Neurons in the fusiform gyrus are fewer
and smaller in autism
Imke A. J. van Kooten,1,2,3Saskia J. M.C. Palmen,3Patricia von Cappeln,4Harry W. M. Steinbusch,1,2
Hubert Korr,4Helmut Heinsen,5Patrick R. Hof,6Herman van Engeland3and Christoph Schmitz1,2
1Department of Psychiatry and Neuropsychology, Maastricht University,2European Graduate School of Neuroscience
(EURON), Maastricht,3Rudolph Magnus Institute of Neuroscience, Department of Child and Adolescent Psychiatry,
University Medical Center Utrecht,The Netherlands,4Department of Anatomy and Cell Biology, RWTH Aachen University,
Aachen,5Morphological Brain Research Unit,University of Wuerzburg,Wuerzburg,Germany and6Department of
Neuroscience, Mount Sinai School of Medicine, NewY ork, NY,USA
Correspondence to: Dr Christoph Schmitz, Department of Psychiatry and Neuropsychology, Division of Cellular
Neuroscience, Maastricht University, P.O. Box 616, 6200 MD Maastricht,The Netherlands
Abnormalities in face perception are a core feature of social disabilities in autism. Recent functional magnetic
resonance imaging studies showed that patients with autism could perform face perception tasks.However, the
fusiform gyrus (FG) and other cortical regions supporting face processing in controls are hypoactive in patients
with autism.The neurobiological basis of this phenomenon is unknown.Here, we tested the hypothesis that the
FG shows neuropathological alterations in autism, namely alterations in neuron density, total neuron number
and mean perikaryal volume.We investigated the FG (analysing separately layers II, III, IV ,V and VI), in seven
post-mortem brains from patients with autism and 10 controls for volume, neuron density, total neuron
number and mean perikaryal volume with high-precision design-based stereology.T o determine whether these
results were specific for the FG, the same analyses were also performed in the primary visual cortex and in the
cortical grey matter as a whole. Compared to controls, patients with autism showed significant reductions in
neuron densitiesinlayer III, totalneuron numbersin layers III,Vand VI, andmean perikaryalvolumes ofneurons
in layers Vand VI in the FG. None of these alterations were found in the primary visual cortex or in the whole
cerebral cortex. Although based on a relatively small sample of post-mortem brains from patients with autism
and controls, the results of the present study may provide important insight about the cellular basis of abnorm-
alities in face perception in autism.
Keywords: fusiform gyrus; design-based stereology; autism
Abbreviations: AMG=amygdala; CGM=cortical grey matter; FFA=fusiform face area; FG=fusiform gyrus;
fMRI=functional magnetic resonance imaging; IFG=inferior frontal gyrus; IOG=inferior occipital gyrus;
KS=Kolmogorov^Smirnov; OFC=orbitofrontal cortex; STG=superior temporal gyrus
Received September17 , 2007 . Revised February 7 , 2008. Accepted February13, 2008. Advance Access publication March10, 2008
Autism is a neurodevelopmental disorder with an estimated
heritability of 490% (DiCicco-Bloom et al., 2006). It is
defined by the presence of social deficits, language
abnormalities and stereotyped and repetitive behaviours
thought to be specific to autism (Bodfish et al., 2000). A
key feature of normal social functioning in humans is the
processing of faces, which allows people to identify
individuals and enables them with the capacity to under-
stand the mental state of others (Baron-Cohen et al., 1994).
Although not included in the current diagnostic criteria,
patients with autism have marked deficits in face processing
(Grelotti et al., 2002). As such, alterations of this crucial
skill for social interaction may represent a central feature of
social disabilities in autism (Schultz et al., 2000). Imaging
studies have provided evidence for a role of temporal lobe
structures in face processing. It is well recognized from
functional magnetic resonance imaging (fMRI) studies that
the fusiform gyrus (FG) is consistently active when normal
humans view faces (Kanwisher et al., 1999). Patients with
autism can perform face perception tasks (Schultz, 2005)
? The Author (2008).Publishedby Oxford University Pressonbehalfofthe Guarantorsof Brain. Allrightsreserved.For Permissions, please email: email@example.com
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but there is strong evidence that the FG, as well as other
cortical regions supporting face processing in controls, is
hypoactive in patients with autism (Kanwisher et al., 1999;
Pierce et al., 2001, 2004; Bolte et al., 2006). However, the
unknown (Palmen et al., 2004a; Van Kooten et al., 2005;
DiCicco-Bloom et al., 2006)
It has been proposed that the failure to make direct eye
contact may explain the observed hypoactivation of the FG
in face perception tasks in autism (Dalton et al., 2005).
Imaging studies have reported unchanged (Pierce et al.,
2001) or increased (Waiter et al., 2004) volumes of the FG
in patients with autism compared to controls, or asym-
metry abnormalities of the FG in autism (i.e. larger on the
left side in patients with autism) (Herbert et al., 2002). It
has also been suggested that an innate impairment of
specialized neural systems may explain the reported
functional abnormalities of the FG in autism (Sasson,
2006). Based on this evidence, we hypothesized that the FG
would show neuropathological alterations at the cellular
level, i.e. in neuron density, total neuron number and mean
perikaryal volume in autism compared to controls. We
tested this hypothesis by investigating these parameters in
the FG of seven post-mortem brains from patients with
autism and 10 matched controls using high-precision
design-based stereology. To determine whether these results
were specific for the FG in autism, we performed the same
analyses on the primary visual cortex and the whole cortical
grey matter (CGM) as well. It should be mentioned that a
subset of the post-mortem brains investigated here (i.e. six
brains from patients with autism and six from controls)
were recently also investigated for possible alterations in the
modular organization of cellular microdomains (minicol-
umns) in the pre-frontal cortex (area 9), primary motor
cortex (area 4), primary sensory cortex (area S1) and
primary visual cortex (area 17) (Casanova et al., 2006).
Materials and Methods
Post-mortem brains (one hemisphere per case) from seven
patients with autism (four males, three females; mean age
12.1?2.8 years; mean?SEM) and 10 matched controls (eight
males, two females; mean age 30.1?7.5 years) were analysed.
Clinical data and the origin of the brains are shown in Tables 1
and S1 (in Supplementary data). The patients with autism did not
differ from the controls with respect to mean age [two-tailed
Student’s t-test; t(15)=1.917 (15 degrees of freedom)], P=0.07),
mean brain weight [t(15)=0.3913, P=0.70], mean interval between
death and autopsy [t(15)=0.0423, P=0.97] and mean fixation time
(American Psychiatric Association, 1994) and Autism Diagnostic
Interview (Lord et al., 1994) criteria of autism, and none of them
exhibited any chromosomal abnormalities. In all of the cases,
autopsy was performed after informed consent had been obtained
from a relative. The use of these autopsy cases for scientific
investigations was approved by the relevant Institutional Review
Boards. Except for the tissue provided by the Morphologic Brain
Research Unit, University of Wuerzburg, Wuerzburg, Germany
(UWMBRU), allocation of tissue was officially approved by the
Tissue Advisory Board (TAB) of the US-Autism Tissue Program
(ATP). Clinical records were available for all cases.
