Virginia Tech Carilion Research Institute, Roanoke, United States; School of Psychological and Cognitive Sciences, IDG/McGovern Institute for Brain Research, Beijing Key Laboratory of Behavior and Mental Health, Peking–Tsinghua Center for Life Sciences, Peking University, Beijing, China
John M Wang
Virginia Tech Carilion Research Institute, Roanoke, United States; Department of Psychology, Virginia Tech, Blacksburg, United States
B Christopher Frueh
University of Hawaii, Hilo, United States
Brooks King-Casas
Virginia Tech Carilion Research Institute, Roanoke, United States; Department of Psychology, Virginia Tech, Blacksburg, United States; Salem Veterans Affairs Medical Center, Salem, United States; School of Biomedical Engineering and Sciences, Virginia Tech-Wake Forest University, Blacksburg, United States
Virginia Tech Carilion Research Institute, Roanoke, United States; Department of Psychology, Virginia Tech, Blacksburg, United States; Salem Veterans Affairs Medical Center, Salem, United States
Disproportionate reactions to unexpected stimuli in the environment are a cardinal symptom of posttraumatic stress disorder (PTSD). Here, we test whether these heightened responses are associated with disruptions in distinct components of reinforcement learning. Specifically, using functional neuroimaging, a loss-learning task, and a computational model-based approach, we assessed the mechanistic hypothesis that overreactions to stimuli in PTSD arise from anomalous gating of attention during learning (i.e., associability). Behavioral choices of combat-deployed veterans with and without PTSD were fit to a reinforcement learning model, generating trial-by-trial prediction errors (signaling unexpected outcomes) and associability values (signaling attention allocation to the unexpected outcomes). Neural substrates of associability value and behavioral parameter estimates of associability updating, but not prediction error, increased with PTSD during loss learning. Moreover, the interaction of PTSD severity with neural markers of associability value predicted behavioral choices. These results indicate that increased attention-based learning may underlie aspects of PTSD and suggest potential neuromechanistic treatment targets.