Although associative learning theory suggests that symptoms of posttraumatic stress disorder (PTSD) largely reflect maladaptive learning during and after a traumatic event, classical threat conditioning and extinction experiments in PTSD are often inconclusive. Here, we used quantitative modeling to study reversal learning in a Pavlovian threat conditioning paradigm. We included combat-exposed veterans who met PTSD criterion A with a wide range of psychiatric symptoms and focused on trauma-related psychopathology and its relationship to the latent variables of threat learning, using Hierarchical Bayesian modeling and the best-fit heterogeneous DSM-IV five-factor model of PTSD. We found greater sensitivity to prediction errors in symptomatic veterans and decreased neural correlates of value in the amygdala, in addition to smaller amygdala volumes. These results support a crucial role of the amygdala structure and function in symptoms of PTSD.
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