Abstract

This study presents the first three-dimensional mapping of cortical sulcal patterns in autism, a pervasive developmental disorder, the underlying neurobiology of which remains unknown. High-resolution T1-weighted MRI scans were acquired in 21 autistic (age 10.7 ± 3.1 years) and 20 normal control (age 11.3 ± 2.9) children and adolescents. Using parametric mesh-based analytic techniques, we created three-dimensional models of the cerebral cortex and detailed maps of 22 major sulci in stereotaxic space. These average maps revealed anatomic shifting of major sulci primarily in frontal and temporal areas. Specifically, we found anterior and superior shifting of the superior frontal sulci bilaterally (P ≤ 0.0003), anterior shifting of the right Sylvian fissure (P = 0.0002), the superior temporal sulcus (P = 0.0006 right, P = 0.02 left) and the left inferior frontal sulcus (P ≤ 0.002) in the autistic group relative to the normal group. Less significant sulcal shifts occurred in the intraparietal and collateral sulci. These findings may indicate delayed maturation in autistic subjects in these brain regions involved in functions including working memory, emotion processing, language and eye gaze.

Introduction

Autism is a pervasive developmental disorder marked by social deficits, speech and communication problems, and repetitive behaviors (American Psychiatric Association, 1994). Neuroanatomic and neuroimaging investigations demonstrate a variety of brain abnormalities in this disorder; however the key underlying neurobiological anomalies remain unknown. Neuropathologic findings include abnormalities in the size and density of neurons in forebrain areas including hippocampus, amygdala, entorhinal cortex, mammillary body and septum (Kemper and Bauman, 1993). In addition, several studies demonstrate a decreased number of Purkinje cells in the cerebellum (Ritvo et al., 1986; Kemper and Bauman, 1993; Bailey et al., 1998). Although the neuroimaging literature in autism contains some conflicting findings in these areas, there is MRI evidence of limbic (Filipek, 1992; Mountz et al., 1995; Abell et al., 1999; Aylward et al., 1999; Haznedar et al., 2000; Howard et al., 2000; Pierce et al., 2001) and cerebellar abnormalities (Courchesne et al., 1988, 1994; Kates et al., 1998; Carper and Courchesne, 2000) strongly associated with this disorder.

While these studies clearly implicate the limbic system and cerebellum, there is increasing pathological and structural evidence for neocortical involvement in autism. This evidence includes increased brain size (Filipek, 1992; Piven et al., 1995, 1996; Hardan et al., 2001), and irregularities of the cortical surface such as polymicrogyria, macrogyria and schizencephaly (Ritvo et al., 1986; Gaffney and Tsai, 1987; Kemper, 1988; Piven et al., 1990; Bailey et al., 1998). In addition, Berthier (Berthier, 1994) reported qualitative MRI evidence of smaller gyri and wider sulci in a small group of subjects with Asperger’s syndrome. Post-mortem findings of cortical abnormalities including increased frontal cortical neuronal density and cortical dysgenetic lesions further support the notion of cortical involvement in this disorder (Bailey et al., 1998). While non-specific to autism, these cortical anomalies may indicate defective neuronal proliferation, migration or pruning (Rorke, 1994; Mischel et al., 1995). Derangements of these processes in autistic individuals would be expected to be reflected elsewhere in brain structure, such as abnormal organization of cortical architecture (Berthier et al., 1990).

Functional imaging studies provide further evidence for neocortical involvement in autism. Findings from these studies demonstrate delayed maturation of the frontal lobes (Zilbovicius et al., 1995), and bilateral hypoperfusion of temporal lobe areas (Ohnishi et al., 2000; Zilbovicious et al., 2000) in autistic children at rest. Activation studies demonstrate altered activity in cortical regions including the fusiform gyrus (Critchley et al., 2000; Schultz et al., 2000; Pierce et al., 2001), left middle temporal gyrus (Critchley et al., 2000), inferior temporal gyrus (Schultz et al., 2000) inferior occipital gyrus and superior temporal sulcus (Pierce et al., 2001) in autistic subjects during face processing tasks; and abnormal activation of the STG bilaterally during auditory activation tasks (Boddaert et al., 2001).

