Functional connectomics associated with ASD

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Abstract This project will image 150 children (~ aged 12) with and without autism spectrum disorder to reveal the changes in functional brain organization that relate to autism severity and associated behavioral measures. The children will represent 3 distinct groups of 50 kids each (high risk children with autism, high risk siblings without autism and low risk healthy controls) and we will contrast these groups to understand the major functional network changes associated with autism. We will also develop connectome based predictive models to relate individual functional connectivity profiles to autism scores (using ADOS-2 social affect as the primary measure and RRB as a secondary measure) and examine the extent to which the models localize to specific networks including the executive control, the salience, and the default mode networks. The connectivity input data will be of unprecedented quality and extent (at least 20minutes of resting-state data providing highly reliable single subject data). In addition to the resting-state, we will include data collected during continuous performance tasks (an attention task: gradCPT and a selective social attention task previously characterized with eye-tracking data). Sex differences will be of specific interest in understanding network changes with autism severity. We will also identify the altered networks associated with ASD and provide these networks for exploratory analysis in project 1 (infants) and project 4 (fetal brains) to examine the extent to which these networks are altered early in development. The neural characterization performed in project 3 will be on a subset of the subjects studied in this project and thus we will have direct neural characteristics to relate to the connectivity changes we will quantify. This will be one of the first times neuronal structural features have been related to macroscopic connectivity data.