In all cases, the brains were divided mediosagittally. Either the left
or the right hemisphere was available for each case (Table 1). After
immersion-fixation in 10% formalin for at least 3 months, the
selected hemispheres were embedded in celloidin and cut into
complete series of 200mm thick coronal sections as previously
T able1 Clinical characteristics of all cases included in this study
NoAge (years)SHPMI (h)BW (g)Fix (days)Th (mm)Cause of death
Seizure prior to drowning
Obstructive pulmonary disease
Atherosclerotic heart disease
Atherosclerotic cardiovascular disease
A=patient with autism; C=control; S=sex; M=male; F=female; H=hemisphere; l=left; r=right; PMI=post-mortem interval
(time between death and autopsy); BW=brain weight; Fix=fixation time;Th=section thickness.
988Brain (2008),131,987^999 I. A. J. van Kooten et al.
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described (Heinsen et al., 2000) (all steps were performed at the
New York State Institute for Basic Research in Developmental
Disabilities, Staten Island, NY, USA). Every third section was
shipped to UWMBRU. The hemispheres provided by UWMBRU
were cut at a thickness of 500mm, and every other section was
selected (these differences did not influence the outcome of the
study). All selected sections were stained at UWMBRU with
gallocyanin, mounted and coverslipped as previously described
(Heinsen and Heinsen, 1991).
The FG, the primary visual cortex (Brodmann’s area 17)
(Brodmann, 1909) and the CGM were identified on all sections
showing these regions, according to anatomical landmarks and
cytoarchitectonic criteria (Figs 1 and 2). The fusiform face area
(FFA) within the FG could not be identified separately because
neither gross anatomical landmarks nor cytoarchitectonic criteria
have been established in the literature to identify the FFA within
the FG in human post-mortem brains. However, potential
cytoarchitectonic differences in volumes of cell layers, neuron
densities, total neuron numbers and mean perikaryal volumes
between patients with autism and controls can be assessed by
measuring these variables within the FG that encompasses the
possible range of the FFA within a comparable part of the FG in
each brain section showing the FG. The FG is located in the
temporal lobe, lateral to the parahippocampal gyrus. Its medial
boundary was defined by the collateral sulcus and its lateral
boundary by the temporo-occipital sulcus, which runs anterior to
posterior from the temporal pole to the occipital gyrus. The
superior boundary was characterized by a straight line between the
cortical ribbon and the apex of each sulcus (McDonald et al.,
2000; Pierce et al., 2001; see also Mai et al. at: http://
braininfo.rprc.washington.edu/) (Fig. 2). Area 17 is located in
the occipital lobe along the walls of the calcarine sulcus and
adjacent portions of the cuneus and lingual gyrus (Carpenter,
1985). It is defined histologically by a broad layer IV divided into
three sub-layers and numerous very small pyramidal cells in layers
II and III. The abrupt disappearance of the stripe of Gennari
allows for the precise delineation of the borders of area 17 (Braak,
1980). The CGM is characterized by its layered structure well
visible with classical cellular stains, such as gallocyanin or cresyl
violet (Fig. 1) (Paxinos, 2004). The boundaries of the FG and area
17 were identified using an Olympus SZX9 stereomicroscope
(Olympus; Tokyo, Japan) and were marked on the backside of the
glass slides with a felt-tip pen. Identification and delineation of
boundaries was performed in a blind manner by I.A.J.v.K. (FG),
S.J.M.C.P. (CGM) and P.v.C. (area 17) until all regions per
hemisphere were analysed, and were independently cross-evaluated
(and, if necessary, slightly modified) by C.S., H.H. and P.R.H.
Stereological analyses were performed with a computerized
stereology workstation, consisting of a modified light microscope
(Olympus BX50 with PlanApo objective 1.25?[numerical aperture
(N.A.)=0.04] and UPlanApo objective 20?[(oil; N.A.=0.8);
Olympus], motorized specimen stage for automatic sampling
(Ludl Electronics; Hawthorne, NY, USA), CCD colour video
camera (HV-C20AMP; Hitachi, Tokyo, Japan) and stereology
software (StereoInvestigator; MBF Bioscience, Williston, VT, USA).
Volumes of brain regions were analysed using the Cavalieri’s
principle (Cavalieri, 1966; Schmitz and Hof, 2005), by determin-
ing the projection area of a given brain region on each selected
section showing this region, summing up the data from all sec-
tions and multiplying this value with the interval of selecting
sections for staining with gallocyanin (2 or 3; see above) and the
average actual section thickness after tissue processing [determined
with the stereology workstation (in case of the 200mm thick
sections) or a calibrated fine adjustment knob of an Olympus BH
Fig.1 Representative photomicrographs of 200mm thick coronal
sections of the brain hemispheres from a control patient (A,C,
E) and a patient with autism (B, D, F), showing either the entire
hemisphere (A, B) or area17 (C, D) and the fusiform gyrus (FG)
(E, F). Scale bar=15mm in A and B, and 400 mm in C to F.
Neuron numbers in autism Brain (2008),131,987^999 989
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Fig. 2 Representative photomicrographs of 200mm thick coronal sections throughout the fusiform gyrus (FG) in the post-mortem
brain from a patient with autism, showing the delineation procedure of the entire FG (B to K).The next sections in the series rostral
to the FG (A) and caudal to the FG (L) are also shown.The arrow in E indicates the collateral sulcus and the arrowhead the temporo-
occipital sulcus.Note the tangential cutof the FGin B (arrow) indicating the rostral pole of the FG compared to the centre of the FG (H)
in which the cortical grey matter was found to be much thinner (arrow in H). Scale bar=15mm.
990Brain (2008),131,987^999 I. A. J. van Kooten et al.
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microscope and a PlanApo objective (40?; N.A.=1.0) as
described (Heinsen et al., 1994) (in the case of the 500mm thick
sections)]. The projection areas of the entire hemisphere and the
CGM were determined with point counting (Gundersen and
Jensen, 1987; Schmitz and Hof, 2005). In contrast, the projection
areas of the FG and area 17 [combined analysis of all layers (FG
and area 17), followed by separate analyses of layers II, III, IV, V
and VI (FG)], were determined by tracing their boundaries on
each selected section on video images displayed on the monitor of
the stereology workstation (see Fig. S1 in Supplementary data). No
specific descriptions of the cytoarchitecture of the CGM in the FG
have been provided in the literature. We therefore used the
general criteria as provided by, for example, Braak (1980) and
Kandel et al. (2000) to discriminate cortical layers using the
advanced differentiability of laminar boundaries in 200mm thick
and 500mm thick gallocyanin-stained sections from human post-
mortem brains (see also Heinsen et al., 2000); layers II and IV
comprise mainly small spherical (granule) neurons, layer III
contains mainly pyramidal-shaped neurons and those laying deep
in layer III are larger compared to those located more super-
ficially. Layer V includes pyramidal-shaped neurons that are larger
than those in layer III, and layer VI is a heterogeneous layer of
neurons blending into the white matter and forming the deep
limit of the cortex (Fig. S1 in Supplementary Data).
