A failure to grasp the affective meaning of actions in autism spectrum disorder subjects.

Abstract

The ability to grasp emotional messages in everyday gestures and respond to them is at the core of successful social communication. The hypothesis that abnormalities in socio-emotional behavior in people with autism are linked to a failure to grasp emotional significance conveyed by gestures was explored. We measured brain activity using fMRI during perception of fearful or neutral actions and showed that whereas similar activation of brain regions known to play a role in action perception was revealed in both autistics and controls, autistics failed to activate amygdala, inferior frontal gyrus and premotor cortex when viewing gestures expressing fear. Our results support the notion that dysfunctions in this network may contribute significantly to the characteristic communicative impairments documented in autism.

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Contents lists available at ScienceDirect
Neuropsychologia
journal homepage: www.elsevier.com/locate/neuropsychologia
A failure to grasp the affective meaning of actions in autism spectrum
disorder subjects
J. Grèzesa,∗, B. Wickerb, S. Berthozc, B. de Gelderd
aLaboratoire de Neurosciences Cognitives, INSERM U960 & DEC, Ecole Normale Supérieure, 29 Rue d’Ulm, 75005 Paris, France
bInstitut de Neurosciences Cognitives de la Méditerranée, CNRS, Université de Provence, Marseille, France
cINSERM U669 & Institut Mutualiste Montsouris, Universités Paris Sud & Paris René Descartes, Paris, France
dDonders Laboratory for Cognitive and Affective Neurosciences, Tilburg, The Netherlands
a r t i c l ei n f o
Article history:
Received 30 May 2008
Received in revised form 29 October 2008
Accepted 10 February 2009
Available online xxx
Keywords:
Autism
Action observation
Emotion
Bodily movements
fMRI
a b s t r a c t
The ability to grasp emotional messages in everyday gestures and respond to them is at the core of suc-
cessful social communication. The hypothesis that abnormalities in socio-emotional behavior in people
with autism are linked to a failure to grasp emotional significance conveyed by gestures was explored.
We measured brain activity using fMRI during perception of fearful or neutral actions and showed that
whereas similar activation of brain regions known to play a role in action perception was revealed in both
autistics and controls, autistics failed to activate amygdala, inferior frontal gyrus and premotor cortex
when viewing gestures expressing fear. Our results support the notion that dysfunctions in this network
may contribute significantly to the characteristic communicative impairments documented in autism.
© 2009 Elsevier Ltd. All rights reserved.
1. Introduction
Watching someone running with the hands protectively in
front of his/her face triggers in the observer a representation
of the action of running away, but also prompts the recogni-
tion of the emotional context: that the person runs for cover
because he/she is frightened. Grasping the emotional component
of the various actions we observe around us is a crucial prereq-
uisite for social communication. As the example shows, the skills
needed to decode the emotional components of actions reach
beyond the visuo-motor representation of the observed move-
ments. Additional perceptual and cognitive abilities are required
to represent the emotional significance of the observed move-
ments. The observer needs to appreciate that running and hiding
are significant components of a fear response. Grasping the fear
dimension in the actions we observe directs our attention to poten-
tialsocialorenvironmentalthreat,whichisimportantforpreparing
an appropriate adaptive reaction. While facial expressions provide
information about feelings and mental states, emotionally elicited
behavior is, as stressed by Darwin, at the core of the adaptative
Abbreviations: BOLD, blood oxygenation level-dependent; fMRI, functional MRI;
DCM, Dynamic Causal Modelling; AMG, amygdala; PM, premotor; IFG, inferior
frontal gyrus; STS, superior temporal sulcus.
∗Corresponding author. Tel.: +33 1 44 32 26 76; fax: +33 1 44 32 26 86.
E-mail address: julie.grezes@ens.fr (J. Grèzes).
significanceofexperiencingemotions.Therefore,afocusontheper-
ception of gestures and their emotional content provides a unique
opportunitytoinvestigatenonverbalaspectsofinter-personalcom-
munication (de Gelder, 2006). Because fear is phylogenetically
primitive and is processed relatively automatically and relatively
independently of higher cognitive processes we deemed it is
important to investigate how a population with social commu-
nicativedeficitsprocessesfearexpressionscommunicatedbysocial
gestures.
