarin J. Sci. Tech., 26: 439-445.
Direct Link |
Sittiprapaporn, W., C. Chindaduangratn and N. Kotchabhakdi, 2004. Long- term memory traces for familiar spoken words in tonal language as revealed by the mismatch negativity. Songklanakarin J. Sci. Tech., 26: 779-786.
Sittiprapaporn, W., C. Chindaduangratn and N. Kotchabhakdi, 2006. Pattern of language-related potential maps in consonant-vowel (cv) syllables. Songklanakarin J. Sci. Tech., 28: 911-920.
Direct Link |
Sittiprapaporn, W., C. Chindaduangratn, M. Tervaniemi and N. Kotchabhakdi, 2003. Preattentive processing of lexical tone perception by the human brain as indexed by the mismatch negativity paradigm. Ann. NY. Acad. Sci., 999: 199-203.
CrossRef | Direct Link |
Sittiprapaporn, W., M. Tervaniemi, C. Chindaduangratn and N. Kotchabhakdi, 2005. Preattentive discrimination of vowel across-and within-category- change in consonant-vowel syllable. NeuroReport, 16: 1513-1518.
PubMed | Direct Link |
Sluming, V., J. Brooks, M. Howard, J.J. Downes and N. Roberts, 2007. Broca's area supports enhanced visuospatial cognition in orchestral musicians. J. Neurosci., 27: 3799-3806.
Direct Link |
Thompson, W.F., E.G. Schellenberg and G. Husain, 2001. Arousal, mood and the Mozart effect. Psychol. Sci., 12: 248-251.
Trainor, L.J., Shahin, A. and L.E. Roberts, 2003. Effects of musical training on the auditory cortex in children. Ann. N. Y. Acad. Sci., 999: 506-513.
Tramo, M.J., 2001. Biology and music. Music of the hemispheres. Science, 291: 54-56.
Van Garderen, D., 2006. Spatial visualization, visual imagery and mathematical problem solving of students with varying abilities. J. Learn. Disabil., 39: 496-506.
Vogel, J.J., C.A. Bowers and D.S. Vogel, 2003. Cerebral lateralization of spatial abilities: A meta-analysis. Brain Cogn., 52: 197-204.
Widmann, A., T. Kujala, M. Tervaniemi, A. Kujala and E. Schroger, 2004. From symbols to sounds: Visual symbolic information activates sound representations. Psychophysiology, 41: 709-715.
Zatorre, R.J. and A.R. Halpern, 2005. Mental concerts: Musical imagery and auditory cortex. Neuron, 47: 9-12.