Total neuron numbers were estimated with the Optical
Fractionator (West et al., 1991; Schmitz and Hof, 2005). All
neurons whose nucleus top came into focus within unbiased
virtual counting spaces distributed in a systematic-random fashion
throughout the delineated regions were counted, and their
perikaryal volume was measured with the Nucleator (Gundersen,
1988; Schmitz and Hof, 2005) (see Supplementary data about the
use of the Nucleator to estimate mean perikaryal volumes on
coronal sections). Neurons were differentiated from glial and
endothelial cells by histological criteria. Neurons showed a large
cytoplasm, and a prominent nucleolus within a pale nucleus. Glial
cells were identified by the absence of cytoplasmic staining, intense
staining of the nucleus with dispersed chromatin and lack of a
nucleolus (see Fig. S2 in Supplementary data).
Then, total neuron numbers were calculated from the numbers
of counted neurons and the corresponding sampling probability,
as well as the mean perikaryal volume of all analysed neurons. All
details of the counting procedure (including information about
the sampling parameters) for all investigated brain regions are
summarized in Table 2. Select cases were analysed for total neuron
numbers with the same parameters by three independent
researchers (I.A.J.v.K., S.J.M.C.P. and P.v.C.). In all cases, the
inter-rater variability was55%, reflecting the benefits of the high-
precision design-based stereology approach used here (see also
Schmitz and Hof, 2005). However, a comprehensive inter-rater/
intra-rater analysis was not performed.
For both patients with autism and controls, mean and SEM were
calculated for all investigated variables. Then, Kolmogorov–
Smirnov (KS) tests were performed to assess whether the values
from each investigated variable came from a Gaussian distribution
(these analyses were performed separately for the patients with
autism and the controls). Only in four out of 58 datasets (6.9%)
(two groups and 29 investigated variables per group) it was found
that the data did not pass the KS normality test [patients with
autism: density in the CGM (P=0.007) and neuron density in
layer V of the FG (P=0.028); controls: volume of area 17
(P=0.047) and mean perikaryal volume of the neurons in layer III
of the FG (P=0.045)]. All other datasets passed the KS normality
T able 2 Details of the stereological analysis procedures
Hem CGMArea17 FG I-VI FG IIFG IIIFG IV FG VFG VI
sla-x, sla-y (mm)
sln-x, sln-y (mm)
Hem=entire hemisphere; CGM=cortical grey matter; FG=fusiform gyrus; I, II, III, IV,Vand VI, cortex layers I, II, III, IV,Vand VI.
S=average number of analysed sections; Obj.1=objective used for delineating the regions of interest and point counting; sla-x and
sla-y=distance between the points used for volume estimates in mutually orthogonal directions x and y; ?P=average number of points
counted; Obj. 2=objective used for counting neurons and estimating perikaryal volume; sln-x and sln-y, distance between the unbiased
virtual counting spaces used for counting neurons in mutually orthogonal directions x and y; a and h=base and height of the unbiased
virtual counting spaces; d=depth within the section at which the unbiased virtual counting spaces were placed; ?OD=average number of
unbiased virtual counting spaces used; ?N=average number of neurons counted; t1=measured actual average section thickness of the
sections cut at 200mm after histological processing; t2=measured actual average section thickness of the sections cut at 500mm after
histological processing; CEpred(n)=average predicted coefficient of error of the estimated total neuron numbers using the prediction
method described by Schmitz and Hof (2000).
Neuron numbers in autismBrain (2008),131,987^999 991
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test with P40.1. Furthermore, F-tests were performed to compare
the variances of all investigated variables between patients with
autism and controls. For none of the 29 investigated variables, the
variances were significantly different between the two groups (i.e.
P40.05). Accordingly, comparisons between patients with autism
and controls could be performed with parametric statistics using
generalized linear model multivariate analysis (MANOVA), with
diagnosis as fixed factor and the patients’ age, sex, hemisphere,
post-mortem interval, brain weight and fixation time as covariates
(see Supplementary data for details about reasons not to consider
the history of seizures of some of the patients with autism in the
statistical analysis). For each investigated variable, all investigated
brain regions were tested simultaneously. Post hoc tests in the
analyses of covariance were performed with linear regression
analysis (patients’ age and fixation time) or two-way analysis of
variance (hemisphere). In all analyses, an effect was considered
statistically significant if its associated P-value was 50.05. To test
the hypothesis that the results of this study were independent of
the higher mean age of the controls than the mean age of the
patients with autism, the statistical analysis was repeated by
disregarding the control cases (i) C10, (ii) C9 and C10 and (iii)
C8 to C10. Calculations were performed using SPSS (Version
12.0.1 for Windows; SPSS, Chicago, IL, USA) and GraphPad
Prism (Version 4.0 for Windows, GraphPad software, San Diego,
Photomicrographs shown in Figs 1, 2 and S1 (Supplementary
data) were produced by digital photography using the stereology
workstation described above. On average, ?100 images were
captured for the composite in each Fig. 1A and B, 25 images for
the composite in each Fig. 1C–F, 70 images for the composite in
Fig. 2 and 60 images for the composite in Fig. S1A. These images
were made into one montage using the Virtual Slice module of
the StereoInvestigator software. Photomicrographs shown in
Figs 3A–K and S2 (in Supplementary data) were produced by
digital photography using an Olympus DP 70 digital camera
attached to an Olympus AX 70 microscope and cellPsoftware
(version 2.3; Soft Imaging System, Mu ¨nster, Germany). The
final figures were constructed using Corel Photo-Paint v.11 and
Corel Draw v.11 (Corel, Ottawa, Canada). Only minor adjust-
ments of contrast and brightness were made, without altering the
appearance of the original materials.
The FG (and separate layers II, III, IV, V and VI), area 17
and the CGM were identified on all sections showing these
regions according to Figs 1, 2 and S1 (Supplementary data).
The mean volumes of the investigated brain regions did not
significantly differ between the patients with autism and the
controls (Fig. S3 and Table S2 in Supplementary data).
Compared to the controls, the patients with autism
showed a significantly reduced mean neuron density in
layer III of the FG [?13.1%; F(1)=19.321 (one degree of
freedom), P=0.002] (Fig. S4 in Supplementary data).
Furthermore, the patients with autism had a significantly
reduced mean total neuron number in layers III [?23.7%;
F(1)=6.356, P=0.033], V [?14.3%; F(1)=6.446, P=0.032]
and VI [?10.6%; F(1)=5.518, P=0.043] of the FG
compared to the controls (Figs 3 and 4). In layer III, the
reduced mean total neuron number reflected a combined
reduction in the mean volume of this layer [?12.7%
(patients with autism versus controls)] as well as the mean
neuronal density within this layer (?13.1%). In contrast,
the reduced mean total neuron number in layers V and
VI reflected a reduced mean volume of these layers
Fig. 3 Representative photomicrographs of 200mm thick coronal
sections showing layers II (A, B), III (C, D), IV (E, F),V (G,H) and
VI (I, K) of the fusiform gyrus in the brains from a control patient
(A,C, E,G, I) and a patient with autism (B, D, F,H, K).These
photomicrographs arerepresentative of themagnification at which
the stereological estimates were performed. Note the reduced
numbers of neurons in layers III,Vand VI in the brain from the
patient with autism compared to the control. Scale bar=50mm.
