Przetwarzanie informacji muzycznej w mózgu

Przetwarzanie informacji muzycznej w mózgu

Przetwarzanie
informacji muzycznej w
mózgu
NEUROESTETYKA
PIOTR PRZYBYSZ
Wykład monograficzny. UAM Poznań 2010
Neuroestetyka muzyki?
•
Neuroestetyka sztuk wizualnych a neuropsychologia
muzyki
•
Czy prawa i reguły przetwarzania przez mózg obrazu i
dźwięku różnią się?
•
Czy istnieją wspólne zasady estetyczne rządzące
poczuciem piękna w muzyce i sztukach wizualnych?
•
Przekaz muzyczny w sztukach wielomodalnych
Dźwięk i słyszenie
•
Muzyka to złożona sekwencja dźwięków uporządkowanych w
czasie pod względem głośności i wysokości
•
Dźwięk:
(1) jako zjawisko fizyczne (=fala dźwiękowa) jest wyrażany
przez obiektywne cechy dźwięku:
a) częstotliwość,
b) natężenie,
c) widmo,
d) czas trwania,
(II) jako zjawisko psychologiczne (=wrażenie dzwiękowe)
charakteryzowany jest przez
a) wysokość,
b) głosność,
c) barwę,
d) czas trwania
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Zagadnienie słuchu absolutnego
•
Słuch absolutny = zdolność do odczytania
wysokości dźwięku bez porównywania z
dźwiękiem odniesienia.
•
Własność pozamuzyczna, akustyczna, percepcji
słuchowej.
•
Dotyczy max. 0,1 % populacji (duże
rozbieżności danych); częściej spotykany w
środowisku osób muzykujących (w szkołach
muzycznych ok 15 %); znacznie częściej
spotykany wśród nacji posługujących się
językami tonalnymi (np. w chińskich szkołach
muzycznych do 60 % osób, które zaczęły
wcześnie edukację).
zattore feature
4/3/05
10:11 am
artists on science
Page 312
Droga słuchowa (1)
Music,
the food of
neuroscience?
Playing, listening to and
creating music involves
practically every cognitive
function. Robert Zatorre
explains how music can
teach us about speech,
brain plasticity and even
the origins of emotion.
W
Figure 1 The processing of sound waves from a musical instrument. After being transduced into neural
impulses by the inner ear, information travels through several waystations in the brainstem and midbrain
to reach the auditory cortex. The auditory cortex contains distinct subregions that are important for
decoding and representing the various aspects of the complex sound. In turn, information from the auditory cortex interacts with many other brain areas, especially the frontal lobe, for memory formation and
interpretation. The orbitofrontal region is one of many involved in emotional evaluation. The motor
cortex is involved in sensory–motor feedback circuits, and in controlling the movements needed to
produce music using an instrument.
e tend to consider art and culture from
a humanistic or historical perspective
rather than a biological one. Yet these products of human cognition must have their
origin in the function and structure of the
human nervous system. As such, they
should be able to yield valuable scientific
insights. This line of reasoning is nowhere
more evident than in the contemporary
interest in the neuroscience of music.
Music provides a tool to study numerous
aspects of neuroscience, from motor-skill
learning to emotion. Indeed, from a psychologist’s point of view,listening to and producing music involves a tantalizing mix of
practically every human cognitive function.
Even a seemingly simple activity, such as
humming a familiar tune, necessitates
complex auditory pattern-processing mechanisms, attention, memory storage and
retrieval, motor programming, sensory–
motor integration, and so forth (Fig. 1).
Likewise, the musician does not consider
music to be monolithic, but recognizes
within it multiple features including
melodies, chords, themes, riffs, rhythms and
tempos. This complexity — both psychological and musicological — makes music a
challenging topic for a scientific research
programme. Increasing numbers of investigators are convinced that music can yield
valuable information about how the brain
NATURE | VOL 434 | 17 MARCH 2005 | www.nature.com/nature
312
©2005 Nature Publishing Group
Droga słuchowa (1I)
PRZESTRAJANIE MÓZGU
POSZCZEGÓLNE KOMÓRKI w mózgu reagujà optymalnie
na okreÊlonà wysokoÊç dêwi´ku, czyli cz´stotliwoÊç (a). Komórki zmieniajà swoje dostrojenie, kiedy zwierz´ si´ uczy,
˝e okreÊlony ton jest dla niego wa˝ny (b). Takie komórkowe
przystosowanie modyfikuje „map´ cz´stotliwoÊci” mózgu
szczura, by zwi´kszyç obszar kory przetwarzajàcy ton o du˝ym znaczeniu dla zwierz´cia – na przyk∏ad poszerza rejon
aktywowany przez dêwi´k o cz´stotliwoÊci 8 kHz, jeÊli ta
akurat jest istotna (c).
