Investigating neural predictors of real-world social attention in autism during naturalistic social interactions

About This Grant

Project Summary The field of autism research lacks objective measures of social attention that reflect how autistic people look at real human faces. Altered social perception in autism, including delayed neural response to faces and reduced social attention, is almost exclusively understood in relation to static face images in computer-based settings. For this reason, our current understanding of social attention and its putative neural mechanisms lacks ecological validity and is dissociated from the context in which clinical differences in autism are observed. This reliance on images instead of real faces may reduce sensitivity to detect and may even mask real differences in social attention between autistic and neurotypical individuals, complicating elucidation of underlying neural mechanisms and parsing of clinical heterogeneity. In this proposal, we address these limitations of prior work by using ambulatory eye-tracking technology to investigate visual attention during a novel naturalistic interpersonal interaction task developed by the PI (the Ecologically Valid Observation of Looking and Visual Engagement; EVOLVE); in this way, we measure visual attention to real human faces (and its neural predictors) during actual social interactions. We apply a powerful within-person design to (a) compare this innovative and ecologically valid approach to well-studied, conventional computer-based assays of visual attention (i.e., the Autism Biomarkers Consortium for Clinical Trials (ABC-CT) and (b) evaluate relationships to neural mechanisms indexed with conventional EEG (i.e., the ABC-CT faces N170 paradigm). Participants will include 60 6-11-year- old autistic and 60 matched neurotypical children. We hypothesize that, relative to computer-based assays, the bonafide social signals in this naturalistic approach will amplify signal and improve detection of autistic differences in social attention and relationships to the clinical phenotype. Knowledge from the proposed study will directly inform theoretical frameworks for understanding visual and neural processing of social information in ways true to actual autistic experience and will significantly advance the translatability of neural markers of autism in ways relevant to real world behaviors and clinically meaningful outcomes. This innovative approach has potential to set methodological precedent for using these more naturalistic technologies to better understand social behaviors in autism and other neuropsychiatric conditions more broadly.