Neurophysiological origin of human brain asymmetry for speech and language # Proceedings of the National Academy of Sciences of the United States of America, Vol. 107, No. 43. (26 October 2010), pp. 1.pdf

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Neurophysiological origin of human brain asymmetry
for speech and language
Benjamin Morillon
a
, Katia Lehongre
a
, Richard S. J. Frackowiak
b,c
, Antoine Ducorps
d
, Andreas Kleinschmidt
e
,
David Poeppel
f
, and Anne-Lise Giraud
a,1
Institut National de la Santé et de la Recherche Médicale U960-Ecole Normale Supérieure, 75005 Paris, France;
b
Service de Neurologie, Centre Hospitalier
Universitaire Vaudois, 1011 Lausanne, Switzerland;
c
Neuroimaging Laboratory, Instituto di Ricovero e Cura a Carattere Scientifico Santa Lucia, 00179 Rome,
Italy;
d
Centre de Neuroimagerie de Recherche, Hôpital de la Pitié-Salpêtrière, 75013 Paris, France;
e
Institut National de la Santé et de la Recherche Médicale
U992 Cognitive Neuroimaging Unit, Commissariat á l’Energie Atomique, NeuroSpin, 91191 Gif-sur-Yvette Cedex, France; and
f
Department of Psychology, New
York University, New York, NY 10003
Edited by Mortimer Mishkin, National Institute for Mental Health, Bethesda, MD, and approved September 13, 2010 (received for review June 6, 2010)
a
The physiological basis of human cerebral asymmetry for language
remains mysterious. We have used simultaneous physiological and
anatomical measurements to investigate the issue. Concentrating
on neural oscillatory activity in speech-specific frequency bands
and exploring interactions between gestural (motor) and auditory-
evoked activity, we
find,
in the absence of language-related pro-
cessing, that left auditory, somatosensory, articulatory motor, and
inferior parietal cortices show specific, lateralized, speech-related
physiological properties. With the addition of ecologically valid
audiovisual stimulation, activity in auditory cortex synchronizes
with left-dominant input from the motor cortex at frequencies
corresponding to syllabic, but not phonemic, speech rhythms. Our
results support theories of language lateralization that posit a
major role for intrinsic, hardwired perceptuomotor processing in
syllabic parsing and are compatible both with the evolutionary
view that speech arose from a combination of syllable-sized vocal-
izations and meaningful hand gestures and with developmental
observations suggesting phonemic analysis is a developmentally
acquired process.
EEG/functional MRI
assumption is that motor areas express natural oscillatory activity
that characterizes intrinsic jaw (4 Hz) movements and those of
the tongue (e.g., trill at 35–40 Hz). These frequencies correspond
to the two rhythms required to produce syllables and phonemes
(see above) (12, 20). Activity in brain systems associated with both
speech perception and production should therefore be correlated
in a lateralized manner with neuronal oscillations in speech-
related frequency bands. Our data probed the
intrinsic
tuning no-
tion and then tested, with a naturalistic speech stimulus, a spoken
movie, whether it predicts lateralized language network activity.
Results
fluctuation
by change in the blood oxygen level-dependent (BOLD)
signal and (ii) power
fluctuations
in cortical rhythms by concurrent
EEG, in 16 subjects who alternately
“rested”
for 10 min (intrinsic
correlations) and watched a 10-min movie clip (speech-evoked
correlations, refs. 21, 22). The movie, a documentary on an eco-
logical topic, featured two main characters lecturing, interleaved
with brief illustrative sequences without speech (Movie
S1).
We
extracted fMRI signals bilaterally from cytoarchitectonically de-
fined
regions and correlated their time courses with EEG oscil-
lations determined in 1-Hz steps between 1 and 72 Hz. We then
quantified the degree of hemispheric asymmetry in EEG/fMRI
coupling for 18 pairs of homotopic territories covering the whole
language network and the articulatory motor cortex (Materials
and Methods).
We also included two nonspeech-related control
regions, one in the motor (the foot area) and another in the visual
cortex (BA18).
