Increased brain volume in autism appears to be driven mainly by an unexplained white matter enlargement, and we have reported a similar phenomenon in developmental language disorder (DLD). Localization of this enlargement would strongly guide research into its cause, tissue basis, and functional implications. We utilized a white matter parcellation technique that divides cerebral white matter into an outer zone containing the radiate compartment and an inner zone containing sagittal and bridging system compartments. In both high-functioning autism and DLD, enlargement localized to the radiate white matter (all lobes in autism, all but parietal in DLD), whereas inner zone white matter compartments showed no volume differences from controls. Furthermore, in both autism and DLD, later or longer-myelinating regions showed greater volume increases over controls. Neither group showed cerebral cortex, corpus callosum, or internal capsule volume differences from control. Radiate white matter myelinates later than deep white matter; this pattern of enlargement thus is consistent with striking postnatal head circumference percentile increases reported in autism. These findings suggest an ongoing postnatal process in both autism and DLD that is probably intrinsic to white matter, that primarily affects intrahemispheric and corticocortical connections, and that places these two disorders on the same spectrum.

High-functioning autistic and normal school-age boys were compared using a whole-brain morphometric profile that includes both total brain volume and volumes of all major brain regions. We performed MRI-based morphometric analysis on the brains of 17 autistic and 15 control subjects, all male with normal intelligence, aged 7-11 years. Clinical neuroradiologists judged the brains of all subjects to be clinically normal. The entire brain was segmented into cerebrum, cerebellum, brainstem and ventricles. The cerebrum was subdivided into cerebral cortex, cerebral white matter, hippocampus-amygdala, caudate nucleus, globus pallidus plus putamen, and diencephalon (thalamus plus ventral diencephalon). Volumes were derived for each region and compared between groups both before and after adjustment for variation in total brain volume. Factor analysis was then used to group brain regions based on their intercorrelations. Volumes were significantly different between groups overall; and diencephalon, cerebral white matter, cerebellum and globus pallidus-putamen were significantly larger in the autistic group. Brain volumes were not significantly different overall after adjustment for total brain size, but this analysis approached significance and effect sizes and univariate comparisons remained notable for three regions, although not all in the same direction: cerebral white matter showed a trend towards being disproportionately larger in autistic boys, while cerebral cortex and hippocampus-amygdala showed trends toward being disproportionately smaller. Factor analysis of all brain region volumes yielded three factors, with central white matter grouping alone, and with cerebral cortex and hippocampus-amygdala grouping separately from other grey matter regions. This morphometric profile of the autistic brain suggests that there is an overall increase in brain volumes compared with controls. Additionally, results suggest that there may be differential effects driving white matter to be larger and cerebral cortex and hippocampus-amygdala to be relatively smaller in the autistic than in the typically developing brain. The cause of this apparent dissociation of cerebral cortical regions from subcortical regions and of cortical white from grey matter is unknown, and merits further investigation.

We report a whole-brain MRI morphometric survey of asymmetry in children with high-functioning autism and with developmental language disorder (DLD). Subjects included 46 boys of normal intelligence aged 5.7-11.3 years (16 autistic, 15 DLD, 15 controls). Imaging analysis included grey-white segmentation and cortical parcellation. Asymmetry was assessed at a series of nested levels. We found that asymmetries were masked with larger units of analysis but progressively more apparent with smaller units, and that within the cerebral cortex the differences were greatest in higher-order association cortex. The larger units of analysis, including the cerebral hemispheres, the major grey and white matter structures and the cortical lobes, showed no asymmetries in autism or DLD and few asymmetries in controls. However, at the level of cortical parcellation units, autism and DLD showed more asymmetry than controls. They had a greater aggregate volume of significantly asymmetrical cortical parcellation units (leftward plus rightward), as well as a substantially larger aggregate volume of right-asymmetrical cortex in DLD and autism than in controls; this rightward bias was more pronounced in autism than in DLD. DLD, but not autism, showed a small but significant loss of leftward asymmetry compared with controls. Right : left ratios were reversed, autism and DLD having twice as much right- as left-asymmetrical cortex, while the reverse was found in the control sample. Asymmetry differences between groups were most significant in the higher-order association areas. Autism and DLD were much more similar to each other in patterns of asymmetry throughout the cerebral cortex than either was to controls; this similarity suggests systematic and related alterations rather than random neural systems alterations. We review these findings in relation to previously reported volumetric features in these two samples of brains, including increased total brain and white matter volumes and lack of increase in the size of the corpus callosum. Larger brain volume has previously been associated with increased lateralization. The sizeable right-asymmetry increase reported here may be a consequence of early abnormal brain growth trajectories in these disorders, while higher-order association areas may be most vulnerable to connectivity abnormalities associated with white matter increases.

