Search tips
Search criteria 


Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Biol Psychiatry. Author manuscript; available in PMC 2012 March 12.
Published in final edited form as:
PMCID: PMC3299337

Total Brain Volume and Corpus Callosum Size in Medication-Naïve Adolescents and Young Adults with Autism Spectrum Disorder



Increased total brain volume (TBV) has been reported for children with autism spectrum disorder (ASD) but studies in older ASD subjects have been contradictory. Similarly, studies of corpus callosum (CC) area in ASD differ with regard to inclusion criteria, age, and IQ.


In the present study, TBV, gray matter (GM), and white matter (WM) volume as well as midsagittal CC area were compared between 15 medication-naïve, high-functioning adolescent and young adult ASD subjects and 15 healthy control individuals, and correlations with visuomotor coordination and imitation abilities were explored. In addition, computational surface-based methods were implemented to encode callosal thickness at high spatial resolution.


Total brain volume, GM, and WM were increased and CC area was decreased in ASD subjects, a finding that was predominantly due to ASD subjects with lower IQ. Positive correlations of IQ with volume measures were observed only in control subjects. Autism spectrum disorder subjects showed reduced thickness in the posterior part of the CC. White matter volume showed a trend for negative correlation with dynamic balance and imitation abilities across groups.


This study replicates previous structural magnetic resonance imaging (MRI) findings in ASD, emphasizes the role of IQ differences, and adds some evidence for functional implications of structural findings.

Keywords: Autism, corpus callosum, motor abilities, voxel-based morphometry

Autism spectrum disorders (ASDs) are characterized by quantitative impairments in social interaction and communication, as well as restrictive, stereotyped, repetitive behaviors and interests. Autism spectrum disorders are predominantly genetically determined, and affected individuals show early abnormalities in brain development, resulting in specific anatomical findings as outlined below.

Total brain volume (TBV) has been observed to be increased in children with ASD in the majority of studies (1). This is in accordance with reports of accelerated head growth in the first 2 years of life, resulting in high rates of macrocephaly in ASD (2). Some studies also reported increased TBV in adolescents and adults with ASD (3) but others disputed this finding and reported a normalization of TBV (4). It is also unclear whether the reported increase in TBV might be due to an increase of cortical and subcortical gray matter (GM) volume (3), an increase in subcortical white matter (WM) volume (5), or an increase in both GM and WM volume.

The increase in TBV is in line with the hypothesis of reduced connectivity in ASD. More specifically, accelerated brain growth and increased brain size have been hypothesized to lead to reduced interhemispheric connectivity and higher local specialization to optimize neuronal computational speed (6). This reduced interhemispheric connectivity might result in reduced corpus callosum (CC) area, which was observed in ASD subjects (1). Again, studies of CC area and its subregions in ASD differ in terms of inclusion criteria, age, sex, and IQ. Studies that controlled for TBV and IQ differences between groups in ASD individuals observed decreased total CC size, as well as smaller posterior CC subregions (7), smaller CC body (8), and/or smaller anterior subregions of the CC (9). Another study, which did not control for TBV and IQ differences, did not observe differences in CC area between high-functioning autistic and control children (5). Results of a recent diffusion tensor imaging (DTI) study underscore the impact of IQ differences on CC morphology, as CC area was significantly smaller and radial diffusivity was strongly increased in ASD individuals with low performance IQ (10). Most studies of the size of the CC and its subregions in ASD samples implemented the Witelson parcellation scheme. As this parcellation approach arbitrarily subdivides the CC into seven regions according to its maximal length, it might not recognize subtle regional differences. Also, results might be affected by local variability in callosal shape.

In the present study, we compared TBV, GM, and WM, measured by voxel-based morphometry (VBM), as well as midsagittal CC area, studied by a region-of-interest based approach, between medication-naïve, high-functioning adolescent and young adult ASD subjects and healthy control individuals, group matched for age and sex. We expected an increase in TBV, GM, and WM and a decrease of CC size in ASD individuals. In addition, correlation patterns of visuomotor coordination and imitation abilities with TBV, GM, WM, and CC area were explored. Finally, we applied computational surface-based methods to encode callosal thickness at high spatial resolution without relying on callosal parcellation (11) to replicate findings of regional differences in CC morphology in ASD subjects.

Methods and Materials

Thirteen male and 2 female subjects with autism spectrum disorder (mean age 17.5 years, SD 3.5 years) and 13 male and 2 female age-matched control subjects (mean age 18.6 years, SD 1.1 years) with IQ > 70 were assessed. After complete description of the study, informed consent was obtained from all participants and/or their parents. The study design was approved by the local ethical committee (Ethikkommission der Ärztekammer des Saarlandes). Detailed inclusion and exclusion criteria, methods to assess visuomotor coordination and imitation abilities, magnetic resonance imaging (MRI) data acquisition, MRI image preprocessing, CC area and thickness measurements, and statistical analysis methods are reported in Supplement 1.