Numer komórki
a
2
C
D
3
4
5
6
7
E
F
G
A
H
Reakcja
1
WysokoÊç dêwi´ku
b
Cz´stotliwoÊç treningowa
140
Najlepsza reakcja
Reakcja (liczba wy∏adowaƒ
na sekund´)
120
Najlepsza
reakcja
100
80
60
Przed treningiem
Po treningu
40
20
0
–20
0.1
1
10
100
Cz´stotliwoÊç (kHz)
c
32
16
32 16
8
8
4
2
4
Przed treningiem (Êrodkowa
cz´stotliwoÊç oktaw w kilohercach)
2 Po treningu
go, natomiast przez pozosta∏e 10 lat ˝ycia zachowa∏ zdolnoÊç
pisania muzyki. Tak wi´c przypuszczenia o niezale˝nym przetwarzaniu mogà byç s∏uszne, choç nowsze badania prowadzà
do bardziej wywa˝onej koncepcji, w której przyk∏ada si´ wi´kszà wag´ do cech wspólnych muzyki i j´zyka – funkcji komunikacyjnej oraz sk∏adni, czyli zbioru regu∏ okreÊlajàcych w∏aÊciwe kombinacje elementów (odpowiednio nut lub s∏ów).
Na podstawie wyników badaƒ z wykorzystaniem techniki
54
ÂWIAT NAUKI GRUDZIE¡ 2004
neuroobrazowania Aniruddh D. Patel z Neurosciences Institute w San Diego stwierdzi∏, ˝e w p∏acie czo∏owym istnieje
obszar, który zajmuje si´ sk∏adnià zarówno muzyki, jak i j´zyka, natomiast pozosta∏e okolice mózgu odpowiadajà za inne aspekty przetwarzania i j´zyka, i muzyki.
Badania obrazowe dajà tak˝e doÊç precyzyjny wglàd w to,
jak mózg reaguje na muzyk´. Ich wyniki naj∏atwiej zrozumieç, jeÊli weêmie si´ pod uwag´ sposób przekazywania
przez ucho dêwi´ków do mózgu [ramka na poprzedniej stronie]. Podobnie jak inne zmys∏y s∏uch jest zorganizowany hierarchicznie. Sk∏ada si´ z ciàgu neuronalnych stacji przetwarzania bodêca – od ucha a˝ do poziomu najwy˝szego, czyli
s∏uchowych obszarów kory mózgu. Przetwarzanie dêwi´ków
takich jak te, z których sk∏ada si´ muzyka, zaczyna si´ w uchu
wewn´trznym (Êlimaku), które rozk∏ada z∏o˝one dêwi´ki, na
przyk∏ad brzmienie skrzypiec, na poszczególne cz´stotliwoÊci.
Âlimak przekazuje te informacje dalej jako sekwencje wy∏adowaƒ neuronalnych, które biegnà przez w∏ókna nerwu s∏uchowego nastrojone na ró˝ne cz´stotliwoÊci. Wreszcie sekwencje te docierajà do kory s∏uchowej p∏ata skroniowego. Na
okreÊlone cz´stotliwoÊci reagujà ró˝ne komórki. Po∏o˝one
obok siebie majà zaz´biajàce si´ krzywe strojenia (profile
wra˝liwoÊci na cz´stotliwoÊç). W rezultacie, poniewa˝ sàsiadujàce ze sobà komórki sà nastrojone na podobne cz´stotliwoÊci, na powierzchni kory s∏uchowej tworzy si´ „mapa cz´stotliwoÊci” [ramka z lewej].
Sam odbiór muzyki jest jednak bardziej z∏o˝ony. Muzyka to
sekwencja dêwi´ków, a jej percepcja polega na spostrzeganiu relacji pomi´dzy nimi. W przetwarzanie ró˝nych aspektów muzyki w∏àczonych jest wiele obszarów mózgu. Weêmy
na przyk∏ad dêwi´k, który ma zarówno okreÊlonà cz´stotliwoÊç, jak i g∏oÊnoÊç. KiedyÊ badacze przypuszczali, ˝e wykrycie danej cz´stotliwoÊci zawsze wywo∏uje takie same reakcje komórek, które sà na nià nastrojone.
Jednak w drugiej po∏owie lat osiemdziesiàtych, gdy wspólnie z Thomasem M. McKennà pracowa∏em w moim laboratorium w University of California w Irvine, zakwestionowaliÊmy ten poglàd, zbadawszy kontur melodii, czyli wzór
wznoszenia si´ i opadania linii melodycznej, który stanowi
podstaw´ ka˝dej melodii. NapisaliÊmy melodie sk∏adajàce
si´ z tych samych pi´ciu dêwi´ków, ale ró˝niàce si´ konturem,
i rejestrowaliÊmy reakcje pojedynczych neuronów w korze s∏uchowej kotów. Okaza∏o si´, ˝e reakcje komórek ró˝ni∏y si´
w zale˝noÊci od konturu. Zale˝a∏y od umiejscowienia danego dêwi´ku w melodii. Komórki mogà silniej reagowaç na
dêwi´k poprzedzany przez inne ni˝ na dêwi´k rozpoczynajàcy sekwencj´. Ponadto reagujà na ten sam dêwi´k inaczej,
gdy jest on elementem konturu wznoszàcego si´ (dêwi´ki coraz wy˝sze), a inaczej, kiedy wchodzi w sk∏ad konturu opadajàcego lub mieszanego. Wyniki te pokazujà, ˝e przebieg
melodii ma du˝e znaczenie – przetwarzanie s∏uchowe nie
polega na prostym odwzorowaniu dêwi´ku jak w telefonie
czy zestawie hi-fi.
