Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, United States; Yale MD-PhD Program, Yale School of Medicine, New Haven, United States
Stefan Uddenberg
Princeton Neuroscience Institute, Princeton University, Princeton, United States
Praveen Suthaharan
Department of Psychiatry, Connecticut Mental Health Center, Yale University, New Have, United States
Christoph D Mathys
Scuola Internazionale Superiore di Studi Avanzati (SISSA), Trieste, Italy; Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
Jane R Taylor
Department of Psychiatry, Connecticut Mental Health Center, Yale University, New Have, United States
Paranoia is the belief that harm is intended by others. It may arise from selective pressures to infer and avoid social threats, particularly in ambiguous or changing circumstances. We propose that uncertainty may be sufficient to elicit learning differences in paranoid individuals, without social threat. We used reversal learning behavior and computational modeling to estimate belief updating across individuals with and without mental illness, online participants, and rats chronically exposed to methamphetamine, an elicitor of paranoia in humans. Paranoia is associated with a stronger prior on volatility, accompanied by elevated sensitivity to perceived changes in the task environment. Methamphetamine exposure in rats recapitulates this impaired uncertainty-driven belief updating and rigid anticipation of a volatile environment. Our work provides evidence of fundamental, domain-general learning differences in paranoid individuals. This paradigm enables further assessment of the interplay between uncertainty and belief-updating across individuals and species.