992 Brain (2008),131,987^999 I. A. J. van Kooten et al.
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Fig. 4 Total neuron numbers in the cortical grey matter (CGM) (A1, A2, A3), area17 (B1, B2, B3) and layers II, III, IV,Vand VI of the
fusiform gyrus (FG) (C1,C2,C3to G1,G2,G3, respectively), in post-mortem brains from seven patients with autism (A; open bars in A1to
G1, squares in A3to G3) and10 matched controls (C; closed bars in A1to G1, dots in A2to G2). In A1to G1, data from patients with autism
and controls are shown as mean and standard error of the mean. In A2to G2, individual data from controls are shown as a function of the
persons’age.Blackdotsrepresentdata obtained onbrains cut at 200 mm and open dots data obtained onbrains cut at 500mm.In A3to G3,
individual data from patients with autism are shown as a function of the patients’age.Black squares representdata obtained on brains from
patients without history of seizures, and open squares data obtained on brains from patients with a history of seizures.?P50.05 for the
fixed factor diagnosis in general linear model multivariate analysis of variance (MANOVA).
Neuron numbers in autism Brain (2008),131,987^999993
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[?16.8% (layer V) and ?17.0% (layer VI), respectively],
rather than a reduced mean neuronal density within these
layers [actually the mean neuronal density was slightly
increased in layer V (+2.7%) and layer VI (+8.0%) in the
brains from the patients with autism compared to the
In addition,the patients
significantly reduced mean perikaryal volume of the
neurons in layers V [?21.1%; F(1)=14.763, P=0.004]
and VI [?13.4%; F(1)=8.853, P=0.016] of the FG (Figs 3
and 5) compared to the controls. There were no significant
differences between the patients with autism and the
controls with respect to neuron density, total neuron
number and mean perikaryal volume in the whole CGM
and in area 17 (Figs 4 and 5, as well as Fig. S4 in
The statistical analysis showed a number of significant
effects of the covariates on the investigated variables. With
respect to the variables which showed significant differences
between the patients with autism and the controls, the age
of the subjects under study and the fixation time had a
significant effect on the perikaryal volume in layer V of the
FG [F(1)=6.910, P=0.027 (patients’ age) and F(1)=5.446,
P=0.044 (fixation time), respectively]. However, post hoc
linear regression analysis only revealed a positive significant
correlation between the controls’ age and the perikaryal
volume in layer V of the FG [r2=0.444, F(1,10)=6.384,
P=0.035]. Accordingly, there was no positive correlation
between the age of the patients with autism and the
perikaryal volume in layer V of the FG [r2=0.053,
F(1,7)=0.27, P=0.620]. Furthermore, the hemisphere had
a significant effect on the mean perikaryal volume in layer
VI oftheFG [F(1)=5.147,
Supplementary data). Moreover, two-way ANOVA showed
a significant difference only in the mean perikaryal volume
in layer VI of the FG with respect to diagnosis (P=0.021)
but not with respect to hemisphere (P=0.073) or the
interaction between diagnosis and hemisphere (P=0.839).
In summary, it can be concluded that the alterations in
mean perikaryal volumes found in the investigated regions
in the brains from the patients with autism were not caused
by the patients’ age and sex, the investigated hemispheres,
the post-mortem interval, the brain weight and the
Finally, it should be mentioned that the outcome of the
present study was the same when the older control cases (i)
C10, (ii) C9 and C10 or (iii) C8 to C10 were disregarded.
Furthermore, the results obtained on the brains cut at
200mm section thickness showed no systematic deviation
from those cut at 500mm (Figs 4 and 5, as well as Figs S3
and S4 in Supplementary data). Moreover, the results
obtained on the brains from the patients with a history of
seizures showed no systematic deviation from those without
a history of seizures (Figs 4 and 5, as well as Figs S3 and S4
in Supplementary data).
with autism showeda
P=0.049] (Fig. S5in
This is the first study focusing on volume, neuron density,
total neuron number and mean perikaryal volume of
neurons in the FG of patients with autism and matched
controls. The main findings of the present study include a
significant reduction in the mean neuron density in layer
III (–13.1%), a reduced mean total neuron number in
layers III, V and VI (?23.7%, ?14.3% and ?10.6%,
respectively) and a decreased mean perikaryal volume of
neurons in layers V and VI in the FG (?21.1% and
?13.4%, respectively) in the brains of the patients with
autism compared to the controls. These alterations did not
reflect general neuropathological alterations found in all
cortical regions in autism, as demonstrated by the fact that
no differences in these variables were found in area 17 or in
the whole CGM. In addition, the age of the patients with
autism was not correlated with any of the observed
neuronal alterations, suggesting that the alterations found
in the FG might be of neurodevelopmental origin. The
mean volumes of the FG and CGM found in the present
(McDonald et al., 2000; Kreczmanski et al., 2007).
Although this study consists of a relatively small sample,
it is, besides the series investigated by Schumann and
Amaral (2006; nine patients with autism versus 10
controls), larger than all other autism post-mortem brain
series studied in the past 20 years (Bauman and Kemper,
1985; Raymond et al., 1996; Bailey et al., 1998; Blatt et al.,
2001; Fatemi et al., 2001; Schumann and Amaral, 2006).
Compared to the controls, we did not find alterations in
the mean volumes of the whole hemispheres and the CGM
in the brains from the patients with autism. The observed
lack of increase in brain volume in patients with autism at
older ages is in accordance with some, but not all, related
MRI studies (Piven et al., 1995; Courchesne et al., 2001;
Hardan et al., 2001; Aylward et al., 2002; Palmen et al.,
2004b). Although it has been suggested that abnormal brain
development is a typical feature of autism regardless of IQ
(Aylward et al., 2002), the differences in outcome between
the present and previous studies may be explained by the
influence of several factors associated with smaller brains
such as mental retardation and epilepsy (Mosier et al.,
1965; Theodore et al., 2003), which are the most common
Canitano, 2007). Despite the fact that exact IQ data were
not available in our study, all patients with autism
investigated here were classified as high functioning patients
in the clinical records.
Incomplete pruning during brain development, resulting
in overabundant synapses and neurons, has been suggested
to result in the larger brain size reported in some patients
with autism (Frith, 2003; Belmonte et al., 2004). As
suggested elsewhere (Courchesne et al., 2004), this could
indicate improper function of overabundant synapses and
neurons in patients with autism, that is eventually followed
994Brain (2008),131,987^999I. A. J. van Kooten et al.
