A Neural Network Explanation of Posttraumatic Stress Disorder

Abstract

An introduction to connectionistic neural networks and their importance for behavior therapists was provided by Tryon (1995a). This article shows that the bidirectional associative memory connectionistic neural networks model meets all four of Jones and Barlow’s (1990) requirements and all five of Brewin, Dalgleish, and Joseph’s (1996) requirements for a theoretical explanation of posttraumatic stress disorder (PTSD). The bidirectional associative memory model provides a theoretical basis for explaining the clinical symptom constellation of PTSD, with special emphasis on why trauma is re-experienced through memory; accounts for individual variation in symptom severity, including why some people do not develop PTSD; explains why persons with PTSD are comorbid with depression, generalized anxiety, and substance abuse; explains how abnormal behavior derives from normal memory formation processes; and makes novel predictions.