A JOURNAL OF NEUROLOGY
Atypical neural self-representation in autism
Michael V. Lombardo,1Bhismadev Chakrabarti,1,2Edward T. Bullmore,3Susan A. Sadek,1
Greg Pasco,1Sally J. Wheelwright,1John Suckling,3MRC AIMS Consortium* and
1 Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
2 Department of Psychology, University of Reading, Reading, UK
3 Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge, UK
*The members of the MRC AIMS Consortium are placed in the Appendix 1.
Correspondence to: Michael V. Lombardo,
Autism Research Centre,
18B Trumpington Rd,
Cambridge CB2 8AH,
The ‘self’ is a complex multidimensional construct deeply embedded and in many ways defined by our relations with the social
world. Individuals with autism are impaired in both self-referential and other-referential social cognitive processing. Atypical
neural representation of the self may be a key to understanding the nature of such impairments. Using functional magnetic
resonance imaging we scanned adult males with an autism spectrum condition and age and IQ-matched neurotypical males
while they made reflective mentalizing or physical judgements about themselves or the British Queen. Neurotypical individuals
preferentially recruit the middle cingulate cortex and ventromedial prefrontal cortex in response to self compared with
other-referential processing. In autism, ventromedial prefrontal cortex responded equally to self and other, while middle cingu-
late cortex responded more to other-mentalizing than self-mentalizing. These atypical responses occur only in areas where
self-information is preferentially processed and does not affect areas that preferentially respond to other-referential information.
In autism, atypical neural self-representation was also apparent via reduced functional connectivity between ventromedial
prefrontal cortex and areas associated with lower level embodied representations, such as ventral premotor and somatosensory
cortex. Furthermore, the magnitude of neural self-other distinction in ventromedial prefrontal cortex was strongly related to the
magnitude of early childhood social impairments in autism. Individuals whose ventromedial prefrontal cortex made the largest
distinction between mentalizing about self and other were least socially impaired in early childhood, while those whose
ventromedial prefrontal cortex made little to no distinction between mentalizing about self and other were the most socially
impaired in early childhood. These observations reveal that the atypical organization of neural circuitry preferentially coding
for self-information is a key mechanism at the heart of both self-referential and social impairments in autism.
Keywords: functional neuroimaging; mentalizing; self; autism
Abbreviations: ADI-R=Autism Diagnostic Interview Revised; ADOS=Autism Diagnostic Observational Schedule; BA=Brodmann
Area; BOLD=blood oxygenated level dependent; FDR=false-discovery rate; fMRI=functional magnetic resonance imaging;
FO/PMv=frontal operculum/ventral premotor cortex; MNI=Montreal Neurological Institute; OM=other-mentalizing;
OP=other-physical; PPI=psychophysiological interaction; ROI=region of interest; SI/SII=somatosensory cortex;
SM=self-mentalizing; SP=self-physical; SVC=small-volume correction
doi:10.1093/brain/awp306Brain 2009: Page 1 of 14 |
Received July 9, 2009. Revised October 17, 2009. Accepted October 21, 2009.
? The Author (2009). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved.
For Permissions, please email: email@example.com
Brain Advance Access published December 13, 2009
The self is a complex multidimensional construct key to many
disciplines, including psychology,
neuroscience, among many others. The self is deeply embedded
in the social world and is integral to many aspects of social
behaviour and cognition (Brewer, 1991; Banaji and Prentice,
1994). One example of this integral relationship between the
self and the social world is clearly seen in simulationist theories
of social cognition (Goldman, 2006). The main premise of simula-
tion theory is that an understanding of others occurs through
the use of privileged access to self-representations. In the general
population, evidence from infants (Meltzoff and Brooks, 2008),
toddlers (Birch and Bloom, 2003), and adults (Ames, 2004; Epley
et al., 2004; Birch and Bloom, 2007) suggests that representa-
tions about others are ‘anchored’ in processes centred on self-
representations. This simulative
context-dependent strategies that one learns throughout develop-
ment when navigating the social world.
Similarly, in the brain, neural representations of self and other
recruit largely identical neural circuitry. During low level embo-
died/simulative processes, areas in anterior insula, middle cingulate
cortex, frontal operculum/ventral premotor cortex (FO/PMv) and
somatosensory cortex (SI/SII) respond both to our own actions,
emotions, and sensations and when we observe others acting or
experiencing similar emotional or somatosensory states (Wicker
et al., 2003; Keysers et al., 2004; Singer et al., 2004; Blakemore
et al., 2005; Gazzola and Keysers, 2009). Additionally, during
higher level inference-based processes, the medial prefrontal
cortex, posterior cingulate/precuneus, and temporo-parietal junc-
tion are recruited both when we reflect on ourselves and others
(Ochsner et al., 2005; Amodio and Frith, 2006; Mitchell et al.,
2006; Saxe et al., 2006). Emerging evidence also suggests that
these two neural circuits for shared representations of self and
other interact during high level social cognitive processing
(Zaki et al., 2009; Lombardo et al., 2010b) and may set the
foundation for how we make sense of the complex social world.
Among this distributed network coding for shared representa-
tions, the ventromedial prefrontal cortex (vMPFC) possesses some
special characteristics that make it a crucial centre for neural
cortex responds in a preferential manner for information that is
self-relevant (Moran et al., 2006) even in the absence of explicit
self-referencing (Moran et al., 2009). This preferential tuning for
self-relevant information is apparent even when the task is to
think about others’ impressions of ourselves (Ochsner et al.,
2005; D’Argembeau et al., 2007; Izuma et al., 2008), during
on-line tracking of how our own actions influence others
(Hampton et al., 2008), or when thinking about others who
simply share some variance with oneself, such as similar or close
others (Ochsner et al., 2005; Mitchell et al., 2006; Jenkins et al.,
2008; Mobbs et al., 2009). In preferentially responding to
self-relevant information, the ventromedial prefrontal cortex dis-
tinguishes self-referential from other-referential processing (partic-
ularly for familiar but non-close others) (Craik et al., 1999; Kelley
et al., 2002; Vogeley et al., 2004; David et al., 2006; Pfeifer
et al., 2007). These attributes of the ventromedial prefrontal
psychiatry, philosophy and
anchoring is oneof many
The ventromedial prefrontal
cortex make it a key neural mechanism that distinguishes self
from other, specifically through the coding of self-information.
This neural distinction between self and other enables us to appre-
ciate the similarities and differences between our own and others’
minds (Brewer, 1991; Amodio and Frith, 2006) and is critical
since accurate mentalizing/empathizing and appropriate social
context-dependent strategies that may either use the self as the
anchor point for modelling others’ minds, but also in instances
where de-centring from the self is crucial (Epley et al., 2004).
Individuals with autism spectrum conditions display marked
difficulties in reciprocal social interaction. However, while clinically
important, focusing exclusively on the interpersonal difficulties in
autism may overshadow the importance of the self in underlying
such difficulties. Historically, the self has always been integral in
defining autism. The word ‘autism’ derives from the Greek word
‘autos’ and literally translates to ‘self’. Early clinical accounts
(Kanner, 1943; Asperger, 1944) anecdotally suggested that
individuals with autism spectrum conditions are completely
self-focused or ‘egocentric in the extreme’. Later work demon-
strated that this egocentrism (Frith and de Vignemont, 2005)
may be manifest in the lack of viewing oneself as embedded
within social contexts (Lee and Hobson, 1998) and via the lack
of distinguishing self from other (Loveland and Landry, 1986;
Jordan, 1989; Lee et al., 1994; Lee and Hobson, 2006; Mitchell
and O’Keefe, 2008). In addition to this lack of distinguishing self
from other, individuals with autism also have marked difficulties in
self-referential cognitive processing. These difficulties extend to
reflecting on one’s own false beliefs (Baron-Cohen, 1989; Perner
et al., 1989; Leslie and Thaiss, 1992; Williams and Happe, 2009),
or intentions (Phillips et al., 1998; Williams and Happe, in press),
self-conscious emotion recognition and experience (Kasari et al.,
1993; Heerey et al., 2003; Hobson et al., 2006), self-referential
understanding of emotion (Hill et al., 2004; Lombardo et al.,
2007; Silani et al., 2008), autobiographical/episodic memory
(Klein et al., 1999; Crane and Goddard, 2008), and marked def-
icits in the facilitative effect that the self has on memory encoding
and retrieval processes (Toichi et al., 2002; Lombardo et al., 2007;
Henderson et al., 2009).
The co-occurrence of both egocentrism and impairments in
self-referential cognitive processing in autism has led to several
ideas that can broadly be characterized under the ‘absent-self’
hypothesis (Hurlburt et al., 1994; Frith and Happe, 1999; Frith,
2003; Happe, 2003; Baron-Cohen, 2005; Frith and de Vignemont,
2005; Hobson et al., 2006). Rather than implying a complete lack
of self in autism (as the word ‘absent’ might suggest), the
absent-self hypothesis proposes that a specific kind of higher
order self-awareness, possibly administering top-down control,
may be missing in autism. As observations from patients with
focal lesions in the ventromedial prefrontal cortex may suggest,
deficits in this type of higher order self-awareness are likely to
have detrimental consequences on social behaviour (Beer et al.,
2006). One such consequence in autism may be in appreciating
the dual nature of oneself in the social world, as an agent who is
both similar to, yet different from others (Frith, 2003; Frith and
de Vignemont, 2005; Hobson and Meyer, 2005; Hobson et al.,
2006). In other words, an intrapersonal deficit in high level
Brain 2009: Page 2 of 14 M. V. Lombardo et al.
self-awareness may be tightly linked to the interpersonal deficits in
autism. Thus, the absent-self hypothesis makes two key predic-
tions about the nature of the autistic self and its relation to
social impairment. First, neural self-representation may be atypical
in autism. Secondly,the atypical
self-representations may be intrinsically tied to the social impair-
ments in autism.