In order to understand these activation differences, it is important to examine for corresponding structural abnormalities in these areas. Abell et al. (Abell et al., 1999) utilizing statistical parametric mapping (SPM), described gray matter volume abnormalities in sulcal/gyral regions in a population of high-functioning autistic subjects including left occipitotemporal cortex, right inferior temporal gyrus, left middle temporal gyrus and left inferior frontal sulcus. Although SPM provides information regarding gray matter volumes, this method does not allow for analysis of the organization of the cortical surface. Recent development of a novel parametric mesh-based analytic technique enables three-dimensional (3-D) visualization of the external surface of the cerebrum (Thompson et al., 2001). This technique allows the computerized analysis of sulcal and gyral anatomy, including length, spatial orientation, symmetry and complexity as well as volume. As studies of normal development suggest that cortical anatomy undergoes continued changes into late adolescence (Blanton et al., 2001), it is important to analyze patterns of cortical anatomy in subject groups as related to normal developmental change. We have recently employed this cortical surfacing technique to investigate cortical asymmetry and complexity patterns in normal children (Blanton et al., 2001). In the present study, we use this technique to examine possible abnormalities in cortical sulcal patterns in autistic children as compared with normal subjects.

Materials and Methods

Subjects

Twenty-one subjects with autistic disorder and one subject with pervasive developmental disorder, NOS (mean ± SD = 10.7 ± 3.1) and 20 normal (mean age: 11.3 ± 2.9) children participated in this study. The study was approved by the UCLA Human Subjects Protection Committee, and all parents of subjects provided written informed consent for participation.

Inclusion criteria for the autistic subjects were a DSM-IV (American Psychiatric Association, 1994) diagnosis of autism or pervasive developmental disorder, absence of medical or neurological illness, and PIQ > 70. Diagnoses were based upon structured interviews using the Autism Diagnostic Interview Revised (ADI-R) (Lord et al., 1994) and the Autism Diagnostic Observation Schedule (ADOS) (Lord et al., 1999). The ADI-R, a semi-structured interview administered to the primary caregivers and the ADOS are widely used in the diagnosis of autism. The ADI-R has excellent reliability and validity (Le Couteur et al., 1989), as does the ADOS-G (Lord et al., 2000). The mean FS/V/P IQ of the patients was 98/96/100 (SD = 13/11/17).

Normal control children were recruited from public and private schools in the community. Potential control children were screened for neurological, psychiatric, language, or hearing disorders by clinical interview, developmental history and K-SADS-PL (Kaufman et al., 1997) interviews with the parent. The K-SADS-PL is a highly reliable structured interview used to assess a wide range of psychiatric disorders according to either DSM-III-R or DSM-IV criteria. We excluded children from the normal sample if they met criteria for any lifetime significant medical disorder or Axis I mental disorder. The mean FS/V/P IQ of the control group was 114/113/117 (SD = 14/14/14).

Magnetic Resonance Imaging

All subjects completed MRI scans performed on the same 1.5 Tesla GE Signa magnetic resonance imaging scanner (GE Medical Systems, Milwaukee, WI). T1-weighted spoiled grass (SPGR) sequences were obtained using two imaging acquisition protocols: (i) a coronal plane acquisition with slice thickness of 1.4 mm, repetition time of 42/43, echo time of 5/6, flip angle of 35 and (ii) a sagittal plane acquisition with slice thickness of 1.2 mm, repetition time of 14.6, echo time of 3.3, flip angle of 35. Both sequences used an acquisition matrix of 256 × 192, FOV 24 cm and two excitations.

