title: A bidirectional associative memory explanation of posttraumatic stress disorder.
abstract: Network theory is a relatively recent explanatory development to improve our understanding of emotions and emotional disorders. Connectionist neural networks are introduced as mathematically well-defined network theories that have been suggested as PTSD models, partly because of their ability to form and retrieve memories. Explanatory requirements that a comprehensive PTSD theory must have are reviewed. A connectionist neural network system called the bidirectional associative memory (BAM) is extended to encode emotion and cognition and is then shown to satisfy all PTSD explanatory requirements and consequently constitutes a comprehensive PTSD theory. Empirical work pertaining to a fundamental assumption that learning alters brain structure in ways that can be detected by neuroimaging is reviewed. Novel predictions are made, and relevance to neuroscience is discussed.
authors.affiliation: Department of Psychology, Fordham University, Bronx, NY 10458-5198, USA. Wtryon@Fordham.edu
authors.forename: W W
authors.initials: WW
authors.lastname: Tryon
mesh_terms: D001245:Association Learning / Q000502:physiology*; D001921:Brain / Q000503:physiopathology; D001931:Brain Mapping; D003071:Cognition / Q000502:physiology; D004644:Emotions / Q000502:physiology; D006801:Humans; D016571:Neural Networks, Computer; D009473:Neuronal Plasticity / Q000502:physiology; D013313:Stress Disorders, Post-Traumatic / Q000175:diagnosis / Q000503:physiopathology* / Q000523:psychology; D009435:Synaptic Transmission / Q000502:physiology*