To test these predictions, we designed a functional magnetic
resonance imaging (fMRI) study where participants were scanned
while reflecting on the self or a familiar non-close other (the British
Queen) in either a mentalistic or a physical way. Quantitative
meta-analyses across all normative neuroimaging studies to date
that contrast self from other (e.g. Self4Other; see online supple-
mentary material for the meta-analysis) demonstrate that the two
most consistent and robust of these Self4Other effects are in the
ventromedial prefrontal cortex
Institute (MNI) coordinate x=?2, y=42, z=?8] and middle
cingulate cortex (peak MNI coordinate x=0, y=0, z=38). Based
on this and other studies which find abnormalities in both ventro-
medial prefrontal cortex (Kennedy et al., 2006; Di Martino et al.,
2009) and the middle cingulate cortex (Chiu et al., 2008; Di
Martino et al., 2009) in autism, we predicted that these critical
areas involved in preferentially coding for self-information are dis-
rupted in autism and that such disruptions are related to the social
impairments in autism.
Finally, a growing literature supports the idea that the neural
mechanisms underlying autism are due to atypical neural connec-
tivity (Belmonte et al., 2004; Just et al., 2004; Minshew and
Williams, 2007). Previous theoretical work on embodied cognition
(Barsalou, 1999; Aziz-Zadeh and Damasio, 2008) suggests that the
neural mechanisms underlying high level conceptual representa-
tions are likely to be tightly integrated (i.e. functionally connected)
with lower level ‘embodied’ sensorimotor representations that deal
with mirroring of actions, emotions and sensations (Wicker et al.,
2003; Keysers et al., 2004; Singer et al., 2004; Blakemore et al.,
2005; Gazzola and Keysers, 2009). These theories predict that
conceptual representations interact with the same sensorimotor
circuitry engaged during the enactment or experience of such
concepts (Aziz-Zadeh et al., 2006). Evidence has emerged demon-
strating that high level social cognitive processes such as accurate
empathic processing engages both medial prefrontal cortex and
circuitry involved in low level embodied sensorimotor representa-
tions (Zaki et al., 2009). Thus, we predicted that in the typical
brain, high level conceptual self-representation within the ventro-
medial prefrontal cortex should be tightly connected to lower level
embodied sensorimotor areas such as somatosensory cortex and
frontal operculum/ventral premotor cortex (FO/PMv) (Avenanti
et al., 2005, 2007; Iacoboni and Dapretto, 2006; Gazzola and
Keysers, 2009). Individuals with autism spectrum conditions have
deficits in embodied sensorimotor representations (Dapretto et al.,
2006; Cattaneo et al., 2007; Haswell et al., 2009; Minio-Paluello
et al., 2009) and it has been speculated that in autism, interactions
between embodied neural circuits and high level conceptual rep-
resentation may be atypical (Iacoboni, 2006; Uddin et al., 2007;
Williams, 2008). Therefore, we predicted such connectivity pat-
terns would be reduced in autism spectrum conditions.
Thirty-three typically developing male adult participants (mean age
27.97 years?6.10 SD, range 18–42) and 33 male adults with
autism spectrum conditions (mean age 26.59 years?7.04 SD, range
18–41) participated in this study. Both groups were matched on
age and all subscales of the Wechsler Abbreviated Scales of
Intelligence (Weschler, 1999) (Table 1). Autism spectrum condition
participants were all diagnosed by ICD-10 criteria for Asperger
Table 1 Participant characteristics
25.87 (6.85) 0.420.31
Abbreviations: ASC=Autism Spectrum Condition; VIQ=Verbal IQ; PIQ=Performance IQ; FIQ=Full-Scale IQ; ADI-R=Autism Diagnostic Interview-Revised;
AQ=Autism Spectrum Quotient; TAS=Toronto Alexithymia Scale; SD=standard deviation; N/A=not applicable. Data are presented as the mean and standard
deviation (in parentheses).
Atypical neural self-representation in autismBrain 2009: Page 3 of 14 |
Syndrome (ICD-10, 1994). The Toronto Alexithymia Scale (Bagby
et al., 1994), Autism Spectrum Quotient (Baron-Cohen et al., 2001),
Autism Diagnostic Interview-Revised (ADI-R) (Lord et al., 1994), and
module 4 of the Autism Diagnostic Observation Schedule (ADOS)
(Lord et al., 2000) were administered to participants before the
fMRI session. Diagnosis was confirmed for 30/33 participants on
the ADI-R. The remaining three participants, who were subthreshold
on the ADI-R, were 1 point below the cut-off on the Repetitive
Behaviour domain. However, these participants were included since
they met ADOS criteria, scored above the cut-off of 26 on the
Autism Spectrum Quotient (Woodbury-Smith et al., 2005), and were
diagnosed by experienced clinicians. Due to movement artifact (three
autism spectrum condition participants)
equipment malfunction (one autism spectrum condition participant),
data for four autism spectrum condition participants were excluded,
and the remaining 29 participants are reported in all subsequent
analyses. Table 1 shows the participant characteristics. Informed con-
sent was obtained for all participants in accord with procedures
approved by the Suffolk Local Research Ethics Committee. All partici-
pants were native English speakers with normal or corrected vision and
The study design was a 2?2 within-subjects factorial block design
where participants were asked to make either reflective ‘Mentalizing’
or ‘Physical’ judgements about two target individuals; the ‘Self’ or
a familiar non-close ‘Other’ (the British Queen). For self-mentalizing
(SM) blocks, participants judged on a scale from 1 to 4 (where 1=not
at all likely and 4=very likely) how likely they themselves would agree
with opinionquestionsthat focused
(e.g. ‘How likely are you to think that keeping a diary is important’).
On other-mentalizing (OM) blocks, the same mentalizing judgements
were made, except this time it was in reference to how likely the
British Queen would agree with the opinion questions (e.g. ‘How
likely is the Queen to think that keeping a diary is important’).
During self-physical (SP) blocks, participants judged how likely they
would agree to opinion questions about their own physical character-
istics (e.g. ‘How likely are you to have bony elbows?’). Conversely,
the same physical judgements were made during other-physical (OP)
blocks, except that participants rated these questions with the Queen
as the target person (e.g. ‘How likely is the Queen to have bony
elbows’). All opinion questions were acquired from Jason Mitchell’s
lab and have been used in previous studies on reflective mentalizing
judgements of the self and others that reliably elicit robust and con-
sistent activity in mentalizing and self-referential neural circuits such as
ventromedial prefrontal cortex (Mitchell et al., 2006; Jenkins et al.,
2008). All stimuli did not differ per condition in the number of char-
acters, syllables, frequency, or valence.
All participants completed one scanning session with one functional
imaging run. Within this run there were 20 trials within each condition
and five blocks per condition. Each trial type was presented in blocks
of four trials and the trial-duration was 4s each (16 s per block). After
each block there was a rest period of 16s where participants fixated
on a cross in the middle of the screen and were instructed to relax.
All trials within blocks and all blocks throughout the functional run
were presented in pseudorandom order. Stimulus presentation was
implemented with DMDX software and the stimulus presentation
computer was synchronized with the onset of the functional run to
ensure accuracy of event timing.
Imaging was performed on a 3T GE Signa Scanner (General Electric
Medical Systems, Milwaukee, WI) at the Cambridge Magnetic
Resonance Imaging and Spectroscopy Unit (MRIS Unit). Our func-
T2*-weighted echoplanar images (slice thickness, 3mm; 0.8mm skip;
33 axial slices; repetition time, 2000ms; echo time, 30ms; flip angle
90?; matrix, 64?64; field of view, 240mm, sequential slice acquisi-
tion). The first five timepoints of the run were discarded to allow for
T2 stabilization effects. In addition, a high-resolution 3D spoiled
gradient anatomical image was acquired for each subject for registra-
Behavioural and region of interest data were analysed in SPSS 16
(http://www.spss.com). Functional MRI data preprocessing and statis-
tics were implemented using SPM5 (Wellcome Trust Centre for
Neuroimaging, http://www.fil.ion.ucl.ac.uk/spm). The preprocessing
steps were conducted in the following manner: slice timing correction,
realignment to the mean functional image, co-registration of the func-
tional data with a high-resolution structural image, segmentation of
the structural image, normalization into standard anatomical space
(MNI) by applying the transformations estimated from the segmenta-
tion step, and spatial smoothing with an 8mm full width half maxi-
mum (FWHM) Gaussian kernel.
Whole-brain statistical analysis was performed using the general
linear model in SPM5. Each trial was convolved with the canonical
haemodynamic response function. High-pass temporal filtering with
a cut-off of 128s was applied to remove low frequency drift in the
time series and global changes were removed by proportional linear
scaling. Serial autocorrelations were estimated with a restricted maxi-
mum likelihood algorithm with an autoregressive model of order 1.
Factorial contrasts images were outputted automatically in the first
level single-subject analysis. To test for a group difference in the inter-
action effect [(SM4SP)4(OM4OP)] we computed two-sample t-tests
on each participant’s interaction effect contrast image from the
single-subject analysis. Group differences in main effects were also
tested with two-sample t-tests on participant’s main effects contrasts.