Image Preprocessing

Each scan was processed with a series of steps to prepare for manual delineation of cortical sulci. The methods for image preprocessing and sulcal delineation have been described in detail by Blanton et al. (Blanton et al., 2001) and will be briefly summarized here. First a radio-frequency correction (Sled et al., 1998) was applied to ameliorate possible magnetic field inhomogeneities. Secondly, 20–30 known gray, white and cerebrospinal fluid (CSF) values were chosen for each subject to generate tissue-type distribution maps. Extracerebral tissue and the cerebellum were subsequently manually removed to enable extraction of the cerebral cortex. Total brain volume (TBV) measurements were then analyzed by setting a threshold that effectively prohibited any brain matter that was neither gray matter nor white matter from being included. The TBV was automatically computed by summing the volumes of all individually labeled slices excluding the cerebellum. All scans were then digitally aligned and rotated into a Talairach-based coordinate system (Talairach and Tournoux, 1988) using the anterior commissure as the center of origin. Datasets were then resliced into 1 mm sections. Finally, a high-resolution surface rendered model of the cortex was generated for each case using a 3-D active surface algorithm (MacDonald et al., 1994; Thompson et al., 1997). This algorithm extracts cerebrospinal fluid (CSF)/gray matter and gray/white matter boundaries and models the surface of the cortex as a mesh of triangular elements.

Sulcal Delineation

One rater, blind to age, gender and diagnosis, manually traced 11 major sulci on each 3-D, high-resolution cerebral model (Fig. 1). Sulcal curves for each hemisphere were traced for the superior and inferior frontal, pre-central, central, and post-central, superior temporal sulcal body and ascending ramus, intraparietal sulci, collateral and olfactory sulci, and the Sylvian fissure. In addition, resliced coronal, axial and sagittal viewing planes were used in conjunction with the 3-D cortical volume to corroborate sulcal identity. Tracings of 10 scans by two raters demonstrated an intraclass correlation coefficient of ≥0.98 for the inferior frontal, superior temporal, Sylvian fissure, postcentral, precentral and central sulci. Rater drift was assessed by randomly interleaving one scan with all other scans six times. A maximum intrarater error of 4.5 mm [3-D root mean square (r.m.s.) measure of variability] was found in intraparietal regions. However, the majority of error in tracing cortical sulci fell below 2 mm.

3-D Averaging

Inter-individual sulcal curves were averaged using the parametric surface-based approach of Thompson et al. (Thompson et al., 1996, 1997). As each sulcus is manually traced, a series of coordinate points is sampled along the x-, y- and z-axis. Each sulcal curve is reparameterized as a parametric grid resampled into 150 uniformly spaced coordinate point locations. A r.m.s. measure of variability is then calculated that describes the local deviations around its average anatomy for a particular group. Displacement maps are calculated by measuring the distance of corresponding points between an average sulcal surface in the subject group as opposed to the average sulcal surface of the control group. Group differences are then computed as displacement vectors. A color coded look-up table was then applied to represent sulcal variation in anatomic position.

Statistical Analysis

The coordinate spatial positions of the cerebral sulci were treated as dependent variables to assess for between group differences using analysis of variance, correcting for TBV and gender. There was no significant difference between groups in age or TBV. Right and left hemispheric variables were used as repeated measures in paired t-tests to test for possible asymmetries. We assessed 11 measures for each sulcus and hemisphere for a total of 264 variables. We report all P values ≤ 0.05 recognizing that at this Type I error rate 13/264 may be significant by chance alone.

Results

As shown in Table 1, 40 comparisons met the level of statistical significance of <0.05, a rate three-fold greater than the rate expected by chance alone.

