Posttraumatic stress disorder (PTSD) is accompanied by marked alterations in cognition and behavior, particularly when negative, high-value information is present (Aupperle, Melrose, Stein, & Paulus, 2012; Hayes, Vanelzakker, & Shin, 2012) . However, the underlying processes are unclear; such alterations could result from differences in how this high value information is updated or in its effects on processing future information. To untangle the effects of different aspects of behavior, we used a computational psychiatry approach to disambiguate the roles of increased learning from previously surprising outcomes (i.e. associability; Li, Schiller, Schoenbaum, Phelps, & Daw, 2011) and from large value differences (i.e. prediction error; Montague, 1996; Schultz, Dayan, & Montague, 1997) in PTSD. Combat-deployed military veterans with varying levels of PTSD symptoms completed a learning task while undergoing fMRI; behavioral choices and neural activation were modeled using reinforcement learning. We found that associability-based loss learning at a neural and behavioral level increased with PTSD severity, particularly with hyperarousal symptoms, and that the interaction of PTSD severity and neural markers of associability based learning predicted behavior. In contrast, PTSD severity did not modulate prediction error neural signal or behavioral learning rate. These results suggest that increased associability-based learning underlies neurobehavioral alterations in PTSD.