All results from whole-brain analyses were thresholded at P50.05,
false-discovery rate (FDR) corrected, extent 25 voxels. Regions of
interest in the middle cingulate cortex and the ventromedial prefrontal
cortex were independently selected on the basis of suprathreshold
voxels identified from the quantitative meta-analyses (see online
Supplementary material for details). Follow up statistical analyses to
verify the direction of any voxel-based Group?Condition interaction
effects were done by examining on a within-group basis, the percent
signal change at the peak voxel from the contrast of interest. This was
specifically done because of the inherent limitations in alternatively
interpreting between-group differences on any one condition alone.
Given that the groups are known to differ on physiological measures
(Rumsey et al., 1985; Horwitz et al., 1988; George et al., 1992;
Zilbovicius et al., 1995; Haznedar et al., 2000; Ohnishi et al., 2000;
Hazlett et al., 2004; Kennedy et al., 2006; Kennedy and Courchesne,
2008a) one cannot assume that groups are equivalent in terms of
(BOLD) signal baseline. Thus, follow-up analyses on any interaction
effects are done on a within-group basis.
To explore individual differences in social symptom severity and
activity we ran correlational analyses of ADI-R and ADOS social
subscale scores on self-mentalizing (SM)4other-mentalizing (OM)
Brain 2009: Page 4 of 14M. V. Lombardo et al.
and self-physical (SP)4other-physical (OP) contrasts within ventro-
medial prefrontal cortex and middle cingulate cortex regions of
interest. Comparison of the difference between correlations from
these two contrasts was tested after converting correlation coefficients
to z scores with Fisher’s r to z transform (Steiger, 1980).
Functional connectivity analyses were implemented with ‘psycho-
physiological interaction’ analyses within SPM5 (Friston et al., 1997).
The seed region was the ventromedial prefrontal cortex meta-analytic
region of interest. Time courses from the seed region were extracted
and multiplied by a condition vector of 0, 1 or ?1, where self-trials
were coded as 1, other-trials were coded as ?1, and all other events
were 0. The product vector of (time courses?condition vector) was
our psychophysiological interaction vector. The seed time course, con-
dition vector, and psychophysiological interaction vector were entered
as regressors into individual subject analyses and contrast maps
were computed for the psychophysiological interaction regressor.
Psychophysiological interaction contrast maps for each participant
were entered into a second level random effects group analysis thresh-
olded at P50.05 (FDR corrected, extent 25 voxels) across the whole
brain. For a priori hypotheses in regards to the somatosensory cortex
and the frontal operculum/ventral premotor cortex, regions of interest
of Brodmann area 1/2 for somatosensory cortex, and Brodmann area
44 for frontal operculum/ventral premotor cortex, were defined from
the SPM Anatomy toolbox (Eickhoff et al., 2005) (see online
Supplementary material for details).
Participants in both groups were matched on age and IQ
(Table 1). Replicating prior work (Hill et al., 2004; Lombardo
et al., 2007; Silani et al., 2008), we also observed a group differ-
ence in alexithymia. Autism spectrum condition participants report
significantly more alexithymic traits than controls [controls, 42.88;
ASC, 59.28; t(60)=6.26, P=4.44?10?8].
We conducted separate group (control, ASC)?target (self,
other)?judgement (mentalizing, physical) repeated measures
ANOVAs for relevance ratings and reaction-times during the
fMRI task. The analysis of relevance ratings revealed non-
significant 3-way and 2-way interactions (all P40.40), indicating
that the groups rated the judgements similarly. While the main
effect of target was non-significant (P = 0.51), the main
effect for Judgement was highly significant [F(1,60)=171.931,
P50.0001], such that mentalizing trials were judged to be more
relevant than physical trials (Table 2).
group?target interaction [F(1,60)=6.088, P=0.016] and main
effects of target [F(1,60)=7.383, P=0.009] and judgement
[F(1,60)=11.379, P=0.001]. The group?target interaction was
due to the control group responding faster for self-judgements
than the autism spectrum condition group, while the main effect
of Judgement was due to faster responses to mentalizing judge-
ments (Table 2). However, given the unconstrained nature of the
task (i.e. no explicit instruction to respond as quickly as possible),
reaction-time cannot necessarily be assumed to be a measure of
‘efficient performance’ on the task and is unlikely to affect the
fMRI data comparisons. To check this, we pair-wise matched par-
ticipants in each group based on reaction-time during the task.
This procedure resulted in 23 participants in each group (still
matched on age and IQ, Table 1) and eliminated the group?tar-
time-matched participants produced identical fMRI results to
those of the entire sample. Thus, similar to other studies that
find no effects of reaction-time on activity elicited during similar
tasks (Mitchell et al., 2006; Pfeifer et al., 2007), we can rule out
any interpretation of the fMRI group differences as simply a func-
tion of reaction-time group differences (see online Supplementary
fMRI data: Atypical neural
Our first analysis evaluated group differences in the interaction
effect among all four conditions [e.g. (SM4SP)4(OM4OP)].
Given the a priori hypothesis for the middle cingulate cortex
and the ventromedial prefrontal cortex, we ran region of interest
analyses using the meta-analytic regions of interest as the search
space and employing false-discovery rate (FDR) small volume cor-
rection (SVC) within each region of interest. This analysis revealed
a significant group difference (controls4ASC) in the interaction
(Brodmann area 24, MNI x=2, y=4, z=42, t=3.27, P=0.016
FDR, small volume corrected) but not the ventromedial prefrontal
cortex. The middle cingulate cortex peak was six voxels away in
Euclidean distance from the meta-analysis peak of x=0, y=0,
Based on a previous study (Chiu et al., 2008) that observed
marked reductions in middle cingulate cortex activity during
the middle cingulatecortex
Table 2 fMRI rating and reaction-time data
Condition Controls rating,
Abbreviations: SM=self-mentalizing; OM=other-mentalizing; SP=self-physical; OP=other-physical; ASC=autism spectrum condition. Data are given as the mean and
standard deviation (in parentheses).
a Reaction-time data is in milliseconds.
Atypical neural self-representation in autismBrain 2009: Page 5 of 14 |
self-decisions in a social context, we hypothesized that this effect
was due to atypical recruitment of the middle cingulate cortex
change was extracted from the peak voxel in the middle cingulate
cortex and planned comparisons between self-mentalizing and
other-mentalizing were made separately for each group with
paired samples t-tests. In the autism spectrum condition group
there was reduced activation during self-mentalizing compared
with other-mentalizing [t(28)=2.18, P=0.04] while controls
showed increased activation during self-mentalizing compared
with other-mentalizing [t(32)=3.118, P=0.004] (Fig. 1 and
Table 3, panel a). A whole-brain analysis corrected for multiple
comparisons across the whole brain (P50.05, FDR corrected)
revealed no other significant group differences.
To examinethis, signal
Next, we examined the main effect of increased activa-
tion during self-judgements compared with other-judgements
(Self4Other) collapsing across
judgements. Whole-brain analyses within the control group
revealed that the ventromedial prefrontal cortex (Brodmann area
10/11) and cerebellum was activated more for self than other
(Fig. 2a and Table 3, panel b). In contrast, within the autism
spectrum condition group there was no significant difference in
activation for self compared with other (Fig. 2b). Given the a
priori hypotheses regarding group differences in the ventromedial
prefrontal cortex and the middle cingulate cortex, we next ran a
region of interest analysis constrained to a search space within the
meta-analytic regions of interest. Hypoactivation in the autism
spectrum condition group (e.g. controls4ASC) for this contrast
(Self4Other) was found in the ventromedial prefrontal cortex
(Brodmann area 10/11, MNI x=?4, y=46, z=?10, t=4.12,
P=0.016 FDR, small volume corrected) but not the middle
cingulate cortex. This ventromedial prefrontal cortex peak was
6.63 voxels away in Euclidean distance from the meta-analysis
peak of x=?2, y=42, z=?8.
To further qualify the nature of this group?target effect in
ventromedial prefrontal cortex we extracted the signal change
from the peak voxel and specifically compared self with other in
each group separately. The ventromedial prefrontal cortex was
more active in controls for self compared with other-judgements
[F(1,32)=17.43, P=2.13?10?4], while within the autism spec-
trum condition group, ventromedial prefrontal cortex activation
was equivalent across self- or other-judgements [F(1,28)=0.808,
P=0.376] (Fig. 2c and Table 3, panel c). This effect remained in
the subset ofbehaviour-matched
Supplementary material). Whole-brain analyses corrected for mul-
tiple comparisons across the whole brain (P50.05, FDR corrected)
revealed no other significant group differences.
Following these analyses, we flipped the main effect of target in
order to examine group differences in other-referential compared
with self-referential processing (e.g. Other4Self). Controls recruit
virtually identical regions to those of the autism spectrum group
(Supplementary Table S2, panels a and b) and the analysis of
Table 3 fMRI activation results
Anatomical labelHemiBA MNI (x,y,z)t-valueP(FDR) Cluster size
Panel a: Controls4ASC (SM4SP)4(OM4OP) interaction effecta
Middle cingulate cortexB
2, 4, 42
?4, 2, 36
6, ?10, 46
2, ?22, 42
Panel b: Controls Self4Other
ventromedial prefrontal cortexL 10/11
?6, 50, –6
?4, 62, 2
22, ?82, ?24
Cerebellum lobe crus I
Panel c: Controls4ASC Self4Othera
ventromedial prefrontal cortex
?4, 46, –104.120.016
Abbreviations: ASC=autism spectrum conditions; Hemi=hemisphere; L=left; R=right; B=bilateral; BA=Brodmann area; MNI=Montreal Neurological Institute;
FDR=false-discovery rate; SM=self-mentalizing; SP=self-physical; OM=other-mentalizing; OP=other-physical.
a Results are from a priori region of interest analyses using FDR small volume correction at P50.05.
