Dyadic EEG

Dyadic EEG, the simultaneous recording of brain activity from two individuals, aims to objectively quantify interpersonal interactions and neural synchrony. Current research focuses on developing machine learning models, including deep neural networks and tensor decomposition methods, to analyze these complex spatio-temporal patterns from dyadic EEG data to understand social relationships and diagnose neurological conditions like autism spectrum disorder. This approach offers a powerful tool for moving beyond subjective assessments in fields such as psychiatry and cognitive neuroscience, potentially leading to improved diagnostic tools and a deeper understanding of social cognition.