Autism is a neurodevelopmental disorder characterized by a
unique profile of impaired social communication and interaction
(e.g.Lordetal.,1989)withamajorimpactonadaptivesocialbehav-
ior (American Psychiatric Association, 1996). Subjects with autism
spectrum disorder (ASD) typically lack the ability to grasp the emo-
tional dimension of human actions. Several biological hypotheses
have been advanced to account for this problem including amyg-
dala, fusiform and superior temporal gyrus dysfunction (Ashwin,
Baron-Cohen, Wheelwright, O’Riordan, & Bullmore, 2007; Baron-
Cohen et al., 1999; Pierce, Haist, Sedaghat, & Courchesne, 2004;
Schultz, 2005; Zilbovicius et al., 2006), impaired functioning of
mirror neuron system (Dapretto et al., 2006; Hadjikhani, Joseph,
Snyder, & Tager-Flusberg, 2006; Theoret et al., 2005; Williams,
Whiten, Suddendorf, & Perrett, 2001) or abnormal cerebral con-
nectivity (Bachevalier & Loveland, 2006; Belmonte et al., 2004;
Geschwind & Levitt, 2007; Frith, 2004; Horwitz, Rumsey, Grady,
& Rapoport, 1988; Just, Cherkassky, Keller, & Minshew, 2004;
Wickelgren, 2005). So far, these hypotheses have been pursued by
0028-3932/$ – see front matter © 2009 Elsevier Ltd. All rights reserved.
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Fig.1. Designandexamplesofstimuli.(a)2×2factorialdesign.Imageswereeitherstaticordynamicandconsistedofwhole-bodyimagesofactorsopeningadoorinaneutral
or fearful mode. (b) Example of an experimental run and timing. Participants were given an explicit task being instructed to press a button when they saw an upside-down
video-clip interspersed among normal videos of body expressions (50%), scrambled ones (25%) and null stimuli (25%). The targets represented 10% of all videos shown. Video
stimuli were shown for 3000ms each with a 1000ms duration black screen between them.
investigation of deficits in visuo-motor abilities (Williams et al.,
2001) and/or face perception (Schultz, 2005).
Thisstudyaimedatinvestigatingthecerebralcorrelatesofview-
ing actions with and without an emotional meaning in a group of
normal subjects and a group of subjects with ASD. Additionally, we
sought to address directly the hypothesis that autism-associated
dysfunction may result from abnormal inter-regional ‘effective’
cerebral connectivity. Normal and ASD adults underwent fMRI
scanning during passive observation of still images (static condi-
tion) and short movies (dynamic condition) of fearful or neutral
actions (see Fig. 1). To ensure sustained attention during stimu-
lus presentation, participants were instructed to detect occasional
upside-down images occurring randomly during a block. This sim-
ple task performed equally well by both groups provided a control
for visual attention. By contrasting movies to still images we iden-
tified brain regions activated by action perception, irrespective of
theiremotionalcontent.Conversely,bycomparingfearful(dynamic
andstatic)toneutral(dynamicandstatic)stimuli,werevealedacti-
vationsintheamygdalaandother‘social’brainareas,irrespectiveof
the presence of dynamic information. These comparisons allowed
us to address directly whether brain areas associated with action
perception and recognition of emotional messages were differen-
tially engaged in the two groups.
2. Materials and methods
2.1. Participants
Twelve adults with a diagnosis of ASD (10 male and 2 female; 10 Asperger
Syndrome and 2 High-functioning Autistic; age range: 18–56) participated in the
experiment. All participants in the ASD group had been diagnosed according to con-
ventional criteria and a review of available medical records confirmed that all met
DSM-IV (American Psychiatric Association, 1996) criteria for ASD. Brief interviews
ensured that none of them suffered from any mental or neurological disorder other
than ASD and that they were free of medication.
The participants of the control group were recruited from a large sample of
healthy individuals (see Berthoz, Wessa, Kedia, Wicker, & Grezes, 2008). Twelve
controls (all adult males), free of current or past psychiatric or neurological dis-
orders, with low levels of current depressive mood (mean depression score±SD
for the French version of the 13-item Beck Depression Inventory (Collet & Cotraux,
1986)=2±1.7) and state anxiety (mean anxiety score±SD for the state por-
tion of the French State-Trait Anxiety Inventory (Bruchon-Schweitzer & Paulhan,
1993)=35±11) on the day of the scanning session were included. Written consent
was obtained after the procedure has been fully explained. The study was approved
by the local Ethics Committee and was conducted in accordance with the Declara-
tionofHelsinki.Theparticipantswerenotspecificallyinformedabouttheaimofthe
study. Control subjects were paid for their participation. The participants’ descrip-
tive statistics are presented in Table 1. The 2 groups did not differ on age or full-scale
IQ (as measured by the Wechsler Abbreviated Scale of Intelligence, Wechsler, 1999).