Figure 1 Activation in middle cingulate cortex for self-
mentalizing (SM) compared with other-mentalizing (OM)
(SM4OM). This figure shows group differences in the middle
cingulate cortex response (MNI x=2, y=4, z=42; thresholded
at P50.005, uncorrected for display purposes) to SM
compared with OM (SM4OM) for controls (left) and autism
spectrum conditions (ASC) (right). Error bars indicate ?1 SEM.
**P50.005; *P50.05. Note that percent signal change values
cannot be assumed to represent equivalent values between-
groups, because groups may differ in their underlying
physiological baseline level of activity.
Brain 2009: Page 6 of 14M. V. Lombardo et al.
group differences on this contrast revealed no significant differ-
ences across the whole brain. This analysis demonstrates that the
groups do not differ in the neural systems recruited preferentially
for thinking about others compared with oneself.
Altered functional connectivity during
In our functional connectivity analyses, we employed psycho-
physiological interaction analyses to determine which areas show
greater changes in functional connectivity during self-judgements
compared with other-judgements. Specifically, we looked at
connectivity from the ventromedial prefrontal cortex using the
region. Controls exhibited greater ventromedial prefrontal cortex
judgements within a wide distribution of regions, comprising fron-
tal operculum/ventral premotor cortex, somatosensory cortex and
middle cingulate cortex extending into caudal anterior cingulate
cortex, intraparietal sulcus, visual cortex/cerebellum, temporal
pole, anterior temporal lobe and middle temporal gyrus (Fig. 3
and Table 4, panel a). In the autism spectrum condition group,
no significant results were found at the whole-brain corrected
ofinterestas the seed
P50.05 FDR threshold. Given the specific hypotheses with
regards to group differences in ventromedial prefrontal cortex
connectivity to somatosensory cortex and frontal operculum/
ventral premotor cortex, we ran region of interest analyses
within anatomical regions of somatosensory cortex and frontal
operculum/ventral premotor cortex. These analyses revealed that
the control participants had greater functional connectivity com-
pared with autism spectrum conditions during self-judgements
compared with connectivity during other-judgements (P50.05
FDR, small volume corrected) (Fig. 3 and Table 4, panel b).
No other group differences in connectivity were observed after
whole-brain correction for multiple comparisons (P50.05 FDR
Relationships with social symptom
Next, we examined whether individual differences in social
symptom severity in autism spectrum conditions (as measured
on the ADI-R and ADOS) correlated with activity either during
self-mentalizing (SM)4 other-mentalizing (OM) or self-physical
(SP)4 other-physical (OP). The meta-analytic middle cingulate
cortex and ventromedial prefrontal cortex regions of interest
were used as the search space for this analysis and significant
results passed the FDR small volume corrected threshold. ADOS
and ADI-R social symptom severity did not correlate with middle
cingulate cortex activity. Furthermore, ventromedial prefrontal
cortex activity was not correlated with ADOS social symptom
severity. However, ADI-R social symptom severity was negatively
correlated with ventromedial prefrontal cortex activity during
P=1.27?10?4). This result indicates that those individuals with
autism spectrum conditions whose ventromedial prefrontal cortex
made the biggest distinction between self-mentalizing and other-
mentalizing were the least socially impaired in early childhood,
while those whose ventromedial prefrontal cortex made little to
no distinction between self-mentalizing and other-mentalizing
were the most socially impaired in early childhood. During
SP4OP, no correlation was observed between ventromedial
prefrontal cortex and ADI-R social symptom severity (MNI x=2,
y=44, z=?12, t=0.75, r=?0.14, P=0.20). The difference
between these two correlations (i.e. SM4OM versus SP4OP)
was significant (z=?2.17, P=0.03) (Fig. 4a and b).
Theory and prior research suggest that the neural systems involved
in self-representation are atypically organized in autism. In the
current study, we directly tested this hypothesis in 33 neurotypical
male adults and 29 age and IQ-matched individuals with
autism spectrum conditions. We observed specific disruptions
in the neural systems involved in preferentially coding for
self-information. The first of these effects was in the middle
cingulate cortex. Rather than preferentially responding to self-
mentalizing, the middle cingulate cortex in autism responds
more to other-mentalizing. These observations replicate and
Figure 2 Activation in ventromedial prefrontal cortex (vMPFC)
for self-compared with other-judgements (Self4Other). This
figure displays activation for the Self4Other contrast within (a)
controls, (b) ASC (both displayed at P50.05, FDR corrected).
Panel (c) shows the group difference in activation for
Controls4ASC during Self4Other (MNI x=?4, y=46,
z=?10; thresholded at P50.005, uncorrected for display
purposes). The bar graph depicts the group difference in
activation (controls, left; ASC, right). Error bars indicate ?1
SEM. *P50.0005. Note that percent signal change values
cannot be assumed to represent equivalent values between-
groups, because groups may differ in their underlying
physiological baseline level of activity.
Atypical neural self-representation in autismBrain 2009: Page 7 of 14 |
Table 4 fMRI functional connectivity (PPI) results
Anatomical labelHemiBA MNI (x,y,z)t-value P(FDR)Cluster size
Panel a: Controls, vMPFC PPI, Self4Other
Cerebellum lobe crus I
Cerebellum lobe crus I
Intraparietal sulcus (IPS)
Primary somatosensory cortex (SI)
Frontal operculum/ventral premotor cortex (FO/PMv)
Middle temporal gyrus
?36, ?78, –26
16, ?82, ?10
?40, ?82, –20
?30, ?62, 52
?48, ?34, 54
?48, 4, 32
?34, 20, –24
?54, ?22, –14
?56, ?36, –12
?44, 2, –40
?36, 8, –38
36, ?74, 38
18, ?72, 46
?4, ?4, 50
0, 16, 40
?6, ?50, 0
?46, ?72, 6
?52, ?46, 2
?56, ?58, 2
Anterior inferior temporal gyrus27
Intraparietal sulcus (IPS) 133
Middle cingulate cortex
Caudal anterior cingulate cortex
Cerebellum lobe IV
Middle occipital gyrus
Middle temporal gyrus
Posterior middle temporal gyrus
Panel b: Controls4ASC, vMPFC PPI, Self4Othera
Primary somatosensory cortex (SI)L 1/2
?38, ?32, 44
?40, ?30, 60
?40, ?26, 52
?46, 6, 28
0.053 Frontal operculum/ventral premotor cortex (FO/PMv)L 44
Abbreviations: ASC=autism spectrum conditions; PPI=psychophysiological interaction; Hemi=Hemisphere; L=Left; R=Right; B=Bilateral; BA=Brodmann area;
MNI=Montreal Neurological Institute; FDR=false discovery rate; vMPFC=ventromedial prefrontal cortex.
a Results are from a priori region of interest analyses using FDR SVC at P50.05.
Figure 3 Functional connectivity in ventromedial prefrontal cortex during self-judgements compared with other-judgements
(Self4Other). This figure displays increases in ventromedial prefrontal cortex (seed region labelled in green) connectivity for
self-judgements compared with connectivity during other-judgements (Self4Other). Connectivity within the control group is displayed
on the left and top middle brains, while connectivity within the ASC group is displayed on the right (both displayed at P50.05 FDR
corrected). Group differences (Controls4ASC) in connectivity (bottom middle) are displayed at P50.005, uncorrected for display
Brain 2009: Page 8 of 14 M. V. Lombardo et al.
extend prior work showing reduced activity in the middle cingulate
cortex when making self-decisions in a social context (Chiu et al.,
2008). While the previous study could not discern whether such
effects in the middle cingulate cortex were due to self-mentalizing,
other-mentalizing, or both (Frith and Frith, 2008), the current
study was able to separate both processes independently of
each other. This separation highlights that the disruption of
middle cingulate cortex function is due to reversal of the typical
SM4OM effect in the middle cingulate cortex, such that individ-
uals with autism spectrum conditions recruit this region more for
other-mentalizing than self-mentalizing (OM4SM).
The reversal of the middle cingulate cortex’s preferential response
to self (e.g. OM4SM) is intriguing given that the middle cingulate
cortex responds preferentially to self-relevant information (Moran
et al., 2006) and shows Self4Other effects during trait reflection
(Gutchess et al., 2007; Ersner-Hershfield et al., 2009), visual
perspective taking (Vogeley et al., 2004; David et al., 2006),
empathy for pain (Singer et al., 2004; Jackson et al., 2006;
Lamm et al., 2007) and self-decisions in a social context
(King-Casas et al., 2006; Tomlin et al., 2006; Chiu et al., 2008).
Furthermore, studies on similar or dissimilar others observed that
the middle cingulate cortex responds more to others who are similar
to self than to others who are dissimilar (Mitchell et al., 2006;
Lamm et al., in press). Middle cingulate cortex activity also tracks
with learning parameters that indicate how one’s own actions
influence others (Hampton et al., 2008).
It is also notable that the middle cingulate cortex has been
found to be both structurally and functionally atypical in autism.
In a post-mortem neuropathological study, Vargas et al. (2005)
found increased neuroglial activation and presence of inflamma-
tory cytokines in the middle cingulate cortex, suggesting the pres-
ence of neuroinflammation. In recent quantitative meta-analyses
of fMRI studies in autism, the middle cingulate cortex is an area of
consistent hypoactivation across the literature of studies tapping
social processes, but is not hypo- or hyperactive during non-social
processes (Di Martino et al., 2009). Given these considerations,
the altered role of the middle cingulate cortex in autism is critical
and future research investigating this region is likely to render
new insights into the neural basis of autism.
