This past year we have continued to evaluate the behavioral consequences, and associated neural characteristics, of Autism Spectrum Disorders (ASD). The presence of intense and idiosyncratic interests and hobbies has long been recognized as one of the defining clinical features of ASD. We documented this important clinical characteristic in our high-functioning group of ASD subjects, relative to age and IQ matched control subjects. However, contrary to commonly held beliefs, the interests of our subjects were not abnormally restricted in number. Rather, it was the intensity with which they pursued these interests and hobbies, rather than their total number, that was most strongly related to other ASD symptoms such repetitive behaviors and certain aspects of social functioning. Using MRI, our structural brain imaging studies have continued to document abnormally thin cortex, as well as increased cortical folding or gyrification, in our ASD subjects relative to matched control subjects. These findings are consistent with an ever-growing literature on cortical atypicalities in ASD. We have also continued to document the functional consequences of these atypicalities. In a series of studies using functional MRI, we found that the neural circuitry associated with perceiving and understanding social interactions showed a lack of category-specificity in ASD. Specifically, brain regions that typically respond when viewing social, relative to mechanical interactions, responded equally strong to both types of interactions in our high-functioning ASD individuals. One interpretation of this finding is that ASD may be characterized by deficient neural connectivity between brain regions comprising specific processing networks or circuits. We have obtained additional support of this possibility from studies evaluating higher-order cognitive abilities such verbal fluency, as well as study of lower-order functions such as motion perception. Thus, communication between the different brain regions that comprise a processing network may be compromised in autism and related developmental disorders. We have also taken advantage of the ability of fMRI to record very slowly fluctuating neural signals during task-free or resting states to provide a surrogate measure of the strength of the connections between spatially distinct brain regions comprising specific processing circuits. These resting-state data have proven to be particularly useful for comparing clinical patient groups because they are easy to obtain and are not subject to group differences in performance that can confound the interpretation of task-based neuroimaging data. However, the analysis of these data is fraught with a problems and pitfalls that have not been fully appreciated or explored. To help remedy this situation, we have published several papers that describe these difficulties in detail and offer potential solutions.
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