2.2. Stimuli and experimental design
2.2.1. Materials
48 full-light videos (24 fear and 24 neutral) of 3s were used for the present
experiment. Videos were chosen from a wider set of stimuli on the basis of the
reliability of responses from subjects in a pilot study. Details about this validation
and the edition of stimuli can be found elsewhere (Grèzes, Pichon, & de Gelder,
2007; Pichon, de Gelder, & Grèzes, 2008). The recordings of stimuli involved 12
professional actors (6 females, 6 males) performing the simple action of opening a
door and facing a threat for the “fear” script”, opening the same door in a relaxed
natural manner and looked ahead for the “neutral script”. Actors were filmed in
frontal view. Importantly, faces were blurred afterwards such that only information
from the body was available. 48 static stimuli (24 fear and 24 neutral) were obtained
by selecting a frame at the perceived height of emotional expression.
2.2.2. fMRI experimental design (cf. Fig. 1)
A factorial design with one between-group factor (ASD and controls) and two
within group factors (‘stimuli’: dynamic and static stimuli; ‘emotion’: fearful and
neutral actions) was tested. The experiment consisted of two scanning sessions.
During each, a total of 136 stimuli were presented corresponding to 24 stimuli
from each category (dynamic fear, static fear, dynamic neutral, static neutral), 10
oddball stimuli (upside-down video-clips) and 30 null events (black screen). A stim-
ulus lasted 3s and was followed by a black screen of 600ms. Order of stimuli was
fully randomized. Subjects were asked to press a button each time the image was
upside-down so that trials of interest were uncontaminated by motor response. A
between groups comparison for accuracy and reaction times in the oddball task
was performed. For technical reasons, the motor responses were only recorded
for 8 subjects per group. There was no difference between groups either in terms
of number of responses (Mean Controls=98%, Mean Autistics=85%; Two-sample
T-test, p>0.05) or in terms of reaction times (Mean Controls=1029.53; Mean Autis-
tics=1288.57; Two-sample T-test, p>0.05). The same results were obtained with
the non-parametric Mann–Whitney test (Performance: p=0.279; Reaction Times:
p=0.161). Although it is possible that the small sample size may mask a behavioral
Table 1
Summary of age and IQ characteristics of the ASD and control groups.
Measure ASD (n=12) Control (n=12)Mann–Whitney test
M
S.D.
M
S.D.
Age (years)
IQ
26.6
102
10.4
20.6
21
119
1.6
6.6
p=0.410
p=0.195

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Table 2
Conjunction analysis and between-group comparisons for the contrasts revealing the brain regions activated during the perception of Dynamic vs. Static body expressions,
irrespective of the emotional content [(Fd+Nd)−(Fs+Ns)].
Brain regions MNI coordinates
Z score No. voxels
xyz
Controls and ASD
L Inferior occipital–temporal gyrus
L Middle occipital gyrus (Ba 18)
L Middle temporal gyrus
L Middle occipital gyrus
L Superior occipital gyrus
R Inferior temporal cortex (MT/V5)
R Middle temporal gyrus
R Superior temporal gyrus
R Superior temporal sulcus (STS)
R Inferior occipital gyrus
R Inferior occipital gyrus (Ba 18/17)
R Intraparietal sulcus
R Superior occipital gyrus
R Precentral gyrus (Ba 6)
R Inferior frontal gyrus (Ba 44/45)
L Temporo-parietal junction, STG
−50
−28
−52
−24
−24
50
48
56
56
44
28
32
36
44
44
−68
−76
−88
−56
−94
−94
−76
−58
−40
−46
−68
−96
−50
−78
05.26
4.68
4.00
4.40
3.59
3.79
4.56
4.18
3.75
3.53
4.43
3.83
3.61
3.30
3.08
3.06
1699
1699
1699
1699
1699
2312
2312
2312
2312
2312
202
44
82
39
24
2
8
30
6
0
16
10
−16
4
50
24
54
24
16
4
1812
15
−46
Controls>ASD
R Temporo-parietal junction, STG
R Inferior temporal gyrus (MT/V5)
L Inferior temporal gyrus
R Medial superior frontal gyrus
R Superior temporal sulcus, middle part
R Precentral gyrus (Ba 6)
L Inferior frontal gyrus (Ba 44/45)
R Precuneus
R Middle frontal gyrus
R Inferior temporal gyrus (MT/V5)
R Fusiform gyrus/cerebellum
54
46
−36
−74
−54
48
−32
−4
16
−68
14
−72
−42
18
−6
4.32
3.72
3.52
3.63
3.63
3.47
3.39
3.37
3.33
3.15
3.10
54
204
71
40
126
14
13
13
36
18
16
−52
14
48
44
−64
10
54
−54
42
0
54
0
50
12
56
50
6
−26
p≤0.001 non-corrected. The direct comparisons were masked inclusively by the contrast of each group at p<0.001.
