Individuals with autism spectrum disorder (ASD) experience profound difficulty in social interactions. Problems maintaining eye contact, or shared gaze, emerge early in life and persist throughout development. The social challenges experienced by people with ASD are most evident in dynamic, interactive contexts~ however, most brain research in ASD has studied neural responses to social information in less realistic contexts, such as passively viewing static faces on a computer monitor. In the curren study, we propose to combine high-speed eye-tracking (ET~ to measure where a person looks on a computer screen) and electroencephalographic recording (EEG~ to measure brain response). Integration of these methods enables simulation of social interactions y animating on-screen faces that respond to the participant's eye gaze. In this way, we study interactions that, as in real life, are controlled by eye contact rather than a keyboard or computer device. We use computer-generated, highly realistic faces that respond to the gaze of participants by """"""""looking back"""""""" or making a facial expression. In three experiments, we will examine patterns of visual attention and associated brain response in ASD and typically developing counterparts while viewing (a) static faces, (b) interactive faces that respond to the viewer's gaze with reciprocated or averted eye contact, and (c) interactive faces hat respond to the viewer's gaze with a facial expression, such as a smile. This project will also collect information about social and communicative behavior to examine the relationship between neural response to shared gaze and social function. Preliminary data demonstrate the viability of this innovative approach and reveal a novel EEG marker for reciprocal eye contact that is attenuated in ASD and related to social performance. Our innovative approach will advance understanding of the brain bases of ASD by studying social perception in a naturalistic, interactive context. This research is a critical first step with significant clinial translational benefits, including identifying therapeutic targets, developing biologically-baed predictors of treatment response, creating new treatment approaches, defining subgroups of individuals with ASD, and detecting atypical brain development in ASD before behavioral symptoms become evident.

Public Health Relevance

This project focuses on looking patterns and associated brain response in individuals with ASD during simulated social interactions. By integrating eye-tracking and EEG, the study will investigate a neural marker of sensitivity to reciprocal eye contact in ASD. This potential biomarker holds promise for treatment development and selection, defining subgroups of individuals with ASD, and detecting atypical development in ASD before behavioral symptoms emerge.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
1R01MH100173-01A1
Application #
8595560
Study Section
Child Psychopathology and Developmental Disabilities Study Section (CPDD)
Program Officer
Gilotty, Lisa
Project Start
2013-08-29
Project End
2016-06-30
Budget Start
2013-08-29
Budget End
2014-06-30
Support Year
1
Fiscal Year
2013
Total Cost
$416,250
Indirect Cost
$166,250
Name
Yale University
Department
Psychiatry
Type
Schools of Medicine
DUNS #
043207562
City
New Haven
State
CT
Country
United States
Zip Code
06520
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Stavropoulos, Katherine K M; Viktorinova, Michaela; Naples, Adam et al. (2018) Autistic traits modulate conscious and nonconscious face perception. Soc Neurosci 13:40-51
Rolison, Max J; Naples, Adam J; Rutherford, Helena J V et al. (2018) Modulation of reward in a live social context as revealed through interactive social neuroscience. Soc Neurosci 13:416-428
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McPartland, James C (2017) Developing Clinically Practicable Biomarkers for Autism Spectrum Disorder. J Autism Dev Disord 47:2935-2937
Foss-Feig, Jennifer H; McPartland, James C; Anticevic, Alan et al. (2016) Re-conceptualizing ASD Within a Dimensional Framework: Positive, Negative, and Cognitive Feature Clusters. J Autism Dev Disord 46:342-351
Carter Leno, Virginia; Naples, Adam; Cox, Anthony et al. (2016) Common and distinct modulation of electrophysiological indices of feedback processing by autistic and psychopathic traits. Soc Neurosci 11:455-66
McPartland, James C (2016) Considerations in biomarker development for neurodevelopmental disorders. Curr Opin Neurol 29:118-22

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