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Fig. 5 Mean perikaryal volume of neurons in area17 (A1, A2, A3) and layers II, III, IV,Vand VI of the fusiform gyrus (FG) (B1, B2, B3to
F1, F2, F3, respectively), in the post-mortem brains from seven patients with autism (A; open bars in A1to F1, dots in A3to F3), and10
controls (C; black bars in A1to F1, squares in A2to F2). In A1to F1, data from patients with autism and controls are shown as mean and
standard error of the mean.In A2to F2, individual data from controls are shown as a function of the persons’age.Blackdotsrepresentdata
obtained on brains cut at 200mm and open dots data obtained on brains cut at 500mm. In A3to F3, individual data from patients with
autism are shown as a function of the persons’ age. Black squares represent data obtained on brains from patients without history of
seizures, and open squares data obtained on brains from patients with a history of seizures.?P50.05 and??P50.01for the fixed factor
diagnosis in general linear model multivariate analysis of variance (MANOVA).
Neuron numbers in autismBrain (2008),131,987^999995
by guest on December 26, 2015
in later childhood by death of neurons and subsequent
normalization or even decrease in brain volume (and total
neuron number in the CGM) in autism. We found no
significant difference in the mean total neuron number in
the CGM between the patients with autism and the
controls. However, this does not provide evidence for or
against the hypothesis that the total neuron number in the
CGM could change with age in brains from patients with
autism. This is due to the fact that our sample encompassed
a rather wide age range (i.e. from 4 to 23 years). Differences
in total neuron number in the CGM could still be there at a
specific age or time period of development. Further
research is necessary to address this question.
A growing body of evidence suggests that patients with
autism have difficulties in face perception (Schultz, 2005).
Recognition of persons, especially of their individual faces,
is a key part of an individual’s social experience and
successful functioning within a social group. Virtually, all
normal adults are experts in the recognition of faces
(Tanaka and Gauthier, 1997), whereas patients with autism
are consistently impaired in this task (Joseph and Tanaka,
reported reduced activity in the FG during face processing
tasks in autism (Schultz et al., 2000; Hall et al., 2003; Hubl
et al., 2003; Hadjikhani et al., 2004; Pierce et al., 2004;
Piggot et al., 2004). In addition, several studies demon-
strated the involvement of a specific region located within
the FG, the FFA (Schultz et al., 2003; Schultz, 2005;
Hadjikhani et al., 2007). This region is more engaged by
human faces than by any other object (Kanwisher et al.,
1997). In the present study, we did not observe differences
in the mean volume of the FG between the patients with
autism and the controls. The same was observed by Pierce
et al. (2001) in a structural neuroimaging study on the FG
in autism, whereas Waiter et al. (2004) reported an
increased FG volume in autism.
With respect to the neurobiological basis of the reduced
activation of the FG during face processing tasks in autism,
the main finding of the present study was a significant
reduction in mean total neuron numbers in both output
layers III and V of the FG in the patients with autism
compared to the controls. Notably, these alterations were
not found in area 17 and the CGM. Cortical layer III is the
principal source of corticocortical (association) connec-
tions, whereas layer V is the principal source of efferent
fibres to sub-cortical regions (Jones, 1986).
Accordingly, our results suggest a disconnection of the
FG or underdeveloped connections in face processing
networks (shown in Fig. S6 in Supplementary data). Area
17 projects via the inferior occipital gyrus (IOG) to the FG.
In addition, the IOG is also connected to the superior
temporal gyrus (STG). Efferent fibres project from the FG
to the amygdala (AMG) and to two regions in the frontal
lobe, the inferior frontal gyrus (IFG) and the orbitofrontal
cortex (OFC) (Fairhall and Ishai, 2007). Thus, there is
evidence that the FG receives input from the visual cortex
via the IOG and provides the major input into an extended
system consisting of cortical regions (including IFG and
OFC) and sub-cortical regions such as the AMG (Fairhall
and Ishai, 2007).
Although individuals with autism do not show deficits in
visual perception in complex object recognition tasks not
involving faces, abnormalities in the visual system in autism
could be a first sign of a failure to develop perceptual
expertise for faces. Thus, there may be a cortical explana-
tion for the deficits in face perception seen in patients with
autism rather than an involvement of limbic structures
(Schultz et al., 2000). However, the present study found no
differential effect in area 17 in patients with autism. This is
supported by a recent finding showing no differences in
activation of the visual cortex (areas V1 to V5) in eight
patients diagnosed with autism spectrum disorder com-
pared to four IQ-matched controls (Hadjikhani et al.,
2004). Rather the IOG and STG showed reduced activity in
patients with autism (Pierce et al., 2001), indicating that the
altered function of the FG in patients with autism cannot
be explained by abnormal input from area 17.
As mentioned above, Casanova et al. (2006) investigated
a subset of the post-mortem brains investigated in the
present study for possible alterations in the modular
organization of cellular microdomains (minicolumns) in
the pre-frontal cortex, primary motor cortex, primary
sensory cortex and primary visual cortex. Casanova et al.
(2006) found an increased neuron density and a slightly
reduced mean neuron size in area 17 in the brains from the
patients with autism compared with the controls. Although
not directly comparable (because of methodological differ-
ences), the findings by Casanova et al. (2006) are in line
with the results of the present study [as shown in Figs 5
and S4 (in Supplementary Data) of the present study].
Our finding of an age-related increase in the mean
perikaryal volume of neurons in layer V of the FG was
unexpected. In a sample of human post-mortem control
brains with ages 4–4–7–14–23–25–48–52–59–65 (in years)
as the one investigated here, one would not predict
significant changes as a function of age, particularly if all
cases were controlled for the absence of neurodegenerative
diseases (as done in our sample). No design-based
stereological studies have been published addressing the
question of age-related alterations in perikaryal size of
neurons in the human cerebral cortex. However, an earlier
study by Schulz and Hunziker (1980) found no significant
difference in the mean perikaryal size of cortical neurons
between a group of people aged 19 to 44 and another group
aged 65 to 74. Unfortunately, our sample did not include
such age groups making a direct comparison between our
data and the results by Schulz and Hunziker (1980)
impossible. Additional research is necessary to evaluate
the possible neurobiological repercussion of an age-related
increase of the mean perikaryal volume of neurons in layer
V of the FG in the human brain, but this was beyond the
focus of the present study.
996Brain (2008),131,987^999 I. A. J. van Kooten et al.
by guest on December 26, 2015
The reduced mean total neuron numbers in layers III and
V of the FG and the reduced mean perikaryal volume of
neurons in layers V and VI of the FG in the patients with
autism could originate from pathological events primarily
in the FG itself, or from loss of targets to which the FG
projects. In this regard, it is important to note that the
AMG receives input from the FG and is involved in face
processing (as shown in Fig. S6 in Supplementary data)
(Schultz et al., 2000; Fairhall and Ishai, 2007). The AMG
plays a role in the interpretation of faces (threatening or
fearful) (Morris etal., 1999),
(Kawashima et al., 1999) and has been implicated in
autism because of its role in social behaviour and cognition
(Adolphs, 2002). Structural imaging studies have reported
increased (Howard et al., 2000; Sparks et al., 2002;
Schumann et al., 2004), decreased (Aylward et al., 1999;
Pierce et al., 2001; Nacewicz et al., 2006) or unchanged
(Haznedar et al., 2000; Palmen et al., 2006) mean volumes
of the AMG in autism [note that this discrepancy may be
due to differences in the ages of the patients among the
available studies; it was suggested by Schumann et al.
