Modelling metaplasticity and memory reconsolidation during an eye-movement desensitization and reprocessing treatment

In this paper, a computational model is presented to simulate the effect of Eye Movement Desensitization and Reprocessing (EMDR) therapy on persons affected by a Post-Traumatic Stress Disorder (PTSD). The simulation is based on an adaptive temporal-causal network modelling approach. Adaptiveness is achieved using network reification, to model plasticity based on the Hebbian Learning principle and metaplasticity. During EMDR therapy, within the brain resource competition occurs, which helps to improve stress regulation. More specifically, eye-movement intervention causes competition between parietal networks and the amygdala, due to which they negatively affect each other’s activation. Psychological traumas impair (extinction) learning by so-called ‘negative metaplasticity’. EMDR is functional in shifting this back to ‘positive metaplasticity’. This revitalizes extinction learning and memory reconsolidation. The introduced adaptive network model and its simulation confirms the functionality of the neural processes and the effective treatment results of EMDR.

Conference

English

Lennart Zegerius
Jan Treur

Zegerius, L., & Treur, J. (2020). Modelling metaplasticity and memory reconsolidation during an eye-movement desensitization and reprocessing treatment. In Proc. of the 2020 Annual International Conference on Brain-Inspired Cognitive Architectures for Artificial Intelligence (BICA*AI 2020) (Advances in Intelligent Systems and Computing, AISC). Springer International Publishing AG