The second observation of the current study is the complete
lack of preferential responsiveness to self-information in the
While controls significantly recruited the ventromedial prefrontal
cortex more for self than other, individuals with autism did not.
Instead, the ventromedial prefrontal cortex treated self and
other equivalently in autism. This equivalence for self and other
is striking since previous behavioural studies have shown that
individuals with autism do not benefit from processing information
in self-relevant ways. Three studies have now shown a reduced
or absent self-reference effect in memory in autism (Toichi
et al., 2002; Lombardo et al., 2007; Henderson et al., 2009).
The current study extends this observation by showing a lack of
a ‘neural self-reference effect’ in the ventromedial prefrontal
The ventromedial prefrontal cortex result from the current study
differs from a previous study where no group differences in
Self4Other activity were found (Kennedy and Courchesne,
2008a). However, it is worth noting that the Kennedy and
Courchesne study may not have been sensitive enough to detect
a group difference primarily because the ‘other’ person was some-
one close to the participants (i.e. one’s mother). Prior research
(Schmitz et al., 2004; Seger et al., 2004; Ochsner et al., 2005;
Mitchell et al., 2006; Jenkins et al., 2008) demonstrates that
thinking aboutothers who
self-relevant information may reduce the power to elicit a neural
distinction between self and other in the ventromedial prefrontal
cortex. The current study uses a familiar but non-close other, and
the inclusion of this type of person as the ‘other’ condition
increases the reliability in consistently eliciting such an effect in
the general population.Thus
manipulation between self and other was designed to be an
obviously large difference, it is all the more intriguing that
such a manipulation does not elicit the Self4Other effect in the
ventromedial prefrontal cortex of individuals with autism.
Figure 4 Individual differences in ventromedial prefrontal cortex (vMPFC) self-other distinction and early childhood social symptom
severity. This figure displays (a) the vMPFC region (MNI x=2, y=44, z=?12) that is correlated with early childhood social symptom
severity (measured by the ADI-R). (b) The correlation for the contrasts of self-mentalizing compared with other-mentalizing (SM4OM;
red dots) and self-physical compared with other-physical (SP4OP; blue dots).
Atypical neural self-representation in autismBrain 2009: Page 9 of 14 |
However, the lack of a neural self-other distinction in the
ventromedial prefrontal cortex of autism does not mean that
individuals with autism do not recruit areas that code for such a
distinction. On the contrary, in areas of the brain where self
and other are distinguished via its preferential response to
other-information (i.e. Other4Self), both controls and autism
spectrum conditions activated these regions similarly. Thus, there
is specificity in the deficit for neurally distinguishing self from
other. In autism, these deficits only occur in areas that preferen-
tially respond to self-information. This specificity in the lack of
such a mechanism like ventromedial prefrontal cortex for prefer-
entially coding self-information confirms predictions made by the
absent-self theory and sheds new insight into the nature of the
autistic self. The neural deficit in self-representation may also be
crucial for explaining the simultaneous presence of both impaired
self-referential cognition and the self-other equivalence that
appears on the surface to be egocentrism.
While the ventromedial prefrontal cortex is key for distinguish-
ing self from other, it clearly does not work alone. We observed
within our control sample that the neural circuit functionally
connected with the ventromedial prefrontal cortex during high-
level conceptual self-processing (compared with other-processing)
was distributed across lower level sensorimotor regions (frontal
involved in embodied processes essential for sensation/perception
and action. These findings lend support for the broader idea that
building high-level conceptual self-representations relies on the
coordination of information from lower level embodied sensorimo-
tor systems (Barsalou, 1999; Aziz-Zadeh and Damasio, 2008).
In contrast, individuals with autism spectrum conditions do not
show any areas where ventromedial prefrontal cortex connectivity
isstronger during self-judgements
judgements. Thus, in addition to not distinguishing self from
other in the ventromedial prefrontal cortex, self-representation
deficits in autism extend across a crucial neural circuit that
coordinates conceptual self-processing with lower level embodied
To add to the mounting evidence for the critical role of
the ventromedial prefrontal cortex in neural self-representation
in autism, the current study demonstrates a tight link between
atypical neural self-representation and the social impairments in
autism. The magnitude of distinguishing self from other in the
ventromedial prefrontal cortex was related to the magnitude of
early childhood social impairments. Individuals with the greatest
social impairments in early childhood showed the least ventrome-
dial prefrontal cortex self-other mentalizing distinction, while the
least socially impaired individuals showed the largest ventromedial
prefrontal cortex self-other mentalizing distinction. Thus, the
marked deficits in neural self-representation are strongly linked
to the early social impairments in autism.
While specifying the directionality of such a relationship solely
on the basis of the current data may be difficult (i.e. does a
self-deficit lead to social deficits or vice versa?), it is worth stating
developmental considerations that may shed light on such a
relationship. First, Meltzoff has proposed that the starting state
for social cognition is one where infants take the stance that
others are ‘like me’ (Meltzoff, 2007; Meltzoff and Brooks,
2008). However, as development progresses, social cognitive
ability invariably develops past the simple acknowledgement of
self-other equivalence and into a simultaneous or ‘dual’ under-
standing that self can also be different from others. Much of
what is known of later developing social cognition is predicated
on this push and pull between similarities and differences between
self and other (Brewer, 1991; Banaji and Prentice, 1994;
Nickerson, 1999; Ames, 2004; Epley et al., 2004; Birch and
Bloom, 2007; Pronin, 2008). To illustrate, in theory of mind devel-
opment the ability to inhibit privileged self-knowledge facilitates
success on standard false belief tasks (Birch and Bloom, 2003).
Perhaps the most difficult developmental feat crucial for social
cognitive development beyond the ‘like me’ stage is the develop-
ment of understanding the ‘duality’ of self in mentalistic terms
(i.e. by ‘duality of self’ we mean a simultaneous understanding
that oneself is both similar to yet different from others). The
beginning of this transition to developing this dual understanding
of self starts around the end of the first year of life (9–14 months)
(Amsterdam, 1972; Scaife and Bruner, 1975) and continues well
on into the second year of life (Kagan, 1981). Strikingly, some of
the earliest signs of autism are behaviours indicative of this dual
understanding of self; namely, deficits in joint attention (Landa
et al., 2007) and a lack of responding to one’s own name
(Osterling and Dawson, 1994; Zwaigenbaum et al., 2005; Nadig
et al., 2007). Both early risk signs of autism also emerge around
the end of the first year (12–14 months).
Thus, while the data from the current study cannot by itself
distinguish between whether self-deficits cause social deficits or
vice versa, both the developmental time-course of self-other
equivalence (i.e. ‘like me’ stage) followed by a dual understanding
of self and evidence on the early development of autism suggests
that the current findings may be a developmental ‘fingerprint’ of
atypical neural organization laid down during a critical period of
development where such processes are beginning to take shape.
Such atypical early development of the ventromedial prefrontal
cortex may be a driving factor underlying the observed relation-
ship with early childhood social impairments in autism. Work
remains to be done on the typical development of regions such
as the ventromedial prefrontal cortex in self-referential and social
cognition, but initial studies in adolescence appear promising
(Pfeifer et al., 2007; Sebastian et al., 2008; Burnett et al., 2009).
Aside from discussing the cognitive and developmental signifi-
cance of atypical ventromedial prefrontal cortex function, it is
important to note the wealth of data supporting underlying struc-
tural, neurochemical and physiological anomalies in the ventrome-
dial prefrontal cortex. Localized medial prefrontal grey matter
enlargement in autism occurs in early childhood (Carper and
Courchesne, 2005) and may persist into early adolescence
(Waiter et al., 2004; Bonilha et al., 2008). Complementing this
grey matter enlargement, adjacent ventromedial prefrontal cortex
white matter density (Bonilha et al., 2008; McAlonan et al.,
2009), fractional anisotropy, and tract number are reduced
(Barnea-Goraly et al., 2004; Cheung et al., 2009; Pugliese
et al., 2009; Pardini et al., in press), which may ultimately
manifest as an information processing ‘bottleneck’. In terms of
the physiological and neurochemical composition of the ventrome-
dial prefrontal cortex, only one magnetic resonance spectroscopy
Brain 2009: Page 10 of 14M. V. Lombardo et al.
study has specifically explored this region and found decreases in
the concentration of metabolites (i.e. Cho) that may reflect altered
membrane metabolism (Levitt et al., 2003). Serotonin (Murphy
et al., 2006; Makkonen et al., 2008) and dopamine (Ernst
et al., 1997) receptor binding are also reduced in the medial
prefrontal cortex in autism. Positron emission tomography studies
have documented abnormalities in glucose metabolism that is
increased at rest (Rumsey et al., 1985; Horwitz et al., 1988)
and decreased during task performance (Haznedar et al., 2000;
Hazlett et al., 2004). Regional cerebral blood flow is also reduced
(George et al., 1992; Zilbovicius et al., 1995) and correlates with
social symptom severity (Ohnishi et al., 2000). Finally, recent
fMRI evidence suggests that resting ventromedial prefrontal
(Kennedy et al., 2006; Kennedy and Courchesne, 2008a) is also
reduced in a task-independent manner (i.e. irrespective of the
comparison cognitive task) and correlates with social symptom
severity. Resting state functional connectivity from the ventrome-
dial prefrontal cortex is also significantly reduced (Kennedy and
quantitative meta-analyses of task-related functional neuroimaging
studiesfinds consistent hypoactivation
prefrontal cortex in autism across the literature of social (but not
non-social) tasks (Di Martino et al., 2009). Taken together, these
observations highlight the paramount role of the ventromedial
prefrontal cortex in the neurodevelopment of autism. We
mechanism(s) are at work in the ventromedial prefrontal cortex
that derail the normative structural and functional development
of this region, hindering critical developmental transitions in
self-referential and social-cognitive development. For example,
a recently discovered genetic variant associated with autism near
the gene cadherin 10 (CDH10) is involved in neuronal cell adhe-
sion molecules and is specifically expressed in ventromedial
prefrontal cortex of the developing human foetal brain (Wang
et al., 2009).Futurework
autism-associated genetic variants are likely to illuminate core
neurodevelopmental insights into autism (Lombardo et al., 2010a).