Choç wi´kszoÊç badaƒ koncentruje si´ na melodii, rytm
(wzgl´dny czas trwania dêwi´ków i odst´pów mi´dzy nimi),
harmonia (wzajemna relacja wysokoÊci co najmniej dwóch
równoczeÊnie brzmiàcych tonów) i barwa dêwi´ku (charakterystyczna ró˝nica w brzmieniu tego samego tonu wytwarzanego przez dwa ró˝ne instrumenty) tak˝e sà obiektem naukowych dociekaƒ. Wyniki wielu badaƒ nad rytmem sugerujà,
LAURIE GRACE
Mapy mózgowe i ich przestrajanie
Where Does the Brain “Hear”?
Left Hemisphere: Rhythm
Right Hemisphere: Pitch and Melody
Music is processed in various areas of the brain, which
change depending on the focus of the listener and his or
her experience. When the brain of an amateur musician
processes simple rhythmic relations in a melody, such as
the variance in length between certain tones, he utilizes
the premotor, or movement-preparation, regions as well as
sections of the parietal lobe in the left hemisphere. If the
temporal relations among the tones are more complex,
premotor and frontal lobe regions in the right hemisphere
become active. In both cases, the cerebellum (which is
commonly supposed to be involved in movement control)
also participates. In contrast, musicians who are discerning between rhythms or meter predominantly employ parts
of the frontal and temporal lobes in the right hemisphere.
Rhythmic relations display a similar picture: people who
are not musically trained process in the left side, whereas experienced musicians generally do so in the right.
When a musical layperson compares different pitches, the
right posterior frontal lobe and right upper temporal lobe
convolution are active. The tones are stored for future use
and comparison in the auditory working memory located
in the temporal region. The middle and lower areas of the
temporal lobe are also active when processing more complex musical structures or structures being stored in memory for a longer period. In contrast, professional musicians
show increased activity in the left hemisphere when they
are differentiating among pitches or perceiving chords.
When the listener is focusing on whole melodies
rather than individual tones or chords, entirely different
sections of the brain become active: in addition to the primary and secondary auditory cortices, the auditory associative regions in the upper temporal lobe are at work. In
this case, the activity is once again concentrated in the
right hemisphere.
Muzyka w mózgu
Zasady przetwarzania muzyki:
a) rozproszoność/asymetria półkulowa (ograniczona),
b) hierarchiczność,
c) modularność.
Left
Right
Parietal lobe
Rhythm
Rhythm
Frontal
lobe
Melodies
Frontal
lobe
m
yth Temporal
Rh
lobe
Occipital
lobe
Cerebellum
Rhythm
Occipital
lobe
Complex
musical
structures
Despite the gaps, scientists are piecing together
a general understanding of where the brain “hears”
music. We know, for example, that both sides, or
hemispheres, of the brain are involved, though
asymmetrically. For a long time, it was common to
believe in a distinct division between the left brain’s
processing of language (the side that also handles
reasoning tasks) and the right brain’s processing of
music (the half that contains emotional and spatial
information). Many medical textbooks included
this simplified theory until the 1980s. In recent
years, however, researchers have established that
injuries to either side can impair musical abilities.
This happens not only in the case of damage to the
auditory areas in the temporal lobe but also when
associated regions of the frontal lobe and the pari-
28
Auditory
cortex
Parietal lobe
Cerebellum
M
elo
d
ies
Pitch
comparison
Temporal
lobe
Auditory
working
memory
etal regions are affected. (If the Heschl’s gyrus is destroyed on both sides, incidentally, total deafness
does not occur. Instead the ability to distinguish between various sounds is severely impaired. A patient with this condition would not be able to understand language or perceive music at all.)
Early stages of music perception, such as pitch
(a note’s frequency) and volume, occur in the primary and secondary auditory cortices in both
hemispheres. The secondary auditory areas, which
lie in a half-circle formation around the primary
auditory cortex, process more complex music patterns of harmony, melody and rhythm (the duration of a series of notes). Adjoining tertiary auditory areas are thought to integrate these patterns
into an overall perception of music. Farther for-
COPYRIGHT 2003 SCIENTIFIC AMERICAN, INC.
SCIENTIFIC AMERICAN MIND
THOMAS BRAUN G&G
•Z
© 2003 Nature Publishing Group http://www.nature.com/natureneuroscience
REVIEW
Figure 1 A modular model of music processing.
Each box represents a processing component,
and arrows represent pathways of information
flow or communication between processing
components. A neurological anomaly may either
damage a processing component (box) or
interfere with the flow of information between
two boxes. All components whose domains
appear to be specific to music are in green;
others are in blue. There are three neurally
individuated components in italics—rhythm
analysis, meter analysis and emotion expression
analysis—whose specificity to music is currently
unknown. They are represented here in blue, but
future work may provide evidence for
representing them in green.
