Project Description:
Behavioral studies of infants at high familial risk (HR) for ASD have revealed that the defining features of ASD emerge during a relative pre-symptomatic period in the first year of life. However, these behavioral features have not proven sufficiently accurate for clinically-useful diagnostic prediction, and therefore treatment is often delayed until an ASD diagnosis is made. Electroencephalography (EEG) and eye tracking (ET) represent two methods that index neural processing in infancy and can elucidate presymptomatic predictive biomarkers of ASD. EEG and ET are developmentally sensitive, scalable, and accessible in community, real-world settings. In spring 2019, the IBIS Network will launch a new study of 250 HR infants designed to replicate and extend its predictive imaging findings (1R01 MH118362 MRI based pre-symptomatic prediction of ASD). Informed by neuroimaging predictors from IBIS, we propose to examine EEG and ET measures of (1) distributed brain network development (resting state and naturalistic social scenes), (2) low level visual processing (visual evoked potential) and attentional orienting to social information (naturalistic social scenes) and (3) low level auditory processing, in high risk infants from IBIS at 6 and 12 months of age, with clinical outcomes assessed at 24 months of age. Our overarching hypothesis is that these scalable biomarkers will (Aim 1) accurately identify infants with a later diagnosis of ASD and (Aim 2) will relate to dimensional ASD-associated behaviors at 24 months of age. Capitalizing on this unprecedented opportunity to integrate EEG/ET with neuroimaging in the same cohort of infants, we also propose to explore the association between EEG/ET and MRI features (Aim 3) and the predictive power of these combined measures. This study will also generate a rich database of multimodal imaging and behavior in HR infants that can support future scientific inquiries.
