Electrophysiological biomarkers of social engagement in autism

This career development proposal's overall goal is to prepare the candidate, Alexandra Bey, MD, PhD, for an independent research career developing and utilizing electrophysiological and behavioral biomarkers for endophenotyping, stratification, and measuring response to intervention to improve social engagement in autism.

This will be accomplished through a comprehensive training plan targeting expertise in: 1) acquiring, processing, and standard and novel machine-learning analyses of human EEG studies; 2) clinical research with autistic children including study methodology informed by knowledge of social development and interfacing with

neurodiverse stakeholders; and 3) advanced statistical methods including longitudinal and multivariate models. The mentorship team has expertise that overlaps well with these training goals and a proven track record of impactful interdisciplinary research, extensive grant funding, and mentorship of early career faculty, including

several K awardees. The candidate, a neuroscientist and child psychiatrist, has a unique and productive background conducting studies ranging from electrophysiological studies in preclinical models of autism to measuring social engagement in caregiver-child interaction. The environment is ideally-suited, with the

extensive infrastructure of Duke's NIH Autism Center of Excellence research program synergizing with the proposed study as well as the departmental and university commitment to the careers of physician-scientists. Early childhood represents a critical period for delivering early autism intervention to affect lifelong skill

development which impacts an individual's overall functioning. This proposal responds to NIMH autism research priorities to develop “new tools for use in screening, stratification and/or measuring outcome in response to intervention” by investigating electrophysiological biomarkers in autistic preschoolers with relevance to a core

construct of early intervention, enhancing social engagement. Preliminary evidence from electroencephalography (EEG) studies from my mentor's team identified decreased gaze to social compared to nonsocial stimuli is associated with decreased frontal and posterior ß1 power and increased posterior θ EEG

power in autistic children. This proposal will validate this finding in participants undergoing simultaneous EEG and automated detection of eye gaze, analyze the relationship between these EEG power features and rigorous coding of child-caregiver social engagement, and examine the longitudinal relationship between change in these

EEG measures and change in standardized assessments of social communication functioning over time. Finally, the candidate will explore novel analyses of functional connectivity developed from her preclinical electrophysiology studies to determine whether these biomarkers also relate to the above measures of social

engagement given the evidence that aberrant connectivity is a hallmark of autistic brains. Future work will extend these biomarkers to other populations and apply them to early intervention trials.