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Poster E in Poster Session E: Thursday, August 6, 10:30 am – 12:15 pm, Kimmel Center, Shorin & Rosenthal Rooms

Latent Computational Phenotypes of Risky Decision-Making Predict Orbitofrontal Neural Responses During the Balloon Analog Risk Task

Daniel Feldman¹, Rhiannon L Cowan¹, T. Alexander Price¹, Niloufar Shahdoust¹, Tyler S Davis¹, Bornali Kundu¹, Ben Shofty¹, Shervin Rahimpour¹, John D Rolston², Elliot H Smith¹; ¹University of Utah, ²Harvard University

Presenter: Daniel Feldman

Risky decision-making underlies behavioral addictions such as gambling and gaming disorders, yet the computational mechanisms that generate individual differences in risk-taking remain poorly understood. Computational models provide a framework for inferring latent decision processes from behavioral data, including belief updating, valuation, and prediction errors. Here we combine hierarchical Bayesian modeling with intracranial electrophysiology to examine how latent decision variables relate to neural activity during the Balloon Analog Risk Task (BART). Behavioral and neural data from 70 participants were analyzed using a hierarchical model that separates belief updating about balloon pop risk from valuation and choice processes. Gaussian mixture modeling of posterior parameter distributions identified computational phenotypes differing in risk tolerance and choice consistency. A high-risk phenotype showed increased balloon pops and reduced reward. These computational clusters corresponded to distinct neural signatures in orbitofrontal cortex (OFC), with attenuated beta and gamma responses following balloon pops in the high-risk group.

Topic Area: Decision-Making, Cognitive Control & Event Cognition