All sampled territories shared some
intrinsic
correlations (i.e.,
at rest) between EEG power and BOLD signal
fluctuations
(SI
Discussion 1);
these were characterized by positive correlations
in the delta–theta (2–6 Hz;
SI Discussion 2)
and negative in alpha
and beta bands. Positive correlations indicate that regional syn-
aptic activity increased whenever the power in the delta–theta
range increased. Conversely negative correlations indicate re-
gional drops in synaptic activity when alpha and beta power in-
creased. In the gamma band, intrinsic correlation depended on
territory, with positive correlations found in auditory and motor
cortices (Fig. 1
B
and
C).
Asymmetrical EEG/fMRI correlations
were present in the medial part of the
primary auditory cortex A1
(Te1.1; Fig. 1
A
and
D),
and the tongue and hand
motor cortices
Intrinsic Hemispheric Asymmetries in Speech-Related Frequency Com-
ponents.
Across the entire brain we measured (i) local brain activity
|
natural stimulation
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resting state
|
oscillation
uditory asymmetry (1) and hand preference are traits
humans share with other primate and nonprimate species
(2–5). Both have been proposed as the functional origin of human
cerebral dominance in speech and language (6, 7). The motor
theory of language evolution argues that speech evolved from
a preexisting manual language (8) involving lateralized hand/
mouth gestures. Such asymmetric control of gesture or pharyn-
geal musculature could have led to left lateralization of speech
and language (9). Conversely, if auditory preceded motor asym-
metry in evolution, the alignment of vocalization to gestures (10)
might have gradually led to left-lateralized motor and executive
language functions (11). It remains unknown and controversial
which of these scenarios accounts for asymmetry in speech and
language processing, so we set out to
find
empirical evidence in
favor of one or the other.
We obtained simultaneous functional magnetic resonance im-
aging (fMRI) and electroencephalography (EEG) recordings at
rest and while watching an ecologically valid stimulus (movie) to
identify where brain activity correlates with electrophysiological
oscillations in frequency bands related to syllabic and phonemic
components of speech. We tested for evidence of lateralization of
component-associated frequencies. Our experimental approach
was based on two assumptions that have received recent experi-
mental support (12–15): The
first
is that there are two intrinsic
hardwired auditory speech sampling mechanisms, working in par-
allel, at rates that are optimal for syllabic and phonemic parsing of
the input (delta–theta (∼4 Hz) and gamma (∼40 Hz) oscillations,
respectively) (6, 16). They shape neuronal
firing
elicited by audi-
tory stimulation (17) with fast phonemic gamma modulated by
slower syllabic theta oscillations (18, 19), thus aligning neuronal
excitability to the most informative parts of speech. The second
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A
Author contributions: A.-L.G. designed research; B.M., K.L., and A.D. performed research;
B.M., A.K., and A.-L.G. analyzed data; and B.M., R.S.J.F., A.K., D.P., and A.-L.G. wrote the
paper.
The authors declare no conflict of interest.
This article is a PNAS Direct Submission.
1
To whom correspondence should be addressed. E-mail: anne-lise.giraud@ens.fr.
This article contains supporting information online at
www.pnas.org/lookup/suppl/doi:10.
1073/pnas.1007189107/-/DCSupplemental.
www.pnas.org/cgi/doi/10.1073/pnas.1007189107
Fig. 1.
Auditory and motor oscillatory profiles at rest. (A)
Cytoarchitectonic and functional parcellation of (Left) au-
ditory (axial plane) and motor cortices (sagittal plane), re-
spectively. (B and
C)
Correlation coefficients between each
EEG frequency band (1–72 Hz; mean
±
SEM) and left (black)
or right (gray) (A) auditory Te1.1 and (B) motor lip BOLD
time courses. (D and
E)
Asymmetry indexes (mean
±
SEM)
for four (D) auditory and (E) motor regions. The index cor-
responds to left minus right difference in the correlation
between BOLD and EEG
fluctuations
over 1–72 Hz during
rest. Three frequency bands of interest are highlighted in
gray: delta–theta 2–6 Hz, gamma 38–47 Hz, and gamma
56–72 Hz (*P
<
0.05, **P
≤
0.01, uncorrected).