Descriptive data of the sample are shown in Table 1. With adjustment for IQ and interaction of IQ*status, TBV, GM, and WM were larger in ASD than in control individuals (Table 2), predominantly due to individuals with low IQ (Table 1 in Supplement 2). The interaction effect of IQ*status on TBV, GM, and WM indicates contrasting correlations of IQ with TBV, GM, and WM in case and control individuals. While IQ was not associated with TBV, GM, or WM in ASD subjects, control individuals showed strong positive correlations (Table 2, Supplements 3–5). Midsagittal CC area was lower in ASD individuals when adjusted for WM, IQ, and for interaction terms WM*status and IQ*status. A positive correlation of WM with CC area was only observed in control but not in ASD individuals (Table 3; Table 2 in Supplement 2). Regional differences in CC morphology between ASD and control subjects were observed in the posterior part of the CC, with control individuals showing a significantly higher thickness than ASD individuals (Figure 1). White matter showed a trend for a negative association with dynamic balance and hand-finger imitation abilities across all groups (Table 3 in Supplement 2).

Figure 1
Differences of callosal thickness between groups. Illustrated are regions of significantly increased callosal thickness in control subjects compared with ASD individuals (CTL > ASD). Analyses of covariance (ANCOVA) were performed with adjustment ...
Table 1
Descriptive Data
Table 2
Total Brain, Gray, and White Matter Volumes in Autism Spectrum Disorder and Control Subjects Adjusted for IQ
Table 3
Corpus Callosum Area in Autism Spectrum Disorder and Control Subjects Adjusted for WM and IQ


In this study, TBV, GM, WM, and CC area were compared between 15 adolescents and young adults with ASD and 15 healthy control subjects, matched for gender and age. Our findings corroborate previous reports of an enlargement of TBV in adolescents and young adults with ASD (1), especially in individuals with average and below average IQ (70–110). The current analyses suggest that increases in TBV are due to increases in both GM and WM. Given that subjects in our study were medication-naïve, the observed volume increases cannot be attributed to treatment effects (12).

Our findings emphasize the strong impact of IQ differences on study outcomes. For example, positive correlations of IQ with TBV, GM, and WM were only observed in control but not in ASD individuals. Increased TBV, GM, and WM were predominantly observed in ASD individuals with IQ equal to or lower than the median IQ in our study. In a previous study on individuals with low-functioning autism (LFA), high-functioning autism (HFA), and Asperger syndrome (AS), only LFA and HFA subjects showed increased GM, whereas AS subjects did not show increased GM. Given that AS individuals showed significantly higher IQ scores than HFA in that study (13), findings might have been driven by IQ differences between groups. Gray matter and WM increase might be due to an overproduction of neurons, glia, or astrocytes; abnormal myelination; and/or decreased neuronal elimination (pruning). In one study, active neuroinflammatory processes have been shown to exist in the WM, cortex, and cerebellum of patients with autism (14). Neuropathological studies have reported abnormal neocortical minicolumns in 4- to 25-year-old individuals with ASD (15), possibly resulting in increased GM and WM. Increased WM in our study showed a trend for an association with reduced dynamic balance and hand-finger imitation abilities across groups. A recent study reported a positive correlation of neurological subtle signs as indicators of motor impairment with local WM in the primary motor and premotor cortices of 8- to 12-year-old children with ASD (16). Therefore, either local or global WM enlargement might contribute to motor and imitation impairment in ASD.

Corpus callosum area was smaller in ASD, likely due to individuals with high IQ and large WM. However, due to low sample size, the unadjusted post hoc comparison has to be viewed with caution. Reduced CC thickness was observed in the isthmus and anterior part of the splenium. Our findings are well in line with previous studies in age-, gender-, and IQ-matched samples (79). The CC isthmus and anterior part of the splenium connect primary somatosensory, temporal, and posterior parietal fibers (17). Several functional and structural MRI studies have reported volumetric changes and altered function of right and left temporal and parietal regions in ASD (7,18). Reduction in CC thickness either might be the result of these structural and functional findings or might cause some of the functional differences between ASD and control individuals. Previous studies indicated CC hypoplasia, but not atrophy, and suggested a reduction in the number of axonal fibers traversing the CC (19,20). A recent DTI study reported reduced CC fractional anisotropy and increased mean diffusivity in ASD individuals, also indicative of CC microstructure changes (10).

Our study had several limitations. For example, the sample size was relatively small, so post hoc tests comparing ASD and control individuals with high/low IQ have to be viewed with caution and need to be replicated in a larger sample. Also, groups were not fully matched with regard to IQ measures. Similar to prior structural MRI studies, our study had a cross-sectional design, which does not allow conclusions about causality. Further structural MRI studies should implement a longitudinal approach to compare brain development in ASD and control children.

In conclusion, we replicated findings of increased TBV, GM, and WM in adolescent and adult ASD individuals and described the strong influence of IQ on these anatomical measures. Finally, CC area and posterior thickness were reduced, replicating previous studies.