difference between the two groups, we would like to emphasize that none of our
fMRI results and their interpretation presented below are related to the behavioral
performance. The oddball task was designed as to ensure that subjects would pay
attention to the stimuli. In this respect, the level of performance in both groups
indicates that the subjects were indeed attending to the stimuli and detected with
accuracy far above the chance level if a stimulus was played upside down.
2.3. fMRI data acquisition
Images were acquired using a 3-T whole-body imager equipped with a
circular polarized head coil. For each participant, we first acquired a high-
resolution structural T1-weighted anatomical image (inversion-recovery sequence,
1mm×0.75mm×1.22mm) parallel to the AC–PC plane, covering the whole brain.
For functional imaging, we used a T2*-weighted echo-planar sequence at 36 inter-
leaved 3.5-mm-thick axial slices with 1mm gap (TR=2995ms, TE=35ms, flip
angle=80◦, FOV=19.2cm×19.2cm, 64×64 matrix of 3mm×3mm voxels). For
each session, 173 volumes were acquired.
2.4. fMRI data: statistical analyses
Image analysis was performed with SPM2 (Statistical Parametric Mapping,
www.fil.ion.ucl.ac.uk/spm). The first 4 volumes of each functional session were dis-
carded to allow for T1 equilibration effects. The remaining 169 functional images
were reoriented, slice-time corrected to the middle slice and spatially realigned
to the first volume. These images were normalized to the standard MNI template
and sub-sampled at an isotropic voxel size of 2mm. The normalized images were
smoothedwithanisotropic6-mmfull-width-half-maximum(FWHM)Gaussianker-
nel.
A two-stage general linear model was used to examine the effect sizes of each
key condition and compare them to the group level. Statistical analysis was also
carried out using Statistical Parametric Mapping (SPM2). At the first level, the five
following conditions were modelled for each session for each subject: two where
subjects saw fearful body expressions, presented in dynamic (Fd) or static format
(Fs), two where subjects saw neutral body expressions presented in dynamic (Ns)
or static formats (Nd), one where subjects saw oddball-inverted stimuli (Odd). Null
events were implicitly modelled. The BOLD response to the stimulus onset for each
event-type was convolved with a canonical haemodynamic response function of
3s. Also included for each subject session were six covariates, corresponding to the
temporal derivatives of the realignment parameters (the 3 rigid-body translations
and 3 rotations determined from initial image co-registration) in order to capture
residual movement-related artefacts, plus a single covariate representing the mean
(constant)BOLDsignaloverscans.Thedatawerehigh-passfilteredwithafrequency
cut-off at 128s.
To compare the groups, a random effects analysis was performed consisting of
ANOVAs implemented in SPM2. To do this, we first created images of parameter
estimates for the following contrasts for each subject at the first level:
1. Main effects of Dynamic vs. Static actions [(Fd+Nd)−(Fs+Ns)] (see Table 2).
2. Main effects of Fearful vs. Neutral actions [(Fs+Fd)−(Ns+Nd)] (see Table 3).
3. Interaction between Fearful and Dynamic actions [(Fd−Fs)−(Nd−Ns)] (see
Table 4).
These contrast images were smoothed with an isotropic 6-mm full-width-
half-maximum (FWHM) Gaussian kernel. The effect of Group (Controls vs. ASD)
was then computed for each of the 3 contrasts. A non-sphericity correction was
applied for variance differences between groups. For each ANOVA, we performed
a conjunction analysis to investigate regions of activation that were common to
both ASD and control groups. This analysis allows rejection of the null hypothesis
only if all the comparisons in the conjunction are individually significant (Friston,
Penny, & Glaser, 2005). We also calculated the contrasts between groups to reveal
brain areas that were significantly more activated in one group compared to the
other.