in the gamma band, and in the motor lip area in the gamma and
delta–theta bands (Fig. 1E). Asymmetry was also detected in the
ventral part of the parietal operculum/secondary
somatosensory
cortex S2,
which contained somatosensory/proprioceptive repre-
sentations of speech sounds (23) important for feedback control
of speech production and in
BA40
in the vicinity of the Sylvian
parietal temporal (SPT) area implicated in sensorimotor trans-
formations of speech (24) (Fig. 2, colored bars). Motor cortical
asymmetry was also found in the beta domain around 20 Hz (Fig.
1E). Asymmetry was greatest in the articulatory motor cortex and
in BA40 (Fig. 2), but in relation to speech-associated frequencies
(delta–theta and gamma bands) asymmetry was most pronounced
in the auditory cortex. There was no significant intrinsic left
dominance in control regions. Likewise, we found no significant
left lateralization in the
planum temporale
or the ventral pre-
frontal cortex. This is a critical
finding
because they are recog-
nized as archetypal left lateralized, language-specific regions, since
Wernicke
and
Broca
showed that lesions in them caused ma-
jor perception and production impairments (25). The
findings
in-
dicate that left auditory, somatosensory, inferior parietal, and
articulatory-motor cortices show better inherent tuning to speech-
related frequencies than right homotopic regions. Frequency-
specific asymmetries in auditory cortices were replicated using
magnetoencephalography (MEG) at rest where we computed the
frequency power over auditory left and right hemispheric sensors
(Fig.
S1
and
SI Results).
We evaluated whether regions exhibiting asymmetries of os-
cillatory activity at rest constitute a functional network (26). We
used a cross-correlogram approach to assess similarity of asym-
metry in the sampled frequency spectrum across all sampled
territories (Fig. 3
A
and
B; Materials and Methods).
Asymmetry
profiles were shared as a function of anatomical proximity,
resulting in correlated patterns across A1, S2, and BA40, be-
tween BA40 and the motor cortex, and across the tongue, lip,
and hand motor regions (SI
Discussion 3).
These data suggest
that left auditory, somatosensory, and motor cortices constitute
with SPT a core lateralized network at rest, which does not in-
clude Wernicke’s and Broca’s areas. Overall we found no evi-
dence for any computational advantage in these regions result-
ing from the intrinsic presence of speech-matching oscillations,
Fig. 2.
Asymmetry indexes (mean
±
SEM)
during rest (colored bars) and movie
(white bars) averaged over the whole
spectrum (1–72 Hz) for each region of in-
terest. Positive values correspond to left
dominance and significant interactions
are highlighted with brackets [*P
<
0.05,
**P
≤
0.01, ***P
≤
0.001 at the post hoc
(Fisher’s LSD) comparison].
Morillon et al.
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Fig. 3.
Shared asymmetry profiles (A and
B)
at rest and
(C and
D)
between rest and movie. (A and
C)
Pearson’s
cross-correlation (r) matrices of the normalized asym-
metry indexes of 18 regions of interest computed over
the whole spectrum (1–72 Hz) data points (A) during
rest condition and (C) between rest (horizontal axis)
and movie (vertical axis) conditions (see the schematic
in the
Lower Right
part of
D).
(B and
D)
Representation
of the significant correlations (B) during rest condition
over the whole spectrum (P values corrected for multi-
ple comparisons) and (D) driven by rest over movie
conditions (uncorrected
P
values). Note some bidi-
rectional influences (simple traits).
i.e., no greater ability to phase lock with speech than their right
homolog. This result suggests that this property is either irrele-
vant for such neural computations in these regions, e.g., strictly
time-independent computations, or more likely, that speech-
matching oscillations are asymmetrically elaborated during
language-associated stimulation.
Language-Network Lateralization During Audiovisual Linguistic Stimu-
lation.
