Abstract

Autism is a disorder of neurodevelopment resulting in pervasive abnormalities in social interaction and communication, repetitive behaviours and restricted interests. There is evidence for functional abnormalities and metabolic dysconnectivity in 'social brain' circuitry in this condition, but its structural basis has proved difficult to establish reliably. Explanations for this include replication difficulties inherent in 'region of interest' approaches usually adopted, and variable inclusion criteria for subjects across the autism spectrum. Moreover, despite a consensus that autism probably affects widely distributed brain regions, the issue of anatomical connectivity has received little attention. Therefore, we planned a fully automated voxel-based whole brain volumetric analysis in children with autism and normal IQ. We predicted that brain structural changes would be similar to those previously shown in adults with autism spectrum disorder and that a correlation analysis would suggest structural dysconnectivity. We included 17 stringently diagnosed children with autism and 17 age-matched controls. All children had IQ >80. Using Brain Activation and Morphological Mapping (BAMM) software, we measured global brain and tissue class volumes and mapped regional grey and white matter differences across the whole brain. With the expectation that volumes of interconnected regions correlate positively, we carried out a preliminary exploration of 'connectivity' in autism by comparing the nature of inter-regional grey matter volume correlations with control. Children with autism had a significant reduction in total grey matter volume and significant increase in CSF volume. They had significant localized grey matter reductions within fronto-striatal and parietal networks similar to findings in our previous study, and additional decreases in ventral and superior temporal grey matter. White matter was reduced in the cerebellum, left internal capsule and fornices. Correlation analysis revealed significantly more numerous and more positive grey matter volumetric correlations in controls compared with children with autism. Thus, using similar diagnostic criteria and image analysis methods in otherwise healthy populations with an autistic spectrum disorder from different countries, cultures and age groups, we report a number of consistent findings. Taken together, our data suggest abnormalities in the anatomy and connectivity of limbic-striatal 'social' brain systems which may contribute to the brain metabolic differences and behavioural phenotype in autism.