Group Differences — 3-D Average Maps

As illustrated in Figure 2, autistic subjects show specific differences from controls particularly in the superior frontal sulci bilaterally and in the right Sylvian fissure. This analysis demonstrated an anterior and superior shifting of the left and right superior frontal sulci (P ≤ 0.0003) and anterior shifting of the right Sylvian fissure (P = 0.0002) in the autistic subjects relative to the normal group. Moreover, the main body of the right (P = 0.0006) superior temporal sulcus was found to be shifted anteriorly in anatomic position and to have a significantly larger vertical extent (P = 0.009 right, 0.025 left) in autistic subjects as compared with the normal group; this was true for the left superior temporal sulcus as well, but only at the P = 0.02 level. Additionally, we found anterior shifting of the left inferior frontal sulcus in the autistic group relative to the normal group (P ≤ 0.002).

The intraparietal sulci and ascending rami of the superior temporal sulcus were shifted superiorly in each hemisphere in the autistic group (P ≤ 0.03). This effect was strongest for the left intraparietal sulcus (P = 0.006).

Analyses of the precentral, central and postcentral sulci in the autistic group revealed superior shifting of all three sulci bilaterally particularly in precentral (P = 0.007 left, P = 0.0002 right) sulci. In addition, anterior shifting occurred in the left central (P = 0.0006) and right precentral (P = 0.013) sulci.

Finally, on the ventral aspects of the brain, there was anterior shifting of the olfactory sulcus bilaterally (P = 0.002) and lateral shifting of the collateral sulcus, particularly on the right (P = 0.016) in the autistic group as compared with the normal group.

We found no evidence of outliers, clustering or non-normality in the distribution of these data.

Asymmetries

In both the autistic and normal groups, the left Sylvian fissure was found to extend more posteriorly in the left hemisphere as compared with the right (P < 0.001).

Discussion

In this evaluation of structural brain findings using a novel 3-D parametric mesh-based technique, we report significant differences of cortical sulcal patterns in the autistic subjects in the superior frontal sulcus, Sylvian fissure, and inferior frontal, superior temporal and olfactory sulci. These brain regions are involved in functions including working memory, emotion processing, language and eye gaze. Less striking changes occurred in the intraparietal and collateral sulci, areas involved in eye gaze and facial recognition. Although the autistic subjects showed a shifting of these sulci, normal asymmetry was still preserved with both autistic and normal children showing L > R asymmetries in the Sylvian fissure.

The nature of the sulcal pattern differences between patients with autism and normal controls was quite similar in almost all instances in that the sulci of the autistic children were shifted anteriorly and/or superiorly. Our developmental data on sulcal pattern change in normal children (Blanton et al., 2001) demonstrated posterior shifting with age in the inferior frontal gyrus. Therefore, these findings of anterior shifting in the autistic children suggest delayed or incomplete maturation at least in the frontal lobe, similar to previous fMRI findings by Zilbovicious et al. (Zilbovicious et al., 1995).

Our most robust findings were in the superior frontal sulcus (SFS) and the Sylvian fissure. While the right Sylvian fissure was displaced anteriorly, both left and right SFS were shifted both anteriorly and superiorly. This is the first report, to our knowledge, of a clear anatomical difference in these regions in autistic subjects as compared with normal control subjects. The superior frontal gyrus is active during tasks generating emotion using a variety of stimuli including visual, auditory and olfactory (Royet et al., 2000). It has been proposed that this gyrus is involved in some aspects of emotional processing such as monitoring or consciously experiencing emotion (Lane et al., 1997; Reiman et al., 1997; Royet et al., 2000) or the self regulation/inhibition of emotion (Davidson et al., 2000; Beauregard et al., 2001). Autistic children have an impaired ability to inhibit inappropriate responses (Minshew et al., 1999; Russell et al., 1991) and it has been proposed that this difficulty, rather than impaired theory of mind skills, results in their failure to pass strategic deception tasks (Russell et al., 1991).