We therefore addressed the hypothesis that the left-domi-
nant activity in Wernicke’s and Broca’s areas seen during language
processing results from a propagation of lateralized output from
the core network. To test this hypothesis, we carried out the same
analyses as above on data acquired watching the spoken movie. We
assumed that watching a movie would activate the cortical lan-
guage network ecologically, so we were unsurprised to
find
an in-
crease of BOLD signal in a set of regions including bilateral
auditory and visual areas, bilateral precentral sulci, and the left
inferior frontal gyrus between
“movie”
and
“rest”
conditions (Fig.
S2
and
SI Materials and Methods;
ref. 27); equally, we noted in-
creased strength of EEG/fMRI coupling over the whole spectrum
of frequencies in most sampled territories (Fig.
S3).
Augmented
coupling was often, but not always, accompanied by an increase
in asymmetry (Fig.
S4).
All core auditory territories were left
dominant and tuned to the gamma frequency band (Fig. 4A). In
Wernicke’s area, left dominance became significant in the two,
rest-associated, gamma bands asymmetrically tuned in the auditory
region Te1.1 (Fig. 4A, shaded columns;
SI Discussion 4).
Asym-
metry also increased in Broca’s region and BA40, but over
a broader frequency range that included beta frequencies (Fig. 2,
white bars;
Fig. S4).
No increase of asymmetry was found in the
motor cortex (Figs. 2 and 4B). We conclude that asymmetry in
articulatory and hand motor cortex is
intrinsically
strong and not
prone to modulation by audiovisual language processing. This
asymmetry may be due to left-dominant pharyngeal muscle control
(9). EEG/fMRI coupling remained symmetric in the visual cortex
(Fig. 2 and
Fig. S4D),
indicating that the induction of asymmetry in
classical language areas is not due to stimulus-driven cortical en-
trainment but to specific augmentation of a constitutive asymmetry
that in other regions is already manifest at rest.
Impact of Intrinsic on Stimulus-Driven Asymmetry.
To test the hy-
pothesis that
intrinsic
lateralization of the core system determines
lateralization of the language network during language stimula-
tion we computed cross-correlograms between spectral asymme-
try profiles in all territories at rest and when watching a movie,
thus probing which intrinsically lateralized, frequency-coupled
regions predict the asymmetry profile of the language network
during processing of audiovisual speech. We found four regions
where resting asymmetry predicts language-driven asymmetry
(Fig. 3C, vertical red stripes): A1, S2, BA40, and Wernicke’s area.
Fig. 4.
Asymmetry indexes (1–72 Hz; mean
±
SEM) during movie in (A) auditory and (B) motor regions. Positive values correspond to left dominance
(*P
<
0.05, **P
≤
0.01, uncorrected). Frequency bands of interest are highlighted in gray (Fig. 1).
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Morillon et al.
Whereas the
first
three of these were asymmetric at rest, Wer-
nicke’s area was not (Fig. 1D). This acquired asymmetry pattern
reflects both the integration from auditory and somatosensory
cortices (horizontal red stripe in Fig. 3C) during movie watching,
and the induction of Wernicke’s profile (vertical red stripe; non-
significant trends over A1 and BA40, both
P
values
<0.1)
on other
regions. These data are in line with the notion that the
planum
temporale
is an important hub (28) for relaying speech-induced
neural activity to language areas.
Leftward dominance in the language network appears to be
rooted in left-hemisphere regions tuned to speech rhythms.
However, motor cortex, although showing strong asymmetry at
rest, failed to influence other regions. In addition, the asymmetry
in Broca’s area induced by watching a movie was not determined
by activity in any other region at rest. These results were obtained
from analyses over the complete frequency range, so we then
asked whether the regions interacted with other components of
the language system in speech-specific frequency bands, e.g.,
delta–theta (2–6 Hz) and gamma (Fig. 3D and
Fig. S5;
Materials
and Methods).