(2004) that larger volumes are typically observed in young
subjects, whereas no difference or smaller volumes are
observed in older subjects. However, this question was
beyond the focus of the present study]. In an earlier
neuropathological study, neurons in the AMG were found
to be abnormally small and densely packed in autism
(Kemper and Bauman, 1993), whereas a recent design-
based stereological study found no changes in mean neuron
size but a significantly reduced mean total neuron number
in the AMG overall and in its lateral nucleus in autism
(Schumann and Amaral, 2006). The latter result suggests
target loss of the FG in autism, which could contribute to
reductions in mean total neuron numbers and mean
neuronal size in the FG in autism as reported in the
present study. The FG receives reciprocal input from the
corticomedial nucleus of the AMG; however, these connec-
tions play a minor role during face perception (Fairhall and
Ishai, 2007). Although no reduction in the mean total
neuron number was found in this part of the AMG in
patients with autism (Schumann and Amaral, 2006) and
our data do not show alterations in the main input layers II
and IV of the FG in autism, the results might point to an
intact input from the AMG to the FG. In addition, because
no alterations were found in area 17, input to the FG from
the visual cortex seems to remain intact.
Finally, it should be noted that a reduced mean total
neuron number in the lateral nucleus of the AMG is not
specific for autism, as the same finding was recently
reported for schizophrenia (Kreczmanski et al., 2007). In
this regard, it will be important to evaluate whether the FG
also shows reduced mean total neuron numbers in
schizophrenia (as in autism). The mean volume of the FG
is however comparable in patients with schizophrenia and
controls (McDonald et al., 2000). There is indeed evidence
schizophrenia (Pinkham et al., 2005), yet patients with
schizophrenia do not show
responses in the FG during face perception tasks studied
with fMRI (Yoon et al., 2006).
In summary, although based on a relatively small sample
of post-mortem brains, the present study provides novel
insight into the neuropathology of autism. Specifically,
reduced mean total neuron numbers and smaller neurons
in the main output layers of the FG in patients with autism
might be involved in impaired face processing in autism.
Although the precise interpretation of the reported FG
hypoactivity in fMRI studies in autism has not yet been
clearly established, Pierce et al. (2001) suggested that face
processing could also occur outside the FG and FFA. In this
regard, both the IFG (semantic aspects) (Leveroni et al.,
2000) and the OFC (facial attractiveness and sexual
relevance) (O’Doherty et al., 2003; Kranz and Ishai, 2006)
belong to the cortical networks mediating face processing
(Fairhall and Ishai, 2007) and are related to autism.
Interestingly, imaging studies found a reduced activation
of the IFG (Just et al., 2004; Harris et al., 2006; Koshino
et al., 2007) and a decreased volume of the OFC in autism
(Hardan et al., 2006; Girgis et al., 2007). It will therefore be
of interest to investigate total neuron numbers and neuron
densities in the IFG and OFC in post-mortem brains of
patients with autism as well. Further studies are needed to
test the hypothesis that there is a causal relationship
between abnormal activation of the FG and related cortical
areas in face processing in autism and the neuropatholo-
gical findings reported in the present study.
Supplementary material is available at Brain online.
We are indebted to E.K. Broschk and A. Bahrke for expert
technical assistance. The authors gratefully acknowledge the
following institutions and colleagues for the provision of
human tissue: the Harvard Brain Tissue Research Center
(Belmont, MA, USA), the University of Maryland Brain and
Tissue Bank for Developmental Disorders (Baltimore, MD,
USA), the US Autism Tissue Program (Princeton, NJ,
USA), Dr J. Wegiel (New York State Institute for Basic
Research in Developmental Disabilities, Staten Island, NY,
USA) and NIH grant NO1 HD13138. P.R.H. is the
Regenstreif Professor of Neuroscience. This work was
supported by the US National Alliance for Autism
European Community (Quality of Life and Management
of Living Resources, QLK6-CT-2000-60042, QLK6-GH-00-
60042-56; to S.J.M.C.P.), the Korczak foundation (to
H.v.E.), the James S. McDonnell Foundation (22002078 to
P.R.H.), and by NIH grant MH66392 (to P.R.H.).
Neuron numbers in autism Brain (2008),131,987^999 997
by guest on December 26, 2015
Adolphs R. Neural systems for recognizing emotion. Curr Opin Neurobiol
2002; 12: 169–77.
American Psychiatric Association. Diagnostic and statistical manual of
mental disorders (DSM-IV). 4th edn. Washington (DC): American
Psychiatric Association; 1994.
AylwardEH,MinshewNJ, FieldK,SparksBF, SinghN.Effects ofage onbrain
volume and head circumference in autism. Neurology 2002; 59: 175–83.
Aylward EH, Minishew NJ, Goldstein G, Honeycutt NA, Augustine AM,
Yates KO, et al. MRI volumes of amygdala and hippocampus in non-
mentally retarded autistic adolescents and adults. Neurology 1999; 53:
Bailey A, Luthert P, Dean A, Harding B, Janota I, Montgomery M, et al.
A clinicopathological study of autism. Brain 1998; 121: 889–905.
Blatt GJ, Fistgerald CM, Guptill JT, Booker AB, Kemper TL, Bauman ML.
Density and distribution of hippocampal neurotransmitter receptors in
autism: an autoradiographic study. J Autism Dev Disord 2001; 31: 537–43.
Baron-Cohen S, Ring H, Moriarty J, Schmitz B, Costa D, Ell P.
Recognition of mental state terms. Clinical findings in children with
autism and a functional neuroimaging study of normal adults. Br J
Psychiatry 1994; 165: 640–9.
Bauman ML, Kemper TL. Histoanatomic observations of the brain in early
infantile autism. Neurology 1985; 35: 866–74.
Belmonte MK, Allen G, Beckel-Mitchener A, Boulanger LM, Carper RA,
Webb SJ. Autism and abnormal development and brain connectivity.
J Neurosci 2004; 24: 9228–31.
Bodfish JW, Symons FJ, Parker DE, Lewis MH. Varieties of repetitive
behaviour in autism: comparisons to mental retardation. J Autism Dev
Disord 2000; 30: 237–43.
Bolte S, Hubl D, Feineis-Matthews S, Prvulovic D, Dierks T, Poustka F.
Facial affect recognition training in autism: can we animate the fusiform
gyrus? Behav Neurosci 2006; 120: 211–6.
Braak H. Architectonics of the human telencephalic cortex. Berlin:
GROßHIRNRINDE. Leipzig: Barth; 1909.
Canitano R. Epilepsy in autism spectrum disorders. Eur Child Adolesc
Psychiatry 2007; 16: 61–6.