In addition to emotion regulation, both neuroimaging (Courtney et al., 1996, 1998; Carlson et al., 1998; Thomas et al., 1999; Haxby et al., 2000) and transcranial magnetic stimulation (Oliveri et al., 2001) studies demonstrate evidence that the superior frontal gyrus (SFG)/sulcus are functionally associated with working memory tasks in humans. Although some studies have failed to find significant group differences between autistic subjects and controls on working memory tasks (Russell et al., 1996; Griffith et al., 1999; Ozonoff and Strayer, 2001), a variety of other studies demonstrate impairment in autistic subjects on tasks associated with working memory and other executive functions (Ozonoff et al., 1991; Hughes et al., 1994; Ozonoff and McEvoy, 1994; Bennetto et al., 1996; Minshew et al., 1999) Working memory has been associated with discourse (Carpenter and Just, 1989) and narrative (Grafman, 1989; Dennis, 1991) processes, and there is a large body of research demonstrating that autistic children have impaired conversational and narrative skills (Loveland and Tunali, 1991; Tager-Flusberg and Sullivan, 1995; Tager-Flusberg et al., 2001) as well as a restricted range of speech acts (Wetherby, 1986; Loveland et al., 1988).

Cortical areas that may be implicated in impaired language functioning include the Sylvian fissure (Leonard et al., 2001), as well as the left inferior frontal sulcus and superior temporal sulcus (Demonet et al., 1992; Shaywitz et al., 1995; Just et al., 1996; Friederici et al., 2000). Our findings demonstrate anterior shifting of all of these sulci, with differences ranging from 6 mm in the Sylvian fissure to 5 mm in STS and IFS. Recent studies using positron emission tomography (PET) and fMRI have shown that areas of the left inferior prefrontal cortex (LIPC) are activated during semantic functioning (Demb et al., 1995; Roskies et al., 1996; Klein et al., 1997; Paulesu et al., 1997; Wagner et al., 1997; Dapretto and Bookheimer, 1999). Moreover, it appears that the anterior/ventral region of the left inferior frontal gyrus (BA 47/10) may be specifically related to semantic processing, while posterior/dorsal regions of this gyrus (BAs 44 and 45) are activated during both semantic and phonological processing tasks (Shaywitz et al., 1995; Roskies et al., 1996; Poldrack et al., 1999; Paulesu et al., 1997). Fiez and Poldrack et al. (Fiez, 1997; Poldrack et al., 1999) review evidence supporting the hypothesis that the LIPC may play a role as a semantic executive system (Demb et al., 1995; Buckner and Petersen, 1996; Wagner et al., 1997), accessing and manipulating semantic representations, while the temporal cortex may be the primary region supporting the interpretation and storage of semantic knowledge representations (Damasio et al., 1996; Price et al., 1997). Thus, more severe disruptions of semantic processing are seen in subjects with temporal lobe lesions, while patients with lesions to the LIPC have milder impairment of semantic processing (Swick and Knight, 1996).

A variety of research establishes the importance of the relationship between language dysfunction and autistic difficulties. The level of receptive language abilities in autistic children is correlated with vocalization, gesture imitation and functional and symbolic play (Ungerer and Sigman, 1984; Paul et al., 1988); while expressive language levels in both autistic and language impaired preschoolers also correlate strongly with a range of social behaviors (Lord and Pickles, 1996). Our findings of abnormalities in cortical areas involved in working memory and semantic processing provide evidence for a potential neuroanatomical basis for these communication abnormalities in autism.

