Neural Dynamics of Social Cognition: A Single-Trial Computational Analysis of Learning Under Uncertainty.

ABSTRACT: Understanding others' intentions amidst uncertainty is critical for effective social interactions, yet the neural mechanisms underlying this process are not fully understood. Here, we combined computational modeling and single-trial EEG analysis to examine how the brain dynamically updates beliefs about others' intentions in volatile social contexts. A total of 43 healthy volunteers engaged in a deception-free advice-taking task, featuring alternating stable and volatile phases that systematically manipulated the reliability of an adviser's intentions. Using the hierarchical Gaussian filter (HGF), a Bayesian model of learning, we quantified trial-by-trial updates of participants' beliefs and their neural correlates. EEG amplitudes systematically varied according to task volatility, engagin

SUBMITTER: Charlton CE 

PROVIDER: S-EPMC12800744 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature