Individual Differences in Functional Brain Connectivity Predict Social Attention Abilities and Attention Switching Autistic Traits

Brindley, Samantha, Psychology - Graduate School of Arts and Sciences, University of Virginia
Morris, James, Psychology, University of Virginia

The ability to attend to relevant social information in the environment, referred to as social attention, is necessary for successful social functioning. Individuals with autism typically exhibit disordered social attention processes and also experience difficulties during social interactions. Within a neurotypical population, the degree to which social stimuli automatically capture attention is highly variable, as is the degree of subclinical autistic traits that individuals possess. Here, we investigated the neural systems underlying the wide range of individual variability in social attention abilities in a neurotypical sample. Participants underwent fMRI while performing a one-back matching social attention task involving either selective attention to faces or selective attention to houses in composite images. We found that whole-brain functional connectivity models reliably predicted social attention task performance when participants selectively attended to faces, but not when participants selectively attended to houses and ignored salient face stimuli. We also demonstrated that connectivity strength while selectively attending to faces predicted the subclinical autistic trait of poor attention switching abilities. While network connectivity included numerous regions distributed throughout the brain, the cerebellum and the prefrontal cortex emerged as particularly predictive regions involved in the automaticity of social cognitive processes and attentional control, respectively. These results have implications for our basic understanding of the neural systems underlying individual differences in social attention abilities in a neurotypical population, which are related to varying levels of autistic attention switching traits. This research provides a framework for the reliable predictive modeling of individual differences in social cognitive behavior.

MA (Master of Arts)
social attention, functional connectivity, attention switching, autistic traits, individual differences
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