Autism is a neurodevelopmental disorder affecting cognitive, language, and social functioning. Although language and social communication abnormalities are characteristic, prior structural imaging studies have not examined languagerelated cortex in autistic and control subjects. Subjects included 16 boys with autism (aged 7-11 years), with nonverbal IQ greater than 80, and 15 age-and handedness-matched controls. Magnetic resonance brain images were segmented into gray and white matter; cerebral cortex was parcellated into 48 gyral-based divisions per hemisphere. Asymmetry was assessed a priori in language-related inferior lateral frontal and posterior superior temporal regions and assessed post hoc in all regions to determine specificity of asymmetry abnormalities. Boys with autism had significant asymmetry reversal in frontal language-related cortex: 27% larger on the right in autism and 17% larger on the left in controls. Only one additional region had significant asymmetry differences on post hoc analysis: posterior temporal fusiform gyrus (more left-sided in autism), whereas adjacent fusiform gyrus and temporooccipital inferior temporal gyrus both approached significance (more right-sided in autism). These inferior temporal regions are involved in visual face processing. In boys with autism, language and social/face processing-related regions displayed abnormal asymmetry. These structural abnormalities may relate to language and social disturbances observed in autism.

Advances in magnetic resonance imaging (MRI) have contributed greatly to the study of neurodegenerative processes, psychiatric disorders, and normal human development, but the effect of such improvements on the reliability of downstream morphometric measures has not been extensively studied. We examined how MRI-derived neurostructural measures are affected by three technological advancements: parallel acceleration, increased spatial resolution, and the use of a high bandwidth multiecho sequence. Test-retest data were collected from 11 healthy participants during 2 imaging sessions occurring approximately 2 weeks apart. We acquired 4 T1-weighted MP-RAGE sequences during each session: a non-accelerated anisotropic sequence (MPR), a non-accelerated isotropic sequence (ISO), an accelerated isotropic sequence (ISH), and an accelerated isotropic high bandwidth multiecho sequence (MEM). Cortical thickness and volumetric measures were computed for each sequence to assess test-retest reliability and measurement bias. Reliability was extremely high for most measures and similar across imaging parameters. Significant measurement bias was observed, however, between MPR and all isotropic sequences for all cortical regions and some subcortical structures. These results suggest that these improvements in MRI acquisition technology do not compromise data reproducibility, but that consistency should be maintained in choosing imaging parameters for structural MRI studies.

Language deficits are among the core impairments of autism. We previously reported asymmetry reversal of frontal language cortex in boys with autism. Specific language impairment (SLI) and autism share similar language deficits and may share genetic links. This study evaluated asymmetry of frontal language cortex in a new, independent sample of right-handed boys, including a new sample of boys with autism and a group of boys with SLI. The boys with autism were divided into those with language impairment (ALI) and those with normal language ability (ALN). Subjects (righthanded, aged 6.2-13.4 years) included 22 boys with autism (16 ALI and 6 ALN), 9 boys with a history of or present SLI, and 11 normal controls. MRI brain scans were segmented into grey and white matter; then the cerebral cortex was parcellated into 48 gyral-based divisions per hemisphere. Group differences in volumetric asymmetry were predicted a priori in language-related regions in inferior lateral frontal (Broca's area) and posterior superior temporal cortex. Language impaired boys with autism and SLI both had significant reversal of asymmetry in frontal language-related cortex; larger on the right side in both groups of language impaired boys and larger on the left in both unimpaired language groups, strengthening a phenotypic link between ALI and SLI. Thus, we replicated the observation of reversed asymmetry in frontal language cortex reported previously in an independent autism sample, and observed similar reversal in boys with SLI, further strengthening a phenotypic link between SLI and a subgroup of autism. Linguistically unimpaired boys with autism had similar asymmetry compared with the control group, suggesting that Broca's area asymmetry reversal is related more to language impairment than specifically to autism diagnosis.

These findings suggest a relationship between amygdala volume reduction, alcohol craving, and prospective relapse into alcohol consumption.

Volumetric magnetic resonance imaging (MRI) brain data provide a valuable tool for detecting structural differences associated with various neurological and psychiatric disorders. Analysis of such data, however, is not always straightforward, and complications can arise when trying to determine which brain structures are “smaller” or “larger” in light of the high degree of individual variability across the population. Several statistical methods for adjusting for individual differences in overall cranial or brain size have been used in the literature, but critical differences exist between them. Using agreement among those methods as an indication of stronger support of a hypothesis is dangerous given that each requires a different set of assumptions be met. Here we examine the theoretical underpinnings of three of these adjustment methods (proportion, residual, and analysis of covariance) and apply them to a volumetric MRI data set. These three methods used for adjusting for brain size are specific cases of a generalized approach which we propose as a recommended modeling strategy. We assess the level of agreement among methods and provide graphical tools to assist researchers in determining how they differ in the types of relationships they can unmask, and provide a useful method by which researchers may tease out important relationships in volumetric MRI data. We conclude with the recommended procedure involving the use of graphical analyses to help uncover potential relationships the ROI volumes may have with head size and give a generalized modeling strategy by which researchers can make such adjustments that include as special cases the three commonly employed methods mentioned above.