The diagnosis of autism spectrum disorder (ASD) is currently based on behavior and developmental history of the child. With the development of advanced forms of diffusion-weighted magnetic resonance imaging (DW-MRI), it is expected that imaging will elucidate pathology-induced and neuro-developmental changes in white matter (WM) architecture, and provide diagnostic and predictive anatomical biomarkers. This project aims to develop computational methods for analyzing diffusion MRI data fitted with higher order models that uniquely characterize complex white matter regions affected in autism spectrum disorder (ASD). These well validated methods will be applied to the analysis of an ASD population to produce a quantification of abnormalities in brain connectivity and white matter integrity. Correlation with clinical diagnostic measures will provide an image-based link to deficits observed in autism such as impaired social interactions, language and communication, and restricted and repetitive behaviors, and hence aid in prognosis and in studying disease progression.