Author:

Abstract:

Poster presentation - Early career scientists Background: Autism spectrum disorder (ASD) is a neurodevelopmental condition, often diagnosed after the age of three, but by definition, some symptoms have to be present before that age. Early detection seems difficult, because symptoms are diverse and subtle. In this study (part of a larger interdisciplinary project: TIARA, Tracking Infants At Risk for ASD), multimodal longitudinal data will be collected between 5 and 36 months to identify developmental patterns that could lead to ASD. Methods: Data will be collected in three groups of infants at high risk of developing ASD: 1) infants born before 30 weeks of pregnancy1, 2) infant siblings of children with ASD and 3) infants with feeding problems without sufficient somatic explanation. This population is different from previous research (e.g. by the BASIS network, EASE team, Baby Siblings Research consortium), where researchers mainly focused on the siblings. A broad range of data will be collected at 5, 10, 14, 24 and 36 months of age, including behavioral measures (individual and mother-child interaction), neurophysiological data (EEG, fNIRS), genetic and metabolic data. Results: Data collection is ongoing. I will investigate developmental patterns of different parameters (yet to be selected from our range of data). We expect to find different subgroups within the ASD group, for example a group that shows regression, and a group that keeps developing but at a slower pace in certain domains. Besides the longitudinal research question, my focus will be on eye tracking: for example paradigms that focus on attention, preference for social vs non-social cues, pupil dilation, and on EEG: Event related potentials (ERP) to direct vs averted gaze, ERP to own name vs strange name, resting state connectivity. Discussion: Several limitations will be present: for example, recruitment could be biased and drop out is expected.