Acoustic input
Acoustic analysis
Temporal
organization
Pitch organization
Tonal
encoding
Interval
analysis
Contour
analysis
Rhythm
analysis
Meter
analysis
Acoustic-tophonological
conversation
foot (thus a direct connection to tapping in
Emotion
Musical
Phonological
Fig. 1; see accompanying review36 in this
expression
lexicon
lexicon
issue). Both the melodic and temporal pathanalysis
ways send their respective outputs to either
the ‘musical lexicon’ or the ‘emotion expression analysis’ component. The musical lexicon
Associative
Vocal plan
memories
is a representational system that contains all
formation
the representations of the specific musical
phrases to which one has been exposed during
one’s lifetime. The same system also keeps a
Speaking
Singing
Tapping
record of any new incoming musical input.
Accordingly, successful recognition of a familIvelisse Robles
iar tune depends on a selection procedureIsabelle
that Peretz & Max Colthear (2003) Modularity of music processing, Nature Review Neuroscience, vol.6, iss. 7.
takes place in the musical lexicon. The output of the musical lexicon three new output modules again stems from the study of neurological
can feed two different components, depending on task requirements. patients: singing performance in aphasic patients38 and tapping abiliIf the goal is to sing a song like “Happy Birthday,” the corresponding ties in adults suffering from congenital amusia39. Thus, our proposed
melody, represented in the musical lexicon, will be paired with its asso- modular architecture for processing music provides a plausible frameciated lyrics that are stored in the phonological lexicon and will be work for further investigating the neural mechanisms of music protightly integrated and planned in a way that is suitable for vocal pro- cessing.
duction. If the task requires retrieving nonmusical information about
a musical selection, such as naming the tune or retrieving a related ACKNOWLEDGMENTS
Based on research supported by grants from the Natural Sciences and Engineering
experience from memory, the associated knowledge stored in the ‘asso- Research Council of Canada and the Canadian Institutes of Health Research to I.P.
ciative memories’ component will be invoked.
We thank C. Palmer and T. Griffiths for insightful comments made on an earlier
In parallel with memory processes, but independently, the percep- draft.
tual modules will feed their outputs into an emotion expression analyReceived 18 March; accepted 21 April 2003
sis component, allowing the listener to recognize and experience the Published online 25 June 2003; doi:10.1038/nn1083
37
emotion expressed by the music . This emotional pathway also contributes to recognition via the musical lexicon. Emotion expression 1. Handel, S. Listening: an Introduction to the Perception of Auditory Events (MIT
press, Cambridge, Massachusetts, 1989).
analysis is a pivotal processing component because music has the
power to elicit strong emotional responses. It takes as input emotion- 2. Bregman, A. Auditory Scene Analysis. The Perceptual Organization of Sound. (MIT
press, London, 1990).
specific musical features, such as mode (e.g. major or minor) and 3. Zatorre, R. & Peretz, I. (eds.) The Biological Foundations of Music (NY Acad. Sci.,
New York, 2001).
tempo (e.g. slow or fast) as computed by the melodic and temporal
Fodor, J. The Modularity of Mind (MIT press, Cambridge, Massachusetts, 1983).
pathways, respectively. What is currently unclear is to what extent this 4.
5. Fodor, J. The Mind Doesn’t Work That Way (MIT press, Cambridge, Massachusetts,
emotion expression analysis component is specific to music as
2001).
opposed to being involved in more general kinds of emotional pro- 6. Coltheart, M. Modularity and cognition. Trends Cogn. Sci. 3, 115–120 (1999).
7. Gardner, H. Musical intelligence. in Frames of Mind (ed. Gardner, H.) 31–58 (Basic
cessing. A patient who could recognize pieces of music but could not
Books, New York, 1983).
respond emotionally to them, while being able to respond emotionally 8. Jackendoff, R. Consciousness and the Computational Mind (MIT Press, Cambridge,
Massachusetts, 1987).
to other media, would be informative here.
9. Peretz, I. & Morais, J. Music and modularity. Contemporary Music Rev. 4, 277–291
In sum, we propose a modular functional architecture for music
(1989).
processing that comprises several component modules. Our model 10. Peretz, I. et al. Functional dissociations following bilateral lesions of auditory cortex.
117, 1283–1302 (1994).
(Fig. 1) also describes the pathways of information flow among these 11. Brain
Peretz, I., Belleville, S. & Fontaine, S. Dissociations entre musique et langage après
component modules. The characterization of each box and arrow repatteinte cérébrale: un nouveau cas d’amusie sans aphasie. Can. J. Exp. Psychol. 51,
354–368 (1997).
resented in the model has been provided by the detailed study of
12. Griffiths, T.D. et al. Spatial and temporal auditory processing deficits following right
brain-damaged patients with selective impairments or preservations
hemisphere infarction: a psychophysical study. Brain 120, 785–794 (1997).
of particular musical abilities (for review, see ref. 24). The inclusion of 13. Wilson, S.J. & Pressing, J. Neuropsychological assessment and the modeling of
Przypadek Maurice Ravela
•
Po 1927 utracił on zdolność powtarzania ze słuchu melodii, zapisywania
(agrafia) i rozumienia (afazja) i czytania (alexia) zapisanej muzyki
(uszkodzenia skroniowo-ciemieniowe lewej półkuli), poruszania się w
skoordynowany sposób (apraksja).
