Multimodel Assessment of Social Process Systems across Neurodevelopmental Disorders

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 DESCRIPTION (provided by applicant): Disruption of social process systems is a hallmark of multiple neurodevelopmental disorders, resulting in significant functional impairment for affected individuals and substantial public health costs. This project proposes to examine the relationship between social performance and Reception of Facial Communication (a subconstruct within the Social Communication construct of the RDoC Social Processes domain) across multiple levels of analysis, spanning self-report, behavior, and physiology. Dimensional measures of face and emotion perception and social communicative function will be collected in a transdiagnostic sample of 50 adults from each of three recruitment streams: (1) the Yale Child Study Center Developmental Disabilities Clinic and Autism Spectrum Disorder (ASD) Research Program; (2) the Yale Psychiatry Department Specialized Treatment for Early Psychosis (STEP) Clinic and ongoing schizophrenia spectrum disorders (SZS) research program; (3) community controls presenting without clinical impairment in social communication. Though currently classified by separate diagnostic taxonomies, ASD and SZS exhibit shared social dysfunction and overlapping atypicalities in self-reported social characteristics (e.g., social motivation and engagement), behavior (e.g., scanning patterns to human faces, face recognition, and emotional expression deficits), and physiology (e.g., electrophysiological indices of face and emotion perception ). These findings suggest commonalities in the underlying neural processes affected in these disorders and emphasize the import of studying social dysfunction by organizing dimensions that cut across traditional diagnostic categories. This research utilizes a novel experimental paradigm that combines high-speed eye-tracking (ET; to measure where a person looks on a computer screen) and electroencephalographic recording (EEG; to measure brain response) to enable simulation of social interactions by animating on-screen faces that respond to the participant's eye gaze. We use dynamic, computer-generated, highly realistic faces that respond to the gaze of participants by "looking back" or making a facial expression. Across experiments, we relate continuous indices of social ability to variability in ET and EEG measures. Preliminary data demonstrate the viability of this innovative approach and reveal that both gaze patterns and neural response to interactive faces are associated with social functioning across the clinical and non-clinical range. Our innovative approach will advance understanding of the brain basis of social dysfunction in neurodevelopmental disorders by studying social perception in a naturalistic, interactive context. This research will lead to new ways of classifying mental disorders based on dimensions of observable behavior and neurobiological measures. It offers significant clinical translational benefits, including identifyng therapeutic targets, developing biologically-based predictors of treatment response, creating new treatment approaches, and exploring new markers to parse heterogeneity and more effectively conceptualize social processes affected across neurodevelopmental disorders.