Title: Brain network dynamics predict surprise dynamics
Ziwei Zhang, doctoral student in the Rosenberg Lab, Department of Psychology, University of Chicago
Abstract, We experience surprise when reality conflicts with our expectations. When we encounter such expectation violations in psychological tasks and daily life, are we experiencing completely different forms of surprise? Or is surprise a fundamental psychological process with shared neural bases across contexts? To address this question, I will introduce a new brain network model, the surprise edge-fluctuation-based predictive model (EFPM). This model predicts surprise in an adaptive learning task from functional magnetic resonance imaging (fMRI) data. I will demonstrate that the same brain network model generalizes to predict surprise from fMRI data as a separate group of individuals watched suspenseful basketball games. Furthermore, I will show evidence that the surprise EFPM uniquely predicts surprise, capturing expectation violations better than models built from other brain networks, fMRI measures, and behavioral metrics. Together these results suggest that shared neurocognitive processes underlie surprise across contexts and that distinct experiences can be translated into the common space of brain dynamics.