•
Zachował zdolności w zakresie rozpoznawania melodii (np. swoich
utworów), wychwytywania błędów.
•
•
Amuzja
Przypadki odmienne: W. Shebalin - afazja bez amuzji
articles
Mózgi muzyków i nie muzyków
d
e
b
© 2002 Nature Publishing Group http://neurosci.nature.com
© 2002 Nature Publishing Group http://neurosci.nature.com
a
articles
Fig. 1. The auditory stimulus, evoked magnetic fields and cortical
anatomy. (a) Stimulus waveform. A modulation frequency of 26–37 Hz
was superimposed on sinusoidal tones with carrier frequencies of
100–5,600 Hz to measure the responses to tone onset and to each modulation cycle. (b) Typical averaged response at an MEG sensor over the
right auditory cortex shows middle latency onset components P30m and
P50m, long latency components N100m and the sustained field (SF). The
responses to the modulation cycles appear superimposed on the SF.
(c) Typical early N19m-P30m response of the PAC after deconvolution
of the modulated signals. (d, e) Source model with one equivalent dipole
in each hemisphere depicted in sagittal and transversal T1-weighted MRI
images. The transversal section is parallel to the supratemporal plane.
The source activity is modeled with dipoles drawn in the left and right
hemispheres. (f) Three-dimensional (3D) gray matter surface reconstruction between
of the right
The FTS defines
the activity,
anterioramHG
boundary
and volume and musical aptitude. (a) The N19m-P30m
Fig. 4. Correlations
earlyHG.
neurophysiological
source
gray matter
the most
posterior
HS defines
themean
posterior
boundary.
The
first transdipole moment
was strongly
correlated
with the
gray matter
volume
of amHG.
Values were averaged over the right and left hemispheres.
verseraw
HGscore
is sometimes
by(AMMA
the SI, atest)
shallow
sulcuscorrelated
which does
notboth the N19m-P30m dipole moment (b) and the gray
(b, c) The tonal
of musicaldivided
aptitude
was highly
with
matter volume
of amHG
(c).full length.
extend
over its
Tekst
and amateur musicians showed an intermediate gray matter
Influence of external variables
volume (189–798 mm3). The total volume of HG, including
We found no influence of the covariates sex, age or head size
signal
that awas
115variance
± 18% and
larger
over
white and average
gray matter,
showed
larger
could
notall frequencies
on either theinearly dipole amplitudes or on the gray matter volthegroups
right(non-musicians,
hemisphere (F1,955–4,694
P <3; 0.0001)
87of±amHG.
17% To exclude influences of attention during MEG
1,22 = 73.4,mm
separate the
ume
profes- and
3; hemisphere
larger in the
left
(F1,22 = 43.6,
0.0001).recording
Non-musiand of the frequency modulation in the stimulus, we
sionals, 2,629–6,297
mm
amateurs, 2,151–7,603
mmP3).<The
f
cians,
by contrast,
didshowed
not have
significantly
larger dipole
carriedampliout two additional control sessions in a subgroup of 24
asymmetry
measures
(Methods)
only
one significant
stochastically
effect: the tudes
total volume
HG than
was 14%
larger
the right hemiin the of
right
in the
leftinhemisphere
(5 ± 9%,
F1,11 = 3.6, selected subjects. While watching a video, subjects
sphere of professional
musicians
(right, 3,986
± 305
mm3; left, were
n.s). In
amateur
musicians,
dipole
amplitudes
19detected
± 14% deviant tones of a different frequency (1,100 Hz
instead
the
3,468 ± 263
mm3;in!HG
0.14 ±than
0.04;they
F1,11were
= 11.7,
< 0.01).
larger
the=right
inPthe
left hemisphere
(Fof
= standard 500 Hz) and indicated them by button
c
1,12attention
press in the
experiment. We found no significant effect
17.8, P < 0.01). This was significant at three frequencies
(100 Hz,
of attention on the primary N19m-P30m component. Within
Correlation with musical aptitude
500
Hz
and
1,100
Hz,
P
<
0.05).
noise limits, the N19m-P30m signals for the onset of pure sinuFor all three groups, there was a high correlation between the
a pronounced
difference
between
lateagreed with the signals deconvoluted from the
soidaland
tones
N19m-P30m There
signal was
amplitude
and musical
aptitude
as mea-the early
auditory
cortical
Whereas
the primary
early N19m-P30m
commodulated
tones23,40.
sured by the
AMMA
tonal responses.
test (Fig. 4b).