We found that asymmetry in the profile of activity
in Broca’s area was driven specifically by several lower gamma
band (38–47 Hz) inputs from the auditory and somatosensory
cortices, Wernicke’s region, and left BA40 (Fig. 3D, blue arrows).
This pattern emphasizes the integrative function of Broca’s area
(29) (see also the complex asymmetry profile in Broca’s region in
Fig. S4)
and implies that its neural computations occur at specific
timescales that include at least low gamma frequencies. It is not
yet clear how to relate this timescale to the function of Broca’s
region in speech and language subroutines, but if Broca’s region is
involved in a number of them, as has been suggested empirically
(30), local processing, reflected in gamma band activity is neu-
rophysiologically plausible and unsurprising.
These additional analyses also showed that the
intrinsic
asym-
metry (i.e., at rest) in the delta–theta frequency bands found in
hand motor cortex predicted that found in auditory and somato-
sensory cortices during movie viewing (Fig. 3D, green arrows). This
frequency band characterizes dominant hand movements that ac-
company periodic jaw and lip movements when articulating sylla-
bles. They can be meaningful in their own right and are functionally
linked to oral communication (31). Our data suggest that input
from motor hand and lip areas, directly or via the somatosensory
cortex, may contribute to speech parsing at syllabic rates by auditory
cortex. This interpretation is supported by recent
findings
showing
a facilitation of speech perception when the motor lip area is
stimulated by transcranial magnetic stimulation (TMS) (32), and
also by electrophysiological data in monkeys showing that an input
from the somatosensory cortex shapes the response of the auditory
cortex to sounds by phase-resetting ongoing oscillations (33). That
intrinsic left dominance in motor areas at syllabic rates predicts
auditory and somatosensory left dominance during a movie illus-
trates the idea that sensing is an active process that is constrained by
motor routines (34). This does not imply that the motor cortex is
causally indispensable to speech perception, but that it may, much
like the visual system in perception, provide cross-modal synchro-
nization cues subtended by delta–theta phase modulation that are
useful to speech processing (35, 36). Understanding the computa-
tional steps that involve delta (∼1–3 Hz) and theta (∼5–7 Hz) as
a separate (19) or common (36) machinery is an important and
open issue. We did not detect propagation of asymmetry from the
motor tongue area to auditory cortex in the range of frequencies
corresponding to tongue movements and phonemic timescales (low
gamma frequencies). This negative
finding
is consistent with the
view that the motor cortex does not account for left auditory cortex
tuning to phoneme-associated frequencies, but suggests mutual
tuning of auditory and motor cortices, perhaps throughout adaptive
motor and language development.
Morillon et al.
Discussion
Our online concurrent EEG and BOLD fMRI data suggest that
leftward asymmetry in language processing originates in auditory,
somatosensory (37), articulatory motor, and inferior parietal cor-
tices. All four regions show a stronger intrinsic expression of spe-
cific oscillations that can serve speech parsing (38) in the left than
in the right hemisphere. Delta–theta and gamma cortical rhythms
can be found in many brain regions and are involved in a broad
range of cognitive operations (39, 40). However, our data show
that within the studied regions, delta–theta and gamma asym-
metric expression is confined to the language system, i.e., is
absent in (motor and visual) control regions, suggesting that these
rhythms play a specific role in speech processing. It is possible that
throughout evolution, the human brain has developed a commu-
nication signal adapted to the cortical oscillatory machinery pres-
ent in sensory and motor cortices, and has exploited incidental
cortical asymmetry (4) to implement parallel handling of linguistic
and nonlinguistic material (1). That the oscillatory machinery has
been locally reinforced by speech processing is also supported by
recent data showing that the topography of gamma and delta–theta
rhythms overlaps more with neural speech perception and pro-
duction than with other cognitive systems (12).
Our data show that asymmetric expression of speech-related
rhythms found in the articulatory motor areas extends to the
motor hand area and interacts with auditory left dominance at
the syllabic, but not the phonemic timescale.
