Rethinking post-traumatic stress disorder – A predictive processing perspective. (June 2020) - Kube, Tobias; Berg, Max; Kleim, Birgit; Herzog, Philipp
Highlights: This article presents a predictive processing account of PTSD. It reviews how the experience of a traumatic event may alter perception. This account provides new insights into the clinical profile of PTSD. E.g., an imbalance of priors and sensory information may account for flashbacks. This has implications for the psychological and pharmacological treatment of PTSD. Abstract: Predictive processing has become a popular framework in neuroscience and computational psychiatry, where it has provided a new understanding of various mental disorders. Here, we apply the predictive processing account to post-traumatic stress disorder (PTSD). We argue that the experience of a traumatic event in Bayesian terms can be understood as a perceptual hypothesis that is subsequently given a very high a-priori likelihood due to its (life-) threatening significance; thus, this hypothesis is re-selected although it does not fit the actual sensory input. Based on this account, we re-conceptualise the symptom clusters of PTSD through the lens of a predictive processing model. We particularly focus on re-experiencing symptoms as the hallmark symptoms of PTSD, and discuss the occurrence of flashbacks in terms of perceptual and interoceptive inference. This account provides not only a new understanding of the clinical profile of PTSD, but also a unifying framework for the corresponding pathologies at the neurobiological level. Finally, we derive directions for future research and discuss implications for psychological and pharmacological interventions.