Both the
source activity
and much
the tonal
score
musical aptitude
plex was
larger
inofmusicians,
the latecomN100m component,
pletely separated
the evoked
professional
musicians
the non- tones,
DISCUSSION
which was
by the
onset offrom
the sinusoidal
showed
musicians.similar
The amateur
musicians
showed
an intermediate
Here(Fig.
we found
amplitudes
in all three
groups
over all frequencies
3b). a large difference in the early neurophysiological
range of musical aptitude and dipole amplitudes that overactivity of the auditory cortex in musicians versus non-musicians,
For all groups,
N100m
largest around 1,000
Hz.
frequency andP,
ranged
from 78%
Hz,HG,
P < 0.0001)
to 144%
Schneider
Scherg
M, (1,100
Dosch
Specht
HJ, Gutschalk
A,the
Rupp
A.was
Morphology
of Heschl's
reflects
lapped
with the two other
groups.
Within
groups, the correlausing simplegyrus
tonal stimuli.
In addition, we found strong correla(5,600 Hz, P < 0.0001).
tion was significant for non-musicians (r = 0.55, P < 0.05), but
tions of this activity with the gray matter volume of amHG and
We next averaged
the peak-to-peak
N19m-P30m
Morphology
Heschl’s
gyrus
notmusicians.
for amateurs
(r =Nat
0.19, of
n.s.)
or professionals
(r = 0.05,
n.s.).
with musical aptitude. Using partial correlations, we showed that
enhanced
activation
in the auditory
cortexdipole
of
Neurosci.
2002
Jul;5(7):688-94.
amplitudes for each group (Fig. 3a). Amateur musicians
large neurophysiological
difference
betweenthemusicians
In general,The
professional
musicians had high AMMA
scores, high
gray matter volume of amHG was the key parameter influsignal amplitudes
and large gray
matter
of amHG.
early evoked response of the auditory cortex. The
showed an intermediate average increase of 37 ± 11% over nonand non-musicians
at the
levelvolumes
of the PAC
coincidedencing
with athe
large
When analysis was restricted to amateur and professional musilarger gray matter volume in professional musicians was most
musicians (F1,23 = 7.8, P < 0.05). The difference
cians,
the
correlation
was
significant
(r
=
0.52,
P
<
0.01).
pronounced
for amHG (130% greater than in non-musicians)
between amateur musicians and non-musicians
Similarly, the gray matter volume of amHG was highly corand dropped to 37% more volume than in non-musicians when
was significant only in the low frequency range
related with musical aptitude (Fig. 4c). Within groups, the corthe whole HG was used for anatomical reference. Together with
(<1,000 Hz, P < 0.05). There was a frequency !
relation was significant for non-musicians (r = 0.71, P < 0.001)
evidence from previous EEG20 and MEG21–23 studies that localgroup interaction (F 10,165 = 2.9, P < 0.01) that
and amateurs (r = 0.56, P < 0.05), but not for professionals
ized the origin of the primary auditory-evoked N19-P30 source
ranged from 77% (100 Hz, P < 0.01) to 14%
(r = 0.40, n.s.). When all amateurs and professionals were comactivity to amHG, our findings provide evidence for the augbined, however, the correlation was highly significant (r = 0.70,
mentation of PAC gray matter in musicians.
(2,500 Hz, nonsignificant (n.s.)).
P < 0.0001). This correlation was smaller when considering the
This functional–anatomical interpretation is consistent with
In professional musicians, dipole amplitudes
gray matter volume of aHG in its full lateral extent (r = 0.44, P
the microanatomical24–29 finding that amHG comprises most
were significantly larger in the right than in the left
< 0.01) and was nonsignificant when the whole gray matter
of the primary granular core field. However, the macroanatomhemisphere at all frequencies. On average, the
volume of HG was calculated (r = 0.26, n.s.). No correlation
ically defined amHG is only an approximate measure of the
N19m-P30m signal was 21 ± 9% larger in the right
was found between musical aptitude and white matter volumes
location and extent of PAC, because there is considerable indihemisphere (F1,11 = 47.3, P < 0.0001). Compared
of HG.
vidual variability27–31. Non-primary cortical fields are most
to non-musicians, professional musicians had an
Under the assumption that anatomical size determined the
likely to be found near the lateral and posterior edges of
signal strength, a partial correlation was calculated to eliminate
amHG2,27–29. Thus, the larger volume of gray matter in musithe influence of amHG gray matter volume of on the correlacians may comprise PAC as well as surrounding belt areas. The
tion between N19m-P30m amplitude and AMMA score. This
strong functional–anatomical correspondence at the level of
Fig. 2. Auditory evoked N19m-P30m signals and 3D
partial correlation was only r = –0.04 (n.s.), indicating that
amHG is probably related to the stimulation with sinusoidal
gray matter surface reconstructions of HG for all subanatomical size was the key parameter.
tones. Whereas functional MRI41,42 and PET43 studies have shown
jects aligned in the same order. Both the neurophysiological and the anatomical data show a large increase in
professional musicians and a smaller increase in amanature neuroscience • volume 5 no 7 • july 2002
691
teur musicians. Left, dipole strength of the primary
cortical response at 500 Hz. Source activities of the
right (thick lines) and left (thin lines) hemispheres are
superimposed. Right, highlighted areas show the
amHG for each subject, aligned in the same order as
the primary evoked responses.
nature neuroscience • volume 5 no 7 • july 2002
689
served
as subyears
(range,
7 to 17for
years)
of 11.7
their
instruments
a mean
period
for our
jectsyears
study.
served
to nonmusicians
as sub(range,
7Six
17 years)served
as controls
The
mean
for
(15).
age
both
jects for ourstudy.Six nonmusiciansserved
Evidence has accumulatedover the past deafferentationof an entireforelimbin ma- groups
24 ? (15).