Inherent
auditory–
motor tuning at the syllabic rate and
acquired
tuning at the
phonemic rate are also compatible with two recognized stages of
language development in infants; an early stage with production
of syllables that does not depend on hearing (also observed in
deaf babies) (41), followed by a later stage in which infants match
their phonemic production to what they hear in caregiver speech
(42). This
finding
is hence compatible with the observation that
syllabic
“packaging”
is universal and perhaps innately specified,
while a phonemic repertoire is acquired over the course of de-
velopment in specific linguistic contexts (43). From phylo- and
ontogenetic perspectives, our
findings
support an evolutionary
scheme in which spoken language arose from the combination of
syllable-like vocalizations with hand gestures (10). Whereas this
scenario appears hardwired in the human brain, auditory–motor
interactions underlying the evolution of phonemic complexity in
speech are not. Phonemic complexity probably results from ac-
quired tuning of articulatory performance to fast integration
properties of left auditory cortex during maturation. An impor-
tant further step will be to assess how this later stage relates to
the recent evolution of FOXP2 (44), which influences
fine
ar-
ticulatory processes and thus may have orchestrated the capacity
to
fine-tune
for motor–auditory integration.
Finally, we show that speech parsing oscillatory machinery is not
intrinsically asymmetric in the posterior superior temporal cortex,
although Wernicke’s area typically responds more specifically to
speech than its right homolog (28). Our data demonstrate that
Wernicke’s area inherits speech-specific integration properties
from nearby left auditory and orofacial somatosensory cortices
when speech is heard, which is a key argument in a scenario where
asymmetry originates in mutual tuning across primary cortices.
Likewise, Broca’s area, which is critical for speech production,
expresses stronger gamma oscillations than its right homolog dur-
ing automatic speech processing, under the influence of
“posterior”
regions, i.e., Wernicke’s area, A1, S2, and BA40. These data sup-
port previous studies showing that Broca’s area is not asymmet-
rically involved in nonlinguistic tasks and hence not specific to
language (45), even though recent empirical work suggest that it
carries out essential computations in hierarchical language pro-
cessing (30). As functional selection of different subroutines
(within one structurally connected system) is one of the possible
functions of neuronal gamma-band synchronization (39), our
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study could reflect that the hierarchical selection of language-
specific subroutines in Broca’s area is in part controlled by pos-
terior language regions.
Materials and Methods
Subjects, Methods, and Data Acquisition.
Sixteen right-handed, healthy male
volunteers (age range, 19–29; written informed consent) with (corrected to)
normal vision and audition, and no history of neurological or psychiatric ill-
ness, underwent simultaneous EEG and BOLD fMRI to explore temporal cor-
relations in specific regions between the amount of synaptic activity driving
the hemodynamic BOLD signal and power at different EEG frequency bands
(46, 47) (see also
SI Discussion 1).
Only male subjects were used to minimize
subject-based variance of no interest (48) as possible sex differences were not
a subject of this study. They wore ear defenders and earplugs to attenuate
scanner noise and were requested to stay awake and to avoid moving.
Subjects were either asked to rest with eyes closed or to watch a movie
(Movie
S1)
for 10 min each. Data were acquired in three sessions, as follows:
session 1, rest; sessions 2 and 3, movie followed by rest.
The three sessions yielded 1,560 echoplanar fMRI image volumes (Tim-Trio;
Siemens, 40 transverse slices, voxel size = 3
×
3
×
3 mm
3
; repetition time =
2,000 ms; echo time = 50 ms;
field
of view = 192) and continuous EEG data
recorded at 5 kHz from 62 scalp sites (Easycap electrode cap) using MR-
compatible amplifiers (BrainAmp MR and Brain Vision Recorder software;
Brainproducts). Two additional electrodes (electrooculograph, EOG and
electrocardiograph, ECG) were placed under the right eye and on the col-
larbone. Impedances were kept under 10 kΩ and EEG was time-locked with
the scanner clock, which further reduced artifacts and resulted in higher EEG
quality in the gamma band (49). Additionally, an eye-tracking system
allowed for online monitoring of pupil movements during the movie, ensur-
ing an attentive watching in all subjects. A 7-min anatomical T1-weighted
magnetization-prepared rapid acquisition gradient echo sequence (176 sli-
ces,
field
of view = 256, voxel size = 1
×
1
×
1 mm) was acquired at the end
of scanning.
fMRI and EEG Preprocessing.