In conclusion, we have observed disruptions in the neural sys-
tems critical for coding self-information in autism. The disruption
of such systems is integrally related to the early social impairments
in autism. The abundance of evidence highlighting atypical devel-
opment, structure, function, and physiology of the ventromedial
prefrontal cortex suggests that the current study highlights the
end result of an early pathophysiological biological mechanism in
this area. The expression of such a pathophysiological mechanism
may derail the normative development of the ventromedial
prefrontal cortex in a critical period where a dual understanding
of self is beginning to emerge. Future work on the ventromedial
prefrontal cortex will be crucial for elucidating core neural
mechanisms in the neurodevelopment of autism.
on these findings,recent
of the ventromedial
targetingthis region and
We thank Jason Mitchell and Adrianna Jenkins for generously let-
ting us use their stimuli, and Mike Cohen, Matthew Belmonte,
Caroline Robertson, Teresa Tavassoli, Meng-Chuan Lai and Ilaria
Minio-Paluello for their valuable discussion and comments, as well
as support from the MRC Autism Imaging Multi-Centre Study
(AIMS) Consortium. This work was conducted in association
with the NIHR CLAHRC for Cambridgeshire and Peterborough
NHS Mental Health Trust. E.T.B. is employed half-time by the
University of Cambridge and half-time by GlaxoSmithKline plc.
This work was funded by doctoral studentship/bursaries from the
Shirley Foundation (to M.V.L.); Cambridge Overseas Trust and
Medical Research Council (MRC) [to the AIMS Consortium and
to S.B.C.-(program grant)].
Supplementary material is available at Brain online.
Ames DR. Inside the mind reader’s tool kit: projection and stereotyping
in mental state inference. J Pers Soc Psychol 2004; 87: 340–53.
Amodio DM, Frith CD. Meeting of minds: the medial frontal cortex
and social cognition. Nat Rev Neurosci 2006; 7: 268–77.
Amsterdam B. Mirror self-image reactions before age two. Dev
Psychobiol 1972; 5: 297–305.
Asperger H. Die autistischen Psychopathen im Kindesalter. Archiv fur
Psychiatrie und Nervenkrankheiten 1944; 117: 76–136.
Avenanti A, Bolognini N, Maravita A, Aglioti SM. Somatic and
Avenanti A, Bueti D, Galati G, Aglioti SM. Transcranial magnetic
stimulation highlights the sensorimotor side of empathy for pain. Nat
Neurosci 2005; 8: 955–60.
Aziz-Zadeh L, Damasio A. Embodied semantics for actions: findings from
functional brain imaging. J Physiol Paris 2008; 102: 35–9.
Aziz-Zadeh L, Wilson SM, Rizzolatti G, Iacoboni M. Congruent embodied
representations for visually presented actions and linguistic phrases
describing actions. Curr Biol 2006; 16: 1818–23.
Bagby RM, Parker JD, Taylor GJ. The twenty-item Toronto Alexithymia
Scale-I. Item selection and cross-validation of the factor structure.
J Psychosom Res 1994; 38: 23–32.
Banaji MR, Prentice DA. The self in social contexts. Annu Rev Psychol
1994; 45: 297–332.
Barnea-Goraly N, Kwon H, Menon V, Eliez S, Lotspeich L, Reiss AL.
White matter structure in autism: preliminary evidence from diffusion
tensor imaging. Biol Psychiatry 2004; 55: 323–6.
Baron-Cohen S. Are autistic children "behaviorists"? An examination of
their mental-physical and appearance-reality distinctions. J Autism Dev
Disord 1989; 19: 579–600.
Baron-Cohen S. Autism – ’autos’: Literally, a total focus on the self? In:
Feinberg TE, Keenan JP, editors. The lost self: pathologies of the brain
and identity. Oxford: Oxford University Press; 2005.
Baron-Cohen S, Wheelwright S, Skinner R, Martin J, Clubley E.
syndrome/high-functioning autism, males and females, scientists and
mathematicians. J Autism Dev Disord 2001; 31: 5–17.
Barsalou LW. Perceptual symbol systems. Behav Brain Sci 1999; 22:
(AQ): evidence fromAsperger
Atypical neural self-representation in autismBrain 2009: Page 11 of 14 |
Beer JS, John OP, Scabini D, Knight RT. Orbitofrontal cortex and social
behavior: integrating self-monitoring and emotion-cognition interac-
tions. J Cogn Neurosci 2006; 18: 871–9.
Belmonte MK, Allen G, Beckel-Mitchener A, Boulanger LM, Carper RA,
Webb SJ. Autism and abnormal development of brain connectivity.
J Neurosci 2004; 24: 9228–31.
Birch SA, Bloom P. Children are cursed: an asymmetric bias in mental-
state attribution. Psychol Sci 2003; 14: 283–6.
Birch SA, Bloom P. The curse of knowledge in reasoning about false
beliefs. Psychol Sci 2007; 18: 382–6.
Blakemore SJ, Bristow D, Bird G, Frith C, Ward J. Somatosensory activa-
tions during the observation of touch and a case of vision-touch
synaesthesia. Brain 2005; 128: 1571–83.
Bonilha L, Cendes F, Rorden C, Eckert M, Dalgalarrondo P, Li LM, et al.
Gray and white matter imbalance-typical structural abnormality
underlying classic autism? Brain Dev 2008; 30: 396–401.
Brewer MB. The social self: on being the same and different at the same
time. Pers Soc Psychol Bull 1991; 17: 475–82.
Burnett S, Bird G, Moll J, Frith C, Blakemore SJ. Development during
adolescence of the neural processing of social emotion. J Cogn
Neurosci 2009; 21: 1736–50.
Carper RA, Courchesne E. Localized enlargement of the frontal cortex in
early autism. Biol Psychiatry 2005; 57: 126–33.
Cattaneo L, Fabbri-Destro M, Boria S, Pieraccini C, Monti A, Cossu G,
et al. Impairment of actions chains in autism and its possible role in
intention understanding. Proc Natl Acad Sci USA 2007; 104:
Cheung C, Chua SE, Cheung V, Khong PL, Tai KS, Wong TK, et al.
White matter fractional anisotrophy differences and correlates of
diagnostic symptoms in autism. J Child Psychol Psychiatry 2009; 50:
Chiu PH, Kayali MA, Kishida KT, Tomlin D, Klinger LG, Klinger MR,
et al. Self responses along cingulate cortex reveal quantitative neural
phenotype for high-functioning autism. Neuron 2008; 57: 463–73.
Craik FIM, Moroz TM, Moscovitch M, Stuss DT, Winocur G, Tulving E,
et al. In search of the self: a positron emission tomography study.
Psychol Sci 1999; 10: 26–34.
Crane L, Goddard L. Episodic and semantic autobiographical memory in
adults with autism spectrum disorders. J Autism Dev Disord 2008; 38:
D’Argembeau A, Ruby P, Collette F, Degueldre C, Balteau E, Luxen A,
et al. Distinct regions of the medial prefrontal cortex are associated
with self-referential processing and perspective taking. J Cogn
Neurosci 2007; 19: 935–44.
DaprettoM, DaviesMS, Pfeifer
Bookheimer SY, et al. Understanding emotions in others: mirror
neuron dysfunction in children with autism spectrum disorders. Nat
Neurosci 2006; 9: 28–30.
David N, Bewernick BH, Cohen MX, Newen A, Lux S, Fink GR, et al.
Neural representations of self versus other: visual-spatial perspective
taking and agency in a virtual ball-tossing game. J Cogn Neurosci
2006; 18: 898–910.
Di , Martino A, Ross K, Uddin LQ, Sklar AB, Castellanos FX, Milham MP.
Functional brain correlates of social and nonsocial processes in autism
spectrum disorders: an activation likelihood estimation meta-analysis.
Biol Psychiatry 2009; 65: 63–74.
Eickhoff SB, Stephan KE, Mohlberg H, Grefkes C, Fink GR, Amunts K,
et al. A new SPM toolbox for combining probabilistic cytoarchitectonic
maps and functional imaging data. Neuroimage 2005; 25: 1325–35.
Epley N, Keysar B, Van Boven L, Gilovich T. Perspective taking as
egocentric anchoring and adjustment. J Pers Soc Psychol 2004; 87:
Ernst M, Zametkin AJ, Matochik JA, Pascualvaca D, Cohen RM. Low
medial prefrontal dopaminergic activity in autistic children. Lancet
1997; 350: 638.
Ersner-Hershfield H, Wimmer GE, Knutson B. Saving for the future self:
neural measures of future self-continuity predict temporal discounting.
Soc Cogn Affect Neurosci 2009; 4: 85–92.