Carpenter M. Core text of neuroanatomy. Baltimore: Williams and
Casanova MF, van Kooten IAJ, Switala AE, van Engeland H, Heinsen H,
Steinbusch HWM, et al. Minicolumnar abnormalities in autism. Acta
Neuropathol 2006; 112: 287–303.
Cavalieri B. Geometria indivisibilibus continuorum. Bonoiae: Typis
Clementis Ferronij; 1635 (reprinted as Geometria degli indivisibili.
Unione Tipografico-Editrice Torinese: Torino; 1966).
Courchesne E, Karns CM, Davis HR, Ziccardi R, Carper RA, Tigue ZD.
Unusual brain growth patterns in early life in patients with autistic
disorder. Neurology 2001; 57: 245–54.
Courchesne E, Redcay E, Kennedy DP. The autistic brain: birth through
adulthood. Curr Opin Neurol 2004; 17: 489–96.
Dalton KM, Nacewics BM, Johnstone T, Scheafer HS, Gernsbacher MA,
Goldsmith HH, et al. Gaze fixation and the neural circuitry of face
processing in autism. Nat Neurosci 2005; 8: 519–26.
DiCicco-Bloom E, Lord C, Zwaigenbaum L, Courchesne E, Dager SR,
Schmitz C, et al. The developmental neurobiology of autism spectrum
disorder. J Neurosci 2006; 26: 6897–906.
Fairhall SL, Ishai A. Effective connectivity within the distributed cortical
network for face perception. Cereb Cortex 2007; 17: 2400–6.
Fatemi SH, Halt AR. Altered levels of Bcl-2 and p53 proteins in parietal
cortex reflect deranged apoptotic regulation in autism. Synapse 2001; 42:
Frith C. What do imaging studies tell us about the neuronal basis of
autism? Novartis Found Symp 2003; 251: 149–66.
Girgis RR, Minshew NJ, Melhem NM, Nutche JJ, Keshavan MS,
Hardan AY. Volumetric alterations of the orbitofrontal contex in
autism. Prog Neuropsychopharmacol Biol Psychiatry 2007; 31: 41–5.
Grelotti D, Gauthier I, Schultz RT. Social interest and the development of
cortical facespecialization: what autism teaches us about face
processing. Dev Psychobiol 2002; 40: 213–25.
Guerin P, Lyon G, Barthelemy C, Sostak E, Chevrollier V, Garreau B, et al.
Neuropathological study of a case of autistic syndrome with severe
mental retardation. Dev Med Child Neurol 1996; 38: 203–11.
Gundersen HJ. The nucleator. J Microsc 1988; 151: 3–21.
Gundersen HJG, Jensen EB. The efficiency of systematic sampling and its
prediction. J Microsc 1987; 147: 229–63.
Hadjikhani N, Joseph RM, Snyder J, Chabris CF, Clark J, Steele S, et al.
Activation of the fusiform gyrus when individuals with autism spectrum
disorder view faces. NeuroImage 2004; 22: 1141–50.
Hadjikhani N, Joseph RM, Snyder J, Tager-Flusberg H. Abnormal
activation of the social brain during face perception in autism. Hum
Brain Mapp 2007; 28: 441–6.
Hall GB, Szechtman H, Nahmias C. Enhanced salience and emotion
recognition in autism: a PET study. Am J Psychiatry 2003; 160: 1439–41.
HardanAY, GirgisRR, Lacerda
Keshavan MS, et al. An MRI study of the orbitofrontal cortex in
autism. J Child Neurol 2006; 21: 866–71.
Hardan AY, Minshew NJ, Mallikarjuhn M, Keshavan MS. Brain volume in
autism. J Child Neurol 2001; 16: 421–4.
Harris GJ, Chabris CF, Clark J, Urban T, Aharon I, Steele S, et al. Brain
activation during semantic processing in autism spectrum disorders via
functional magnetic resonance imaging. Brain Cogn 2006; 61: 54–68.
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.
Heinsen H, Arzberger T, Schmitz C. Celloidin mounting (embedding
without infiltration) – a new, simple and reliable method for producing
serial sections of high thickness through complete human brains and its
application to stereological and immunohistochemical investigations.
J Chem Neuroanat 2000; 20: 49–59.
Heinsen H, Heinsen YL. Serial thick, frozen, Gallocyanin stained sections
of human central nervous system. J Histotechnol 1991; 14: 167–73.
Heinsen H, Henn R, Eisenmenger W, Gotz M, Bohl J, Bethke B, et al.
Quantitative investigations on the human enthorhinal area: left – right
asymmetry and age-related changes. Anat Embryol 1994; 190: 181–94.
Herbert MR, Harris GJ, Adrien KT, Ziegler DA, Makris N, Kennedy DN,
et al. Abnormal asymmetry in language association cortex in autism.
Ann Neurol 2002; 52: 588–96.
Howard MA, Cowell PE, Boucher J, Broks O, Mayes A, Farrant A, et al.
Convergent neuroanatomical and behavioural evidence of an amygdala
hypothesis of autism. NeuroReport 2000; 11: 2931–5.
Hubl D, Bolte S, Feineis-Matthews S, Lanfermann H, Federspiel A, Strik W,
et al. Functional imbalance of visual pathways indicates alternative face
processing strategies in autism. Neurology 2003; 61: 1232–7.
Jones EG. Connectivity of the primate sensory-motor cortex. In: Jones EG,
Peters A, editors. Cerebral cortex, Vol. 5. Sensory-motor areas and
aspects of cortical connectivity. New York/London: Plenum; 1986.
Joseph RM, Tanaka J. Holistic and part-based face recognition in children
with autism. J Child Psychol Psychiatry 2002; 43: 1–14.
Just MA, Cherkassky VL, Keller TA, Minshew NJ. Cortical activation and
synchronization during sentence comprehension in high-functioning
autism: evidence of underconnectivity. Brain 2004; 127: 1811–21.
Kandel ER, Schwartz JH, Jessell TM. Principles of neural science. 4th edn.
Columbus: McGraw-Hill; 2000.
Kanwisher N, McDermott J, Chun MM. The fusiform face area: a module
in human extrastriate cortex specialized for face perception. J Neurosci
1997; 17: 4302–11.
Kanwisher N, Stanley D, Harris A. The fusiform face area is selective for
faces not animals. NeuroReport 1999; 10: 183–7.
Kawashima R, Sugiura M, Kato T, Nakamura A, Hatano K, Ito K, et al.
The human amygdala plays an important role in gaze monitoring. Brain
1999; 122: 779–83.
998 Brain (2008),131,987^999 I. A. J. van Kooten et al.
by guest on December 26, 2015
Kemper TL, Bauman ML. The contribution of neuropathologic studies to Download full-text
the understanding of autism. Neurol Clin 1993; 11: 175–87.
Koshino H, Kana RK, Keller TA, Cherkassy VL, Minshew NJ, Just MA.
fMRI investigation of working memory for faces in autism: visual
coding and underconnectivity with frontal areas. Cereb Cortex 2007
[Epub ahead of print May 20].