We used statistical parametric mapping (SPM5;
Wellcome Department of Imaging Neuroscience, UK;
www.fil.ion.ucl.ac.uk)
for fMRI standard preprocessing, which
first
involved realignment of each
subject’s functional images and coregistration with structural images.
Structural images were segmented and spatially normalized using the uni-
fied
segmentation/normalization approach implemented in SPM5. Seg-
mentation made territory delineation easier. Scans from different subjects
were spatially normalized on the basis of their corresponding normalized
structural image and
finally
spatially smoothed with a 10-mm full-width
half-maximum isotropic Gaussian kernel to compensate for residual vari-
ability after spatial normalization.
EEGlab v.7 (sccn.ucsd.edu/eeglab) and the FMRIB plug-in (users.fmrib.ox.
ac.uk/∼rami/fmribplugin) were used on EEG data for gradient and pulse
artifact subtraction. In two subjects, one of three rest sessions was excluded
due to poor EEG quality, and another subject was completely excluded. The
EEG data were downsampled to 250 Hz, and low-passed
filtered
at 75 Hz.
Cortical Territory Delineation.
We used the SPM Anatomy Toolbox v.1.5 to
delineate 16 different cortical territories on the basis of probabilistic
cytoarchitectonic maps, for each hemisphere. We sampled them within the
language network including the
primary auditory cortex A1
(BA41: territo-
ries Te1.0, Te1.1, and Te1.2, Fig. 1A), the
planum temporale
(Wernicke’s
region: Te3), the ventral prefrontal cortex (Broca’s region: BA44 and BA45),
the parietal operculum/secondary
somatosensory cortex S2
(OP1 to OP4),
and the rostral inferior parietal cortex
BA40
(PFop, PFt, PF, PFm, and PFcm).
We included the secondary visual cortex (BA18) as a control region.
As functional areas corresponding to articulatory and nonarticulatory
primary
motor
regions are all located within a single cytoarchitectonic ter-
ritory (BA4p), we used spatial coordinates resulting from functional MRI
studies of tongue, hand, foot (50), and lip (51) movements. Using MarsBaR
v.0.41 toolbox, we created, for each left and right area, a sphere with a 5-
mm radius centered on the literature-defined coordinates.
These territories and spheres were used as masks to extract, for each
subject, their associated BOLD time courses (averaged across all respective
voxels) over the entire scanning period, using MarsBaR.
Time–Frequency Analysis.
A time–frequency wavelet transform using in-house
Fast_tf v.4.5 software was applied at the frontocentral electrode (equidistant
to both hemispheres) referenced to the mean of the two occipital electrodes
(i.e., most distant position), using a family of complex Morlet wavelets, re-
sulting in an estimate of oscillatory power at each time sample, from 1 to 72 Hz
in steps of 1 Hz. Importantly, the time–frequency resolution of the wavelets
was frequency dependent, so we applied a different wavelet factor for low
and high frequencies: 1–20 Hz,
m
= 10; 21–72 Hz,
m
= 30. Data were further
downsampled at 8 Hz (sliding average of 33%), centered to the mean for
each frequency band, convolved with the hemodynamic response function,
and further downsampled to match the fMRI repetition time.
Territory-Based Correlation Analysis with the EEG Power Spectrum.
For each
sampled area (20 territories
×
2 hemispheres) the BOLD time course was
correlated with each EEG power
fluctuation
across the spectrum of 1–72 Hz,
after concatenation of the 3-rest or 2-movie sessions. Covariates of no in-
terest corresponding to head-motion parameters were included in each
model (using partial correlations). Resulting correlation values were Fisher
Z-transformed,
allowing standard statistics on a near Gaussian population
to be performed. Of note, correlation values were obtained between the
global EEG time course and the BOLD time course of small anatomofunc-
tional areas, resulting in rather small but reproducible values. We interpret
a stronger correlation as a stronger coupling between oscillatory activity and
BOLD response, i.e., a stronger contribution of the oscillatory activity to
regional synaptic activity.
