The hierarchical predictive coding framework of post-traumatic stress disorder

Abstract

Humans rely on internal models from sensory information to predict future action, and the default mode network (DMN) plays a pivotal role in this process. These models, however, can become distorted or disrupted in cases of post-traumatic stress disorder (PTSD) because traumatic stress can maladaptively alter how humans understand themselves and predict what happens in the world around them. Here, we examine the relationship between PTSD and this predictive phenomenon known as hierarchical predictive coding implicated in the DMN. We postulate that a hierarchical predictive coding framework will help researchers and clinicians more effectively explain the neural and psychological effects of PTSD among individuals who live with this condition, which may contribute to more targeted research and treatment outcomes.