JH,ScottAA, Sigman M,
Psychophysiological and modulatory interactions in neuroimaging.
Neuroimage 1997; 6: 218–29.
Frith CD, Frith U. The self and its reputation in autism. Neuron 2008; 57:
Frith U. Autism: explaining the enigma. 2nd edn. Malden, MA:
Frith U, de Vignemont F. Egocentrism, allocentrism, and Asperger
syndrome. Conscious Cogn 2005; 14: 719–38.
Frith U, Happe F. Theory of mind and self-consciousness: what it is like
to be autistic. Mind and Language 1999; 14: 1–22.
Gazzola V, Keysers C. The observation and execution of actions
share motor and somatosensory voxels in all tested subjects: single-
subject analyses of unsmoothed fMRI data. Cereb Cortex 2009; 19:
George MS, Costa DC, Kouris K, Ring HA, Ell PJ. Cerebral blood flow
abnormalities in adults with infantile autism. J Nerv Ment Dis 1992;
Goldman AI. Simulating minds: The philosophy, psychology, and
neuroscience of mind reading. New York: Oxford University Press;
Gutchess AG, Kensinger EA, Schacter DL. Aging, self-reference, and
medial prefrontal cortex. Soc Neurosci 2007; 2: 117–33.
Hampton AN, Bossaerts P, O’Doherty JP. Neural correlates of mentaliz-
ing-related computations during strategic interactions in humans. Proc
Natl Acad Sci USA 2008; 105: 6741–6.
Happe F. Theory of mind and the self. Ann NY Acad Sci 2003; 1001:
Haswell CC,IzawaJ, Dowell
Representation of internal models of action in the autistic brain. Nat
Neurosci 2009; 12: 970–2.
Hazlett EA, Buchsbaum MS, Hsieh P, Haznedar MM, Platholi J,
LiCalzi EM, et al. Regional glucose metabolism within cortical
Brodmann areasin healthy individuals
Neuropsychobiology 2004; 49: 115–25.
Haznedar MM, Buchsbaum MS, Wei TC, Hof PR, Cartwright C,
Bienstock CA, et al. Limbic circuitry in patients with autism spectrum
disorders studied with positron emission tomography and magnetic
resonance imaging. Am J Psychiatry 2000; 157: 1994–2001.
Heerey EA, Keltner D, Capps LM. Making sense of self-conscious
emotion: linking theory of mind and emotion in children with
autism. Emotion 2003; 3: 394–400.
Henderson HA, Zahka NE, Kojkowski NM, Inge AP, Schwartz CB,
Hileman CM, et al. Self-referenced memory, social cognition, and
symptom presentation in autism. J Child Psychol Psychiatry 2009; 50:
Hill E, Berthoz S, Frith U. Brief report: cognitive processing of own
emotions in individuals with autistic spectrum disorder and in their
relatives. J Autism Dev Disord 2004; 34: 229–35.
Hobson PR, Chidambi G, Lee A, Meyer J. Foundations for self-
awareness: an exploration through autism. Monogr Soc Res Child
Dev 2006; 71: vii–166.
Hobson RP, Meyer JA. Foundations for self and other: a study in autism.
Dev Sci 2005; 8: 481–91.
Horwitz B, Rumsey JM, Grady CL, Rapoport SI. The cerebral metabolic
landscape in autism. Intercorrelations of regional glucose utilization.
Arch Neurol 1988; 45: 749–55.
experience in three adults with Asperger syndrome. Psychol Med
1994; 24: 385–95.
Iacoboni M. Failure to deactivate in autism: the co-constitution of self
and other. Trends Cogn Sci 2006; 10: 431–3.
Iacoboni M, Dapretto M. The mirror neuron system and the conse-
quences of its dysfunction. Nat Rev Neurosci 2006; 7: 942–51.
ICD-10. Internation Classification of Diseases. Geneva, Switzerland:
World Heath Organization; 1994.
Izuma K, Saito DN, Sadato N. Processing of social and monetary rewards
in the human striatum. Neuron 2008; 58: 284–94.
KJ, BuchelC, Fink GR,MorrisJ, Rolls E, DolanRJ.
R, MostofskyS, ShadmehrR.
Samplingthe form ofinner
Brain 2009: Page 12 of 14M. V. Lombardo et al.
Jackson PL, Brunet E, Meltzoff AN, Decety J. Empathy examined through
the neural mechanisms involved in imagining how I feel versus how
you feel pain. Neuropsychologia 2006; 44: 752–61.
Jenkins AC, Macrae CN, Mitchell JP. Repetition suppression of ventro-
medial prefrontal activity during judgments of self and others. Proc
Natl Acad Sci USA 2008; 105: 4507–12.
Jordan RR. An experimental comparison of the understanding and use of
speaker addresse personal pronouns in autistic children. Br J Disord
Commun 1989; 24: 169–79.
Just MA, Cherkassky VL, Keller TA, Minshew NJ. Cortical activation
and synchronizationduring sentence
functioning autism: evidence of underconnectivity. Brain 2004; 127:
Kagan J. The second year: the emergence of self-awareness. Cambridge,
MA: Harvard University Press; 1981.
Kanner L. Autistic disturbance of affective contact. Nerv Child 1943; 2:
Kasari C, Sigman MD, Baumgartner P, Stipek DJ. Pride and mastery in
children with autism. J Child Psychol Psychiatry 1993; 34: 353–62.
Kelley WM, Macrae CN, Wyland CL, Caglar S, Inati S, Heatherton TF.
Finding the self? An event-related fMRI study. J Cogn Neurosci 2002;
Kennedy DP, Courchesne E. Functional abnormalities of the default
network during self- and other-reflection in autism. Soc Cogn Affect
Neurosci 2008a; 3: 177–90.
Kennedy DP, Courchesne E. The intrinsic functional organization of the
brain is altered in autism. Neuroimage 2008b; 39: 1877–85.
Kennedy DP, Redcay E, Courchesne E. Failing to deactivate: resting
functional abnormalities in autism. Proc Natl Acad Sci USA 2006;
Keysers C, Wicker B, Gazzola V, Anton JL, Fogassi L, Gallese V.
A touching sight: SII/PV activation during the observation and experi-
ence of touch. Neuron 2004; 42: 335–46.
King-Casas B, Tomlin D, Anen C, Camerer CF, Quartz SR, Montague PR.
Getting to know you: Reputation and trust in a two-person economic
exchange. Science 2006; 308: 78–83.
Klein SB, Chan RL, Loftus J. Independence of episodic and semantic self
knowledge: the case of autism. Soc Cogn 1999; 17: 413–36.
Lamm C, Batson CD, Decety J. The neural substrate of human empathy:
effects of perspective-taking and cognitive appraisal. J Cogn Neurosci
2007; 19: 42–58.
Lamm C, Meltzoff AN, Decety J. How do we empathize with someone
who is not like us? A functional magnetic resonance imaging study.
J Cogn Neurosciin press.
Landa RJ, Holman KC, Garrett-Mayer E. Social and communication
development in toddlers with early and later diagnosis of autism
spectrum disorders. Arch Gen Psychiatry 2007; 64: 853–64.
Lee A, Hobson PR. Drawing self and others: How do children with
autism differ from those with learning difficulties. Br J Dev Psychol
2006; 24: 547–65.
Lee A, Hobson RP. On developing self-concepts: a controlled study of
children and adolescents with autism. J Child Psychol Psychiatry 1998;
Lee A, Hobson RP, Chiat S. I, you, me, and autism: an experimental
study. J Autism Dev Disord 1994; 24: 155–76.
Leslie AM, Thaiss L. Domain specificity in conceptual development:
Levitt JG, O’Neill J, Blanton RE, Smalley S, Fadale D, McCracken JT,
et al. Proton magnetic resonance spectroscopic imaging of the brain
in childhood autism. Biol Psychiatry 2003; 54: 1355–66.
Lombardo MV, Barnes JL, Wheelwright SJ, Baron-Cohen S. Self-
referential cognition and empathy in autism. PLoS One 2007; 2:
Lombardo MV, Baron-Cohen S, Belmonte MK, Chakrabarti B. Neural
endophenotypes for social behaviour in autism spectrum conditions.
In: Decety J, Cacioppo J, editors. Handbook of social neuroscience.
Oxford: Oxford University Press; 2010a.
Lombardo MV, Chakrabarti B, Bullmore ET, Wheelwright SJ, Sadek SA,
Suckling J, Baron-Cohen S. MRC AIMS Consortium.Shared neural cir-
cuits for mentalizing about the self and others. J Cogn Neurosci
Lord C, Risi S, Lambrecht L, Cook EH Jr, Leventhal BL, DiLavore PC,
et al. The autism diagnostic observation schedule-generic: a standard
measure of social and communication deficits associated with the
spectrum of autism. J Autism Dev Disord 2000; 30: 205–23.
Lord C, Rutter M, Le Couteur A. Autism Diagnostic Interview-Revised: a
revised version of a diagnostic interview for caregivers of individuals
with possible pervasive developmental disorders. J Autism Dev Disord
1994; 24: 659–85.
Loveland KA, Landry SH. Joint attention and language in autism and
developmental language delay. J Autism Dev Disord 1986; 16:
Makkonen I, Riikonen R, Kokki H, Airaksinen MM, Kuikka JT. Serotonin
and dopamine transporter binding in children with autism determined
by SPECT. Dev Med Child Neurol 2008; 50: 593–7.
McAlonan GM, Cheung C, Cheung V, Wong N, Suckling J, Chua SE.