Statistical Analyses.
We assessed hemispheric differences by computing the
difference between the correlations coefficients of left and right homotopic
areas, for each 72-frequency band, each 20-territory, each 2-condition (rest or
movie), and each 15-subject. This difference is referred to as
“asymmetry
index.” Preliminary observations showed that the different territories of S2
(4) and BA40 (5) had similar profiles of asymmetry. We subsequently only
studied in detail one territory for each of these two regions, with the criteria
that it should express the most representative asymmetry profile of its own
group and be part of the functionally relevant language network. Accord-
ingly, we selected OP4, which contained somatosensory/proprioceptive
representations of speech sounds (23), and PFt involved in linguistic senso-
rimotor transformation (24).
One-sample
t
tests were performed for each remaining 13-territory,
within the delta–theta 2- to 6-Hz, low gamma 38- to 47-Hz, and high gamma
56- to 72-Hz bands. These bands were chosen because they correspond to
the typical pattern of asymmetry (with left hemispheric positive correlation
coefficients) as observed in Te1.1 (Fig. 1B). Our statistical approach was
therefore a mass univariate one, as the different frequency bands of interest
corresponded to different Gaussian
filters,
and the 13 territories corre-
sponded to nonoverlapping voxels.
P
values
<0.05
uncorrected were then
considered significant and are reported in Figs. 1 and 4 and
Fig. S4.
To obtain a single signature of the asymmetry profile in each 13-territories
within each double condition, we computed the mean asymmetry index over
the whole spectrum (1–72 Hz). Significant hemispheric asymmetries were
tested on the mean correlation coefficients by repeated-measures ANOVA
(factors: territory, 13 levels; condition, 2 levels; and hemisphere, 2 levels),
which showed significant main effects of interest [hemisphere:
F(1,15)
= 6.41,
P
= 0.02; territory
×
condition
×
hemisphere:
F(12,180)
= 2.22,
P
= 0.01],
allowing post hoc
t
tests to be performed. Significant differences between
conditions were tested on the mean asymmetry indexes by repeated-measures
ANOVA (factors: territory, 13 levels; condition, 2 levels), which showed sig-
nificant main effects of interest [condition:
F(1,15)
= 5.46,
P
= 0.03; territory
×
condition:
F(12,180)
= 2.22,
P
= 0.01], allowing for computation of post hoc
t
tests.
P
<
0.05 at the post hoc (Fisher’s least significant difference, LSD) com-
parison were considered significant. These values are reported in Figs. 2 and 3
B
and
D.
In Fig. 3 we pooled together the territories according to their
functional relevance (ex: A1, S2, Broca) and reported the value of the strongest
asymmetric territory.
Finally, to confirm that the different territories of S2 or BA40 had similar
asymmetry profiles, we performed two (region dependent) repeated-meas-
ures ANOVAs on the global asymmetry indexes (factors: territory, 4 or 5 levels;
condition, 2 levels) and found no significant main effects in either case (all
F
values
<2.31;
all
P
values
>0.15).
Correlation Analysis Between the Asymmetry Indexes of Different Territories.
We examined the degree of similarity in the asymmetry profile across all
sampled territories (SI
Discussion 3).
As post hoc comparisons (Fig. 2) showed
no significant global asymmetry during rest or movie in the two control
territories (motor foot and visual BA18), we excluded them from subsequent
analyses. For each 15-subject, each 18-territory, and each 2-condition, we
normalized the asymmetry profile values. We used the asymmetry profile
values over either the whole spectrum or the 2- to 6-Hz, 38- to 47-Hz, or 56-
to 72-Hz bands. Pearson’s cross-correlations were computed for each
18692
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www.pnas.org/cgi/doi/10.1073/pnas.1007189107
Morillon et al.

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