Kranz F, Ishai A. Face perception is modulated by sexual preference. Curr
Biol 2006; 16: 63–8.
Kreczmanski P, Heinsen H, Mantua V, Woltersdorf F, Masson T, Ulfig N,
et al. Volume, neuron density, and total neuron number in five
subcortical regions in schizophrenia. Brain 2007; 130: 678–92.
Leveroni CL, Seidenberg M, Mayer AR, Mead LA, Binder JR, Rao SM.
Neural systems underlying the recognition of familiar and newly learned
faces. J Neurosci 2000; 20: 878–86.
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.
McDonald B, Highley JR, Walker MA, Herron BM, Cooper SJ, Esiri MM,
et al. Anomalous asymmetry of fusiform and parahippocampal gyrus
grey matter in schizophrenia: a post mortem study. Am J Psychiatry
2000; 157: 40–7.
Morris JS, Ohman A, Dolan RJ. A subcortical pathway to the right amygdala
mediating ‘unseen’ fear. Proc Natl Acad Sci USA 1999; 96: 1680–5.
Mosier HD Jr, Grossman HJ, Dingman HF. Physical growth in mental
defectives. A study in an institutionalized population. Paediatrics 1965;
Nacewicz BM, Dalton KM, Johnstone T, Long MT, McAuliff EM,
Oakes TR, et al. Amygdala volume and nonverbal social impairment
in adolescent and adult males with autism. Arch Gen Psychiatry 2006;
O’Doherty J, Winston J, Critchley H, Perret D, Burt DM, Dolan RJ. Beauty
in a smile: the role of medial orbitofrontal cortex in facial attractiveness.
Neuropsychologia 2003; 41: 147–55.
Palmen SJMC, Van Engeland H, Hof PR, Schmitz C. Neuropathologic
findings in autism. Brain 2004a; 127: 2572–83.
Palmen SJMC, Hulshoff Pol HE, Kemner C, Schnack HG, Janssen J,
Kahn RS, et al. Larger brains in medication naı ¨ve high-functioning
subjects with pervasive developmental disorder. J Autism Dev Disord
2004b; 34: 603–13.
Palmen SJMC, Durston S, Nederveen H, Van Engeland H. No evidence for
preferential involvement of medial temporal lobe structures in high-
functioning autism. Psychol Med 2006; 36: 827–34.
Paxinos G, Mai K. The human nervous system. San Diego: Elsevier
Academic Press; 2004.
Pierce K, Mu ¨ller RA, Ambrose J, Allen G, Courchesne E. Face processing
occurs outside the fusiform ‘face area’ in autism: evidence from
functional MRI. Brain 2001; 124: 2059–73.
Pierce K, Haist F, Sedagat F, Courchesne E. The brain response to
personally familiar faces in autism: findings of fusiform activity and
beyond. Brain 2004; 127: 2703–16.
Piggot J, Kwon H, Mobbs D, Blasey C, Lotspeich L, Menon V, et al.
Emotional attribution in high-functioning individuals with autism
spectrum disorder: a functional imaging study. J Am Acad Child
Adolesc Psychiatry 2004; 43: 473–80.
Pinkham A, Penn D, Wangelin B, Perkins D, Gerig G, Gu H, et al. Facial
emotion perception and fusiform gyrus volume in first episode
schizophrenia. Schizophr Res 2005; 79: 341–3.
Piven J, Arndt S, Bailey J, Haverkamo S, Andreasen NC, Palmer P. An
MRI study of brain size in autism. Am J Psychiatry 1995; 152: 1145–9.
Raymond GV, Bauman ML, Kemper TL. Hippocampus in autism: a Golgi
analysis. Acta Neuropathol 1996; 91: 117–9.
Sasson NJ. The development of face processing in autism. J Autism Dev
Disord 2006; 36: 381–94.
Schmitz C, Hof PR. Recommendations for straightforward and rigorous
methods of counting neurons based on a computer simulation
approach. J Chem Neuroanat 2000; 20: 93–114.
Schmitz C, Hof PR. Design-based stereology in neuroscience. Neuroscience
2005; 130: 813–31.
Schulz U, Hunziker O. Comparative studies of neuronal perikaryon size
and shape in the aging cerebral cortex. J Gerontol 1980; 35: 483–91.
Schultz RT. Developmental defecits in social perception in autism: the role
of the amygdala and the fusiform face area. Int J Dev Neurosci 2005; 23:
Schultz RT, Gauthier I, Klin A, Fulbright RK, Anderson AW, Volkmar F,
et al. Abnormal ventral tenporal cortical activity during face discrimina-
tion among individuals with autism and Asperger syndrome. Arch Gen
Psychiatry 2000; 57: 331–40.
Schultz RT, Grelotti DJ, Klin A, Kleinman J, Van der Gaag C, Marois R,
et al. The role of the fusiform face area in social cognition: implications
for the pathobiology of autism. Philos Trans R Soc Lond B Biol Sci
2003; 358: 415–27.
Schumann CM, Amaral DG. Stereological analysis of amygdala neuron
number in autism. J Neurosci 2006; 26: 7674–9.
Schumann CM, Hamstra J, Goodlin-Jones BL, Lotspeich LJ, Kwon H,
Buonocore MH, et al. The amygdala is enlarged in children but not
adolescents with autism; the hippocampus is enlarged at all ages.
J Neurosci 2004; 24: 6392–401.
Sparks BF, Friedman SD, Shaw DW, Aylward EH, Echelard D, Artru AA,
et al. Brain structural abnormalities in young children with autism
spectrum disorder. Neurology 2002; 59: 184–92.
Tanaka JW, Gauthier I. Expertise in object and face recognition. In:
Goldstone RL, Schyns PG, Medin DL, editors. Psychology of learning
and motivation. San Diego: Academic Press; 1997. p. 83–125.
Theodore WH, DeCarli C, Gaillard WD. Total cerebral volume is reduced
in patients with localization-related epilepsy and a history of complex
febrile seizures. Arch Neurol 2003; 60: 250–2.
Van Kooten IAJ, Hof PR, van Engeland H, Steinbusch HWM, Patterson PH,
Schmitz C. Autism: neuropathology, alterations of the GABAergic system,
and animal models. Int Rev Neurobiol 2005; 71: 1–26.
Waiter GD, Williams JHG, Murray AD, Gilchrist A, Perret DI, Whiten A.
A voxel-based investigation of brain structure in male adolescents with
autism spectrum disorder. NeuroImage 2004; 22: 619–25.
West MJ, Slomianka L, Gundersen HJ. Unbiased stereological estimation
of the total number of neurons of the rat hippocampus using the optical
fractionator. Anat Rec 1991; 231: 482–97.
Yoon JH, D’Esposito M, Carter CS. Preserved function of the fusiform face
area in schizophrenia as revealed by fMRI. Psychiatry Res 2006; 148:
Neuron numbers in autismBrain (2008),131,987^999999
by guest on December 26, 2015