Talk from Megan Peters - Department of Experimental Psychology, University College London
Abstract:
Assessing early functional neurodevelopment in the human infants has long been a sought-after goal, with applications ranging from basic science to medical research and health care at large. The methods currently in use rely on essentially qualitative and subjective assessments, whether the readout is EEG recording or motor performance. In this presentation, I will briefly summarize recent advances on two fronts: 1) estimating cortical maturity, or functional brain age (FBA), from the infants’ EEG signals, and 2) quantifying gross motor performance and constructing normative growth charts, based on at-home measurements with MAIJU, a multisensory wearable. Both approaches build on the idea that a child’s age is a fundamental benchmark in all developmental science and medicine. Age can therefore serve as the training target for machine learning-based algorithms, which can learn to read functional maturation in a fully observer-independent manner.