In addition to pragmatic difficulties, one of the cardinal features of autism is abnormality of eye gaze. Our findings provide evidence in the autistic subjects for alteration of cortical regions directly related to perception of eye gaze as well as facial recognition and perception of facial expression: superior temporal sulci and intraparietal sulci. A variety of research methodologies have demonstrated a role for the superior temporal sulcus in the processing of eye gaze direction (Perrett et al., 1992; Puce et al., 1998; Wicker et al., 1998; Puce et al., 1999; Haxby et al., 2002), facial expression (Fried et al., 1982; Ojemann et al., 1992; Kanwisher et al., 1997; Streit et al., 1999; Narumoto et al., 2001) and facial perception (Kanwisher et al., 1997; Halgren et al., 1999; Haxby et al., 1999; Hoffman and Haxby, 2000). Other studies show involvement of the intraparietal sulcus in eye gaze direction (Hoffman and Haxby, 2000) and in spatial perception and memory (Corbetta et al., 1993; Haxby et al., 1994; Nobre et al., 1997; Corbetta et al., 1998). These activities provide information necessary for social interactions including information about identity, mood, level of interest and direction of interest (Haxby et al., 2002). Furthermore, there is an apparently reflexive attentional response to perceived gaze direction (Driver et al., 1999; Langton and Bruce, 1999). Based on experiments demonstrating stronger IPS activity in response to averted than direct eye gaze, Hoffman and Haxby (Hoffman and Haxby, 2000) suggest that the reflexive shift of spatial attention in response to averted eye gaze may result from interactions between the STS (facial-responsive region) and IPS (spatial attention system).

Limitations of this study include a significant group difference in IQ although we selected for high functioning autistic subjects. We did not use IQ as a covariate in our analyses because this would remove variance associated with the illness. Studies (Bennetto et al., 1996; Spiker et al., 2002) demonstrate a clear association between severity of autistic symptoms and IQ. Although we eliminated any subjects with IQ < 70 for this report, in a separate analysis (not presented) we found that if subjects with IQs in the 50–60 range were included (n = 4), differences between groups were not changed appreciably in SFS or Sylvian fissure, but increased significantly in areas involved in perception of eye gaze (intraparietal sulcus) and facial identity (collateral sulcus). Additional studies with lower IQ normal control subjects are needed to further assess these initial findings.

In summary, we report widespread changes in cortical surface anatomy in subjects with autism, primarily in frontal and temporal regions. This is the first study to examine 3-D cortical sulcal patterns in children diagnosed with autism. These data corroborate previous findings of abnormalities in cortical gray matter volume in the inferior frontal gyrus in autistic subjects (Abell et al., 1999); and provide further evidence for anatomical abnormalities in regions that have previously shown functional abnormalities in autistic subjects. In particular, we present evidence for delayed maturation of the frontal lobes in autism in agreement with a previous study by Zilbovicious et al. (Zilbovicious et al., 1995), and although our findings in the collateral sulcus require further study, this is the first report of anatomical changes in this region in autistic subjects, a region with demonstrated functional abnormalities during facial processing tasks. Further studies of both sulcal anatomy and complexity in larger subject groups including a longitudinal component will help to clarify these results and to assess their relationship to normal development.

Notes

This work was supported by the National Institute of Mental Health (AKO8-MH01385 1P01 HD35482-01). The authors wish to thank all the families who so graciously participated in this research. We also wish to thank Gwen Gordon and Rochelle Noel for their expert assistance with statistics and manuscript preparation.

Address correspondence to Jennifer G. Levitt, UCLA Neuropsychiatric Institute, 760 Westwood Plaza, Los Angeles, CA 90024-1759, USA. Email: Jlevitt@mednet.ucla.edu.

