Research aimed at uncovering the pathogenesis of autism spectrum disorders (ASD), and potentially leading to rational approaches to prevention or treatment, is of great importance. In this study, researchers will use novel neuroimaging techniques to identify biomarkers of risk for autism. The discovery of reliable biomarkers will aid in the identification of individuals with ASD as well as those who will subsequently develop or are already developing subtle signs of ASD. In addition, biomarkers could serve to identify early biological risk factors for ASD, ultimately helping to prevent the development of the disorder in people at risk or reduce the degree of severity in those affected. Biomarkers related to increased brain volume derived from structural magnetic resonance imaging (MRI) have revealed differences between individuals with ASD and typically-developing controls. Functional MRI (fMRI) differences have also been found (for instance, using tasks related to face identity and facial expression). Recent evidence suggests altered brain connectivity from both structural and functional measures in ASD. However, all of these alterations are quite subtle, and the findings have been inconsistent. The researchers hypothesize that the combined use of anatomic and diffusion information will provide more sensitive and robust biomarkers for ASD. The researchers will develop a unique mathematical approach that will estimate three functionally-connected subnetworks in the brain related to ASD and a motion perception task. The strategy will first be applied to typically developing children to confirm its utility and identify potential biomarkers. Then, the researchers will demonstrate the effectiveness of the new biomarkers by examining the signal change and connectivity parameters derived from three ASD-related functional subnetworks. The goal is to identify specific biological measures that can stratify three subject groups: children with ASD, unaffected siblings of children with ASD, and typically developing children. This project will lead to sensitive methods for measuring and characterizing autism spectrum disorders from multimodality magnetic resonance images of connectivity in the human brain. Evaluation of these measures will advance our understanding of the development, progression and heterogeneity of these disorders potentially leading to rational treatment approaches.