Supplementary Material

Supplementary Data


This study was financially supported by the Saarland University with a Grant to CMF (T 204 21 03–01). Parts of this work were also supported by a Young Investigator Grant to CKo by the Interdisciplinary Center for Clinical Research Münster (IZKF FG 4), by the National Institutes of Health (NIH) through the NIH Roadmap for Medical Research Grants U54 RR021813 entitled Center for Computational Biology (CCB), and by the NIH Grants P41 RR013642 and M01 RR000865.

We thank the participating individuals for taking part in the study.


The authors report no biomedical financial interests or potential conflicts of interest.

Supplementary material cited in this article is available online.


1. Stanfield AC, McIntosh AM, Spencer MD, Philip R, Gaur S, Lawrie SM. Towards a neuroanatomy of autism: A systematic review and meta-analysis of structural magnetic resonance imaging studies. Eur Psychiatry. 2008;23:289 –299. [PubMed]
2. Courchesne E, Carper R, Akshoomoff N. Evidence of brain overgrowth in the first year of life in autism. JAMA. 2003;290:337–344. [PubMed]
3. Hazlett HC, Poe MD, Gerig G, Smith RG, Piven J. Cortical gray and white brain tissue volume in adolescents and adults with autism. Biol Psychiatry. 2006;59:1–6. [PubMed]
4. Redcay E, Courchesne E. When is the brain enlarged in autism? A meta-analysis of all brain size reports. Biol Psychiatry. 2005;58:1–9. [PubMed]
5. Herbert MR, Ziegler DA, Makris N, Filipek PA, Kemper TL, Normandin JJ, et al. Localization of white matter volume increase in autism and developmental language disorder. Ann Neurol. 2004;55:530–540. [PubMed]
6. Ringo JL. Neuronal interconnection as a function of brain size. Brain Behav Evol. 1991;38:1–6. [PubMed]
7. Waiter GD, Williams JH, Murray AD, Gilchrist A, Perrett DI, Whiten A. Structural white matter deficits in high-functioning individuals with autistic spectrum disorder: A voxel-based investigation. Neuroimage. 2005;24:455–461. [PubMed]
8. Piven J, Bailey J, Ranson BJ, Arndt S. An MRI study of the corpus callosum in autism. Am J Psychiatry. 1997;154:1051–1056. [PubMed]
9. Just MA, Cherkassky VL, Keller TA, Kana RK, Minshew NJ. Functional and anatomical cortical underconnectivity in autism: Evidence from an fMRI study of an executive function task and corpus callosum morphometry. Cereb Cortex. 2007;17:951–961. [PMC free article] [PubMed]
10. Alexander AL, Lee JE, Lazar M, Boudos R, DuBray MB, Oakes TR, et al. Diffusion tensor imaging of the corpus callosum in autism. Neuroimage. 2007;34:61–73. [PubMed]
11. Luders E, Narr KL, Zaidel E, Thompson PM, Toga AW. Gender effects on callosal thickness in scaled and unscaled space. Neuroreport. 2006;17:1103–1106. [PubMed]
12. Phillips ML, Travis MJ, Fagiolini A, Kupfer DJ. Medication effects in neuroimaging studies of bipolar disorder. Am J Psychiatry. 2008;165:313–320. [PMC free article] [PubMed]
13. Lotspeich LJ, Kwon H, Schumann CM, Fryer SL, Goodlin-Jones BL, Buonocore MH, et al. Investigation of neuroanatomical differences between autism and Asperger syndrome. Arch Gen Psychiatry. 2004;61:291–298. [PubMed]
14. 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. [PubMed]
15. Casanova MF, van Kooten IA, Switala AE, van Engeland H, Heinsen H, Steinbusch HW, et al. Minicolumnar abnormalities in autism. Acta Neuropathol. 2006;112:287–303. [PubMed]
16. Mostofsky SH, Burgess MP, Gidley Larson JC. Increased motor cortex white matter volume predicts motor impairment in autism. Brain. 2007;130:2117–2122. [PubMed]
17. Zarei M, Johansen-Berg H, Smith S, Ciccarelli O, Thompson AJ, Matthews PM. Functional anatomy of interhemispheric cortical connections in the human brain. J Anat. 2006;209:311–320. [PubMed]
18. Freitag CM, Konrad C, Haberlen M, Kleser C, von Gontard A, Reith W, et al. Perception of biological motion in autism spectrum disorders. Neuropsychologia. 2008;46:1480 –1494. [PubMed]
19. Chung MK, Dalton KM, Alexander AL, Davidson RJ. Less white matter concentration in autism: 2D voxel-based morphometry. Neuroimage. 2004;23:242–251. [PubMed]
20. Vidal CN, Nicolson R, DeVito TJ, Hayashi KM, Geaga JA, Drost DJ, et al. Mapping corpus callosum deficits in autism: An index of aberrant cortical connectivity. Biol Psychiatry. 2006;60:218 –225. [PubMed]