Differential effects on white-matter systems in high-functioning autism
and Asperger’s syndrome. Psychol Med 2009; 39: 1885–93.
Meltzoff AN. ’Like me’: a foundation for social cognition. Dev Sci 2007;
Meltzoff AN, Brooks R. Self-experience as a mechanism for learning
about others: a training study in social cognition. Dev Psychol 2008;
Minio-Paluello I, Baron-Cohen S, Avenanti A, Walsh V, Aglioti SM.
Absence of embodied empathy during pain observation in Asperger
syndrome. Biol Psychiatry 2009; 65: 55–62.
Minshew NJ, Williams DL. The new neurobiology of autism: cortex,
connectivity, and neuronal organization. Arch Neurol 2007; 64:
Mitchell JP, Macrae CN, Banaji MR. Dissociable medial prefrontal
contributions to judgments of similar and dissimilar others. Neuron
2006; 50: 655–63.
Mitchell P, O’Keefe K. Brief report: do individuals with autism spectrum
disorder think they know their own minds? J Autism Dev Disord 2008;
Mobbs D, Yu R, Meyer M, Passamonti L, Seymour B, Calder AJ,
et al. A key role for similarity in vicarious reward. Science 2009;
Moran JM, Heatherton TF, Kelley WM. Modulation of cortical midline
structures by implicit and explicit self-relevance evaluation. Soc
Neurosci 2009; 4: 197–211.
Moran JM, Macrae CN, Heatherton TF, Wyland CL, Kelley WM.
components of self. J Cogn Neurosci 2006; 18: 1586–94.
Murphy DG, Daly E, Schmitz N, Toal F, Murphy K, Curran S, et al.
Cortical serotonin 5-HT2A receptor binding and social communication
in adults with Asperger’s syndrome: an in vivo SPECT study. Am J
Psychiatry 2006; 163: 934–6.
Nadig AS, Ozonoff S, Young GS, Rozga A, Sigman M, Rogers SJ.
A prospective study of response to name in infants at risk for
autism. Arch Pediatr Adolesc Med 2007; 161: 378–83.
Nickerson RS. How we know – and sometimes misjudge – what others
know: imputing one’s own knowledge to others. Psychol Bull 1999;
Ochsner KN, Beer JS, Robertson ER, Cooper JC, Gabrieli JD, Kihsltrom JF,
et al. The neural correlates of direct and reflected self-knowledge.
Neuroimage 2005; 28: 797–814.
Ohnishi T, Matsuda H, Hashimoto T, Kunihiro T, Nishikawa M, Uema T,
et al. Abnormal regional cerebral blood flow in childhood autism. Brain
2000; 123: 1838–44.
Osterling J, Dawson G. Early recognition of children with autism: a study
of first birthday home videotapes. J Autism Dev Disord 1994; 24:
Pardini M, Garaci FG, Bonzano L, Roccatagliata L, Palmieri MG,
Pompili E, et al. White matter reduced streamline coherence in
distinct cognitive andaffective
Atypical neural self-representation in autismBrain 2009: Page 13 of 14 |
young men with autism and mental retardation. Eur J Neurol 2009; Download full-text
Perner J, Frith U, Leslie AM, Leekam SR. Exploration of the autistic
child’s theory of mind: knowledge, belief, and communication. Child
Dev 1989; 60: 688–700.
Pfeifer JH, Lieberman MD, Dapretto M. ‘‘I know you are but what
am I?’’: neural bases of self- and social knowledge retrieval in children
and adults. J Cogn Neurosci 2007; 19: 1323–37.
Phillips W, Baron-Cohen S, Rutter M. Understanding intention in
normal development and in autism. Br J Dev Psychol 1998; 16:
Pronin E. How we see ourselves and how we see others. Science 2008;
Pugliese L, Catani M, Ameis S, Dell’acqua F, de Schotten MT, Murphy C,
et al. The anatomy of extended limbic pathways in Asperger
syndrome: a preliminary diffusion tensor imaging tractography study.
Neuroimage 2009; 47: 427–34.
Rumsey JM, Duara R, Grady C, Rapoport JL, Margolin RA, Rapoport SI,
et al. Brain metabolism in autism. Resting cerebral glucose utilization
rates as measured with positron emission tomography. Arch Gen
Psychiatry 1985; 42: 448–55.
Saxe R, Moran JM, Scholz J, Gabrieli J. Overlapping and non-overlapping
brain regions for theory of mind and self reflection in individual
subjects. Soc Cogn Affect Neurosci 2006; 1: 229–34.
Scaife M, Bruner JS. The capacity for joint visual attention in the infant.
Nature 1975; 253: 265–6.
Schmitz TW, Kawahara-Baccus TN, Johnson SC. Metacognitive evalua-
tion, self-relevance, and the right prefrontal cortex. Neuroimage 2004;
Sebastian C, Burnett S, Blakemore SJ. Development of the self-concept
during adolescence. Trends Cogn Sci 2008; 12: 441–6.
Seger CA, Stone M, Keenan JP. Cortical Activations during judgments
about the self and an other person. Neuropsychologia 2004; 42:
Silani G, Bird G, Brindley R, Singer T, Frith C, Frith U. Levels of
emotional awareness and autism: an fMRI study. Soc Neurosci 2008;
Singer T, Seymour B, O’Doherty J, Kaube H, Dolan RJ, Frith CD.
Empathy for pain involves the affective but not sensory components
of pain. Science 2004; 303: 1157–62.
Steiger JH. Tests for comparing elements of a correlation matrix. Psychol
Bull 1980; 87: 245–51.
Toichi M, Kamio Y, Okada T, Sakihama M, Youngstrom EA, Findling RL,
et al. A lack of self-consciousness in autism. Am J Psychiatry 2002;
Tomlin D, Kayali MA, King-Casas B, Anen C, Camerer CF, Quartz SR,
et al. Agent-specific responses in the cingulate cortex during economic
exchanges. Science 2006; 312: 1047–50.
Uddin LQ, Iacoboni M, Lange C, Keenan JP. The self and social
cognition: the role of cortical midline structures and mirror neurons.
Trends Cogn Sci 2007; 11: 153–7.
Vargas DL, Nascimbene C, Krishnan C, Zimmerman AW, Pardo CA.
Neuroglial activation and neuroinflammation in the brain of patients
with autism. Ann Neurol 2005; 57: 67–81.
Vogeley K, May M, Ritzl A, Falkai P, Zilles K, Fink GR. Neural correlates
of first-person perspective as one constituent of human self-
consciousness. J Cogn Neurosci 2004; 16: 817–27.
Waiter GD, Williams JH, Murray AD, Gilchrist A, Perrett DI, Whiten A. A
voxel-based investigation of brain structure in male adolescents with
autistic spectrum disorder. Neuroimage 2004; 22: 619–25.
Wang K, Zhang H, Ma D, Bucan M, Glessner JT, Abrahams BS, et al.
Common genetic variants on 5p14.1 associate with autism spectrum
disorders. Nature 2009; 459: 528–33.
Weschler D. Wechsler abbreviated scale of intelligence. San Antonio, TX:
The Psychological Corporation; 1999.
Wicker B, Keysers C, Plailly J, Royet JP, Gallese V, Rizzolatti G. Both of
us disgusted in My insula: the common neural basis of seeing and
feeling disgust. Neuron 2003; 40: 655–64.
Williams D, Happe F. Representing intentions in self and other: studies of
autism and typical development. Dev Sci; in press.
Williams DM, Happe F. What did I say? Versus what did I think?
Attributing false beliefs to self amongst children with and without
autism. J Autism Dev Disord 2009; 39: 865–73.
Williams JH. Self-other relations in social development and autism: multi-
ple roles for mirror neurons and other brain bases. Autism Res 2008; 1:
Woodbury-Smith MR, Robinson J, Wheelwright S, Baron-Cohen S.
Screening adults for Asperger Syndrome using the AQ: a preliminary
study of its diagnostic validity in clinical practice. J Autism Dev Disord
2005; 35: 331–5.
Zaki J, Weber J, Bolger N, Ochsner K. The neural bases of empathic
accuracy. Proc Natl Acad Sci USA 2009; 106: 11382–7.
Zilbovicius M, Garreau B, Samson Y, Remy P, Barthelemy C, Syrota A,
et al. Delayed maturation of the frontal cortex in childhood autism.
Am J Psychiatry 1995; 152: 248–52.
Zwaigenbaum L, Bryson S, Rogers T, Roberts W, Brian J, Szatmari P.
Behavioral manifestations of autism in the first year of life. Int J Dev
Neurosci 2005; 23: 143–52.
The MRC AIMS Consortium is a UK collaboration between the
Institute of Psychiatry at Kings College, London, the Autism
Research Centre and Brain Mapping Unit at the University of
Cambridge, and the Autism Research Group at the University of
Oxford. It is funded by the Medical Research Council (MRC) UK
and headed by the Section of Brain Maturation, Institute of
Psychiatry. The Consortium members are in alphabetical order:
A. J. Bailey, S. Baron-Cohen, P. F. Bolton, E. T. Bullmore,
S. Carrington, B. Chakrabarti, E. M. Daly, S. C. Deoni, C. Ecker,
F. Happe ´, J. Henty, P. Jezzard, P. Johnston, D. K. Jones,
M.V. Lombardo,A. Madden,
D. G. Murphy, G. Pasco, S. Sadek, D. Spain, R. Stewart,
J. Suckling, S. Wheelwright and S. C. Williams.
D. Mullins,C. Murphy,
Brain 2009: Page 14 of 14M. V. Lombardo et al.