Table 1

Coordinates of sulcal position in stereotaxic space

Sulcus Measure Autism (mm) Normal control (mm) P′ 
P′ is used for comparison of means adjusted for total brain volume and gender. Since there are 264 comparisons, we could expect ~13 of them to be significant by chance alone. Formal correction (e.g. Bonferroni) of P-values is infeasible given the large number of variables and small sample size; a concerned reader may wish to impose his/her own correction. 
Y represents the vertical axis or posterior/superior direction; Z represents the horizontal axis or anterior/posterior direction. 
Superior frontal Z Max R 63.43 56.21 <0.0001 
 Y Max R 67.59 59.85 0.0002 
 Z Max L 63.68 56.73 0.0003 
 Y Max L 67.50 59.28 0.0002 
Sylvian fissure Y Max R 25.68 19.31 0.0002 
 Z Min L 63.97 49.01 0.03 
Superior temporal body Y Max R 18.30 13.47 0.0006 
 Y Max L 17.94 13.72 0.02 
 Y Extent R 77.60 70.96 0.009 
 Y Extent L 77.35 70.81 0.025 
Inferior frontal Y Min L 14.51 8.52 0.0015 
 Y Max L 45.78 40.19 0.0024 
 Y Min R 14.18 10.78 0.037 
Olfactory Y Min R 25.49 18.55 0.002 
 Y Max R 53.60 48.69 0.01 
 Y Min L 25.56 17.51 0.002 
 Y Max L 53.18 48.36 0.013 
Intraparietal Z Max R 56.84 51.66 0.027 
 Z Max L 55.29 49.30 0.006 
Collateral Z Max R −3.99 −7.78 0.016 
 Z Max L −4.33 −7.70 0.041 
Superior temporal ascending Z Max R 48.49 41.76 0.024 
 Z Max L 45.04 39.33 0.028 
 Z Extent L 32.11 27.12 0.029 
Sulcus Measure Autism (mm) Normal control (mm) P′ 
P′ is used for comparison of means adjusted for total brain volume and gender. Since there are 264 comparisons, we could expect ~13 of them to be significant by chance alone. Formal correction (e.g. Bonferroni) of P-values is infeasible given the large number of variables and small sample size; a concerned reader may wish to impose his/her own correction. 
Y represents the vertical axis or posterior/superior direction; Z represents the horizontal axis or anterior/posterior direction. 
Superior frontal Z Max R 63.43 56.21 <0.0001 
 Y Max R 67.59 59.85 0.0002 
 Z Max L 63.68 56.73 0.0003 
 Y Max L 67.50 59.28 0.0002 
Sylvian fissure Y Max R 25.68 19.31 0.0002 
 Z Min L 63.97 49.01 0.03 
Superior temporal body Y Max R 18.30 13.47 0.0006 
 Y Max L 17.94 13.72 0.02 
 Y Extent R 77.60 70.96 0.009 
 Y Extent L 77.35 70.81 0.025 
Inferior frontal Y Min L 14.51 8.52 0.0015 
 Y Max L 45.78 40.19 0.0024 
 Y Min R 14.18 10.78 0.037 
Olfactory Y Min R 25.49 18.55 0.002 
 Y Max R 53.60 48.69 0.01 
 Y Min L 25.56 17.51 0.002 
 Y Max L 53.18 48.36 0.013 
Intraparietal Z Max R 56.84 51.66 0.027 
 Z Max L 55.29 49.30 0.006 
Collateral Z Max R −3.99 −7.78 0.016 
 Z Max L −4.33 −7.70 0.041 
Superior temporal ascending Z Max R 48.49 41.76 0.024 
 Z Max L 45.04 39.33 0.028 
 Z Extent L 32.11 27.12 0.029 
Figure 1.

Sample drawings of the 11 cortical sulci traced in each hemisphere.

Figure 1.

Sample drawings of the 11 cortical sulci traced in each hemisphere.

Figure 2.

Three-dimensional cortical sulcal variability between autistic and normal group. Variability across the cortical sulci mapped in each hemisphere is shown after differences in brain orientation and size were removed. Significant variability is seen in the superior frontal sulci bilaterally (4–8 mm, red), Sylvian fissure on the right (6 mm) and left inferior frontal sulcus (6 mm).

Figure 2.

Three-dimensional cortical sulcal variability between autistic and normal group. Variability across the cortical sulci mapped in each hemisphere is shown after differences in brain orientation and size were removed. Significant variability is seen in the superior frontal sulci bilaterally (4–8 mm, red), Sylvian fissure on the right (6 mm) and left inferior frontal sulcus (6 mm).

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