The statistical parametric maps for the conjunction analyses and the between-
group comparisons were thresholded at Z=3.09, p≤0.001 (uncorrected). These
maps were overlaid on the MNI template and labeled using the atlas of Duvernoy
(1999) and the anatomy toolbox (www.fzjuelich.de/ime/spm anatomy toolbox and
for a description, Eickhoff et al., 2005).
2.5. fMRI data: connectivity analyses
Connectivity analyses were carried out with the DCM toolbox in SPM2. Func-
tional imaging data were remodelled at the first level for each subject and for each
session, with a design matrix comprising the five following regressors, encoding
(a) dynamic trials, (b) static trials, (c) fearful trials, and (d) neutral trials and (e)
oddball-inverted trials. Null events were implicitly modelled. The BOLD response
to the stimulus onset for each event-type was convolved with a canonical haemo-
dynamic response function of 3s. Also included for each subject session were six
covariates, corresponding to the temporal derivatives of the realignment parame-
ters (the 3 rigid-body translations and 3 rotations determined from initial image
co-registration) in order to capture residual movement-related artefacts, plus a sin-

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Table 3
Conjunction analysis and between-group comparisons for the contrasts revealing the brain regions activated during the perception of Fearful vs. Neutral actions, irrespective
of Static or Dynamic information [(Fs+Fd)−(Ns+Nd)].
Brain regionsMNI coordinates
Z score No. voxels
xyz
Controls and ASD
L Inferior temporal gyrus (MT/V5)
R Superior temporal sulcus (STS)
R Inferior temporal gyrus (MT/V5)
L Linual gyrus (Ba 18)
L Superior temporal sulcus (STS)
−48
54
48
−24
−46
−76
−44
−64
−100
−52
43.86
3.07
3.14
3.23
3.23
87
86
71
22
55
10
6
−10
10
Controls>ASD
R Inferior frontal gyrus (Ba 45)
R Precentral gyrus (Ba 6)
R Inferior temporal gyrus
R Precentral gyrus (Ba 6)
R AMG
R Middle/inferior temporal gyrus
52
44
46
22
36
58
22
−6
−16
−16
−4
−44
03.71
3.53
3.33
3.12
3.03
3.01
46
76
21
11
6
10
56
−24
74
−20
−6
ASD>Controls
L Medial anterior superior frontal gyrus -6 6210 3.6210
p≤0.001 uncorrected; the direct comparisons were masked inclusively by the contrast of each group at p<0.001.
Table 4
Conjunctionanalysisandbetween-groupcomparisonsforthecontrastsrevealingthebrainregionsactivatedfortheinteractionbetweenFearfulbodyexpressionandDynamic
information [(Fd−Fs)−(Nd−Ns)].
Brain regionsMNI coordinates
Z scoreNo. voxels
xyz
ASD and Controls
R Superior temporal sulcus (STS)60
−4810 3.1711
Controls>ASD
R Precuneus
R Superior temporal sulcus (STS)
R Inferior frontal gyrus, pars triangularis
R Middle cingulate cortex
R Linual gyrus (Ba 17/18)
18
44
62
12
16
−54
−60
28
−42
−60
48
20
20
44
4.29
4.19
3.52
3.50
3.21
32
19
21
13
178
ASD>Controls
R Temporal gyrus, anterior part
L Temporal pole/insula
L Temporo-parietal junction
440
−20
−16
20
5.08
3.94
4.90
65
19
27
−34
−36
10
−38
p≤0.001 uncorrected; the direct comparisons were masked inclusively by the contrast of each group at p<0.001.
gle covariate representing the mean (constant) BOLD signal over scans. The data
were high-pass filtered with a frequency cut-off at 128s.