3 years.
as was
TheBefore
meanour
for both
controls
ageinvestwo decades
that indicates
that alterations
caquedeafferentation
monkeys (8) of
and
upperforelimb
1
extremity
the
a diary
forinvesEvidence
musicians
has accumulated
kept Before
over the past
in ma-tigation,
an entire
was
groups
24 ? 3 years.
our
in afferent
canthat
induce
plastic
reorgaamputation
humans(8)
(9-11).
twoinput
decades
week,
recording
amount
of time
pracindicates
that
caque in
monkeys
and upper extremity
alterations
the the
a diary
for 1
musicians
tigation,
kept
? 8.4 of
in afferent
canthe
induce
plastic
reorga-In amputation
in humans
nizational
(9-11).
changesinput
within
in studies ticedweek,
recording
timeper
pracaddition,it has
been shown
adult
mam9.8amount
hours
per day
(meanthe
? amount
nizational
changes
within
in studies
addition,
it has
been shown
adult mamticed
maliancentral
perhad
dayestimated
(mean 9.8the
8.4 hours
with owlIn
monkeys
that
a prolonged
nervous
system
increase
(1).the
Changes
week),
and
ofper
maliancentral
withstimulation
owl monkeys
nervous
systemsensory
(1). Changes
had estimated
theprevious
amount of
in the relation
between
peripheral
of tactile
of
tothat
thea prolonged
distal padincrease
timeweek),
spent and
practicing
duringthe
in their
the relation
peripheral
oftwo
tactile
sensory
stimulation
to the
pad ofmonth
timeand
the previous
spent
practicing
fieldsand
centralbetween
representations
have
one or
in adistal
phalanges
results
greatly
8.8 hours
year
(10.8 ?during
per
fieldsand
their
representations
one cortical
in a to
or two representation
phalangesresults
greatly
month and year (10.8 ? 8.8 hours per
been observed
for
increased
thecentral
specific
somatosensory
(2), have
week).
been
for the somatosensory
increased
representation
week). the experimental session, sovisual (1,
3, observed
4), and auditory
systems(5), (2),
ofcortical
that portion
the fingers
(12, 13).specific
Evi- to During
visual
(1,
3,
4),
and
auditory
systems
of
(5),
that
the
portion
fingers
(12,
Evi13).
the experimental
During
session,
and comparablechanges also have been dence has also been reportedthat suggests matosensory
was delivered
stimulation
tosoandmotor
comparable
changes
have
dence has
also been
was
reportedthat
stimulation
delivered
suggests
matosensory
found for
systems
(6). Inalso
an increased
cortical
of the
the first
in separate
many
of been
representation
to the to
digit and,
runs,
found for motor
systemsof
(6).afferent
In many index
increased
of thefifththe
first
in separate
of an
representation
to the
and,
runs,
these experiments,
the removal
finger
usedincortical
reading
by blindBraille
of digit
either
hand.
condigit
Stimulation
thesea experiments,
theresulted
removal
afferent
index
fifth
of either hand.
condigitsuperficial
Stimulation
input from
corticalregion
inofan
readers
(14).fingerusedin readingby blindBraille
of light
sisted
pressure
appliedby
from
a corticalregion
inputby
readers(14).
sisted
light superficial
pressure
applied
"invasion"
a neighboring
arearesulted
whose in an Violinists
and other string playerspro- means
of aofpneumatic
with
stimulator
the by
"invasion"
by
a
neighboring
area
whose
Violinists
and
other
string
means
of
a
with
players
prostimulator
pneumatic
innervationremainedintact. For example, vide a good model for the study of the
use of standard,nonpainfulstimulationin-the
innervation
remainedintact.
Forbeexample,
a good model
for input
the study
of thetensity
use(9,
of standard,
stimulation
nonpainful
the cortical
a digit
region representing
effectsvide
of differential
afferent
to the
data (Fig.
16, 17). The
1) indi-inthe
cortical
a
region
representing
beeffects
of
differential
afferent
to
the
The data
digit
input
(9,center
16, 17).
(Fig. 1) indifore amputationin owl monkeyscould be tw,osides of the brain in humans.During catetensity
that the
of cortical
responsivity
fore
in
amputation
owl
in
could
be
tw,o
sides
of
the
brain
cate
that
the
center
of
cortical
monkeys
humans.
