Neural activity, measured by electroencephalography (EEG), is a promising candidate biomarker of ASD. Knowledge of how patterns of neural activity correlate with symptom domains of ASD, such as social deficits and repetitive behavior, could shed light on how neural circuitry is altered in ASD, and provide novel biomarkers for use in clinical trials.  However, like other biomarkers of ASD, EEG has been hampered by the etiologic and phenotypic heterogeneity of ASD. Studies of brain biomarkers including structural and functional brain imaging  have struggled with extreme variability in findings across studies that compare ASD cases to matched controls. Studies that focus on distinct genetic etiologies demonstrate that this inconsistency is attributable to differences between genetic subtypes.

Funded by the Simons Foundation for Autism Research Initiative (SFARI), this project aims to provide good power to detect biomarkers that are directly influenced by genetic risk, could relate wearable device biomarkers to domains of cognition, and could define signatures of neural and physical activity that could help to define subtypes of ASD that are based on common mechanisms of brain function.