Modeling Risk and Reward Expectation and Surprise using Optimal Learning Rates in Human Neuronal Populations to assess Impulsive Choice
Rhiannon Cowan, Tyler Davis, Bornali Kundu, John Rolston, Elliot Smith, University of Utah, United States
Posters 1 Poster
Pacific Ballroom H-O
Thu, 25 Aug, 19:30 - 21:30 Pacific Time (UTC -7)
Impulsive choice is a facet of impulsivity that may lead to one choosing smaller, immediate rewards over larger, delayed rewards. We examined impulsive choice behavior in humans undergoing intracranial seizure monitoring by fitting reinforcement learning models to behavior and broadband high frequency (70-150Hz) local field potentials. We found neural and behavioral differences between more and less impulsive choosers, informing the neural underpinnings of impulsive choices.