During
responsivity
activatedafter amputationby tactile stim- theirpracticeor performance,the secondto
for tactile stimulationof the digits of the
after
amputation
their
of the digits
practice
thehand
secondtoleft hand
for tactile
stimulation
of the
of an intact
ulationactivated
the fifth
in musicians
adjacent
The stimtoperformance,
was shifted
as comfingerby
(7).tactile
digits
(D2or
D5) of the left
ulationof an
the fifth digits (D2 to D5) of the left hand left hand was shifted in musiciansas comadjacent
finger
(7). The
of the
orderof
changes noted wereintact
a few
are continuously
engagedin fingeringthe paredto that in controls,while at the same
changes noted were of the orderof a few are continuouslyengagedin fingeringthe paredto that in controls,while at the same
millimeters.Moreextensiveplasticchanges strings, a task that involves considerable time the strength of response increased.
millimeters.Moreextensiveplasticchanges strings, a task that involves considerable time the strength of response increased.
have recently
been observed
afterthe
abomanual
dexterity
and and
enhanced
TheThe
shift was towardthe midsensory
topographic
have recently
been observed
after
the abomanual
dexterity
enhanced
sensory
topographicshift was towardthe midlition oflition
input
of theof the
At the
stimulation.
the thumb
thethe
of of
time,time,
surface
plane,
which,
along
offrom
fromportions
inputlarger
Atsame
the same
largerportions
stimulation.
the thumbsagittal
surface
sagittal
plane,
which,
along
with
of
body-for
example,
the
neck
the
althe
is toward
thethe
grasps
instrument
and,
somatosensory
postcentral
gyrus,
region
body-for example, with somatosensory graspsthe neck of the instrumentand, al- the postcentralgyrus,
is toward
region
of the individual.
Tekst
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Distance,
to left
D5,hand
Distance,
left hand
Dl toDlD5,
(cm)(cm)
1. (A) Equivalent
Fig.
current dipoles
by stimulation
of the thumb
Dl. dipole
controls;
theisshift
is larger
D5 than
forThe
The dipole
moment
is also
larger
Fig. 1. (A)
Equivalent
current dipoles
elicited elicited
by stimulation
of the thumb
(D1) (D1)
controls;
the shift
larger
for D5for
than
for Dl.
moment
is also
larger
and
fifth
finger
(D5)
of hand
MRI
the left
hand
are superimposed
onto
an
of hand
black
(magnetic
formusicians'
the musicians'
D5,indicated
as indicated
by greater
the
greater
magnitude
the
and
finger
(D5)
ofWienbruch
MRI
the
left
are
superimposed
onto
black
(magnetic
for the
D5, as
by
magnitude
the
Elbert
T,fifth
Pantev
C,
C,
Rockstroh
B, an
Taub
E.
Increased
cortical
representation
of the
the
fingers
of
theofleft
in
resonance
reconstruction
of the cerebral
of a control,
(B)magnitude
The magnitude
the dipole
moment
a function
of the
resonance
imaging)imaging)
reconstruction
of the cerebral
cortex cortex
of a control,
who who
arrow.arrow.
(B) The
of theofdipole
moment
as aasfunction
of the
age age
of of
was Science,
selected
to provide
inception
of musical
practice;
players
are indicated
by filled
circles,
the305-7.
interpretation
selected
to provide
anatomical
for the for
inception
of musical
practice;
stringstring
players
are indicated
by filled
circles,
interpretation
of the of the
stringwas
players
1995anatomical
Octlandmarks
13; landmarks
270(5234):
MEG-based
localization.
The arrows
represent
the location
and orientation
of
moment
for indicontrol
subjects
by hatched
circles.
the larger
dipole
MEG-based
localization.
The arrows
represent
the location
and orientation
of
moment
for indicontrol
subjects
by hatched
circles.
NoteNote
the larger
dipole
ECDfor
vector
of the
twoaveraged
digits'averaged
viduals
beginning
musical
practice
before
the of
age12.
of (C)
12.Scatterplot
(C) Scatterplot
of the
musicians
the ECDthe
vector
eachfor
of each
the two
digits'
across across
viduals
beginning
musical
practice
before
the age
of the
musicians
(black)(black)
and controls
Theof
length
of the arrows
Euclidean
distances
(in centimeters)
between
the cortical
representations
represents
the magnimean magniand controls
(yellow).(yellow).
The length
the arrows
Euclidean
distances
(in centimeters)
between
the cortical
representations
of of
represents
the mean
tudedipole
of themoment
DlD5.
andThis
D5.distance
This distance
formusicians'
the musicians'
left hands
greater
dipole moment
two in
each group.
digits
The average
tude of the
Dl and
for the
left hands
was was
greater
thanthan
thatthat
for the for
twothe
eachingroup.
digits
The average
of Dl
D5 are
andshifted
Dl are medially
shifted medially
for theplayers
string players
compared
to
in controls,
butdifference
this difference
not statistically
significant.
locationslocations
of D5 and
for the string
compared
to
in controls,
but this
is notisstatistically
significant.
* VOL.
SCIENCE
13 OCTOBER
* VOL.
SCIENCE
270 *27013*OCTOBER
1995 1995
305305
Tekst
Schlaug G, Jäncke L, Huang Y, Staiger JF, Steinmetz H. Increased corpus callosum size in musicians.
Neuropsychologia. 1995 Aug; 33(8):1047-55.