For each subject, two dynamic causal models were then constructed which
involved 6 right-lateralized regions of interest. These included the right occipital
gyrus (OCC) [mean coordinates Controls (x, y, z): 30, −98 4; mean coordinates ASD
(x, y, z): 28 −96 2], the right superior temporal sulcus (STS) [mean coordinates Con-
trols(x,y,z):58−4010;meancoordinatesASD(x,y,z):56−4010],therightfusiform
gyrus (FG) [mean coordinates Controls (x, y, z): 44 −58 −20; mean coordinates ASD
(x, y, z): 44 −58 −18], the right amygdala (AMG) [mean coordinates Controls (x, y, z):
24−4−20;meancoordinatesASD(x,y,z):240−22],therightpremotorcortex(PM)
[mean coordinates Controls (x, y, z): 44 0 54; mean coordinates ASD (x, y, z): 42 0 52]
and the right inferior frontal gyrus (IFG) [mean coordinates Controls (x, y, z): 52 26
0; mean coordinates ASD (x, y, z): 56 28 0]. The coordinates (in terms of x, y and z)
did not differ between the 2 groups (p>0.05). The above mentioned 6 ROIs, defined
as 5mm-radius spheres, were extracted on peak effects in each subject-specific sta-
tistical parametric map at p=0.05 and adjusted for effect of interests. To do so, we
used the coordinates found in the control group only as a start, to then look, in each
subject-specific statistical parametric, for the closest maxima which corresponded
to the individual peak effect.
The ROIs were then fed into separate DCMs for each subject/session. In the first
model, a stimulus function that encoded the visual input (Dynamic and Static stim-
uli)wasconnectedtotherightSTS(seeFig.4,schema),whereasinthesecondmodel,
it was connected to the OCC. In the first model (STS, AMG, PM, IFG), “bilinear terms”
which refer to changes in effective connectivity were specified to examine the influ-
ence of context type on all backward and forward connections between the STS,
the AMG, the PM and the IFG (see Fig. 4, schema). This influence was encoded as
a canonical haemodynamic response function of 3s, indicating the context type
(neutral or fearful). The second DCM model also comprised backward and forward
connections between OCC and FG, OCC and STS, STS and AMG, as well as FG and
AMG. This later model aimed at testing whether there was a failure of feed-forward
visual signals to reach STS and/or AMG from fusiform and extra-striate regions as
previously suggested in the literature (Castelli, Frith, Happe, & Frith, 2002; Pierce et
al.,2004;Schultz,2005).Theconnectionsbetweenourregionsofinterestwithinthe
twoestimatedDCMmodelsweremotivatedbyourcurrentknowledgeofanatomical
connections in macaque monkeys (Amaral, Behniea, & Kelly, 2003; Amaral & Price,
1984; Avendano, Price, & Amaral, 1983; Barbas, 2000; Carmichael & Price, 1995;
Luppino, Calzavara, Rozzi, & Matelli, 2001).
After DCMs had been estimated, we extracted and averaged the coefficients
across sessions for each subject and then take the ensuing subject-specific parame-
ters to a second level for population inference (Holmes & Friston, 1998) using SPSS
software. The modulatory effects for the comparison between Fearful and Neutral
contexts on the connectivity strength are presented for the ASD and control groups
in Tables 5 and 6 and are shown in Fig. 4. Two-sample T-tests were used to assess
statistical significance. A threshold of p<0.05 was used for all connectivity analyses.
3. Results and discussion
First, we assessed the commonalities between the two groups
while subjects perceived dynamic as compared to static whole-
body actions. To do so we performed a conjunction analysis for the
contrasts between dynamic and static stimuli in each group thus
revealing a common distributed network of brain regions. This net-
work includes the posterior part of the superior temporal sulcus
(STSp), the intraparietal sulcus (IPS), the precentral gyrus and the
dorsal part of inferior frontal gyrus (BA 6 and BA 44) (cf. Fig. 2a–d
and Table 2). The identified set of brain areas corresponds to the
areas frequently observed in previous human and non-human pri-
mate studies of action perception and motor execution and it is

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Fig. 2. (a) Brain regions common to ASD and controls as revealed by a conjunction analysis (Green) or specific to controls (Blue) showing amplitude differences when
subjects saw Dynamic vs. Static body expressions, irrespective of emotional content and rendered on the MNI brain. (b) Common activation of the right premotor cortex (PM)
superimposed on a saggital section of the MNI brain and mean value of the parameter estimates (arbitrary units, mean centered) for the maxima of the right PM (x, y, z=44
4 54) for both groups. (c) Common activation of the right intraparietal sulcus (IPS) superimposed on a coronal section of the MNI brain and mean value of the parameter
estimates (arbitrary units, mean centered) for the maxima of the right IPS (x, y, z=32 −50 50) for both groups. (d) Common activation of the right superior temporal sulcus
(STS) superimposed on a coronal section of the MNI brain and mean value of the parameter estimates (arbitrary units, mean centered) for the maxima of the right STS (x, y,
z=50 −46 10) for both groups.