A joint research group of Nara Institute of Science and Technology and Advanced Telecommunications Research Institute International has clarified the mechanism of obsessive-compulsive disorder (obsessive-compulsive disorder) using a computational model.

 Obsessive-compulsive disorder, which is characterized by ``obsessions'' accompanied by intense anxiety and ``compulsions'' in which excessive and repetitive behaviors are performed in order to temporarily alleviate them, is not only the mechanism of its onset, but also treatment (behavioral therapy and drug therapy). It is a psychiatric disease for which even the mechanism by which it exerts its effects has not been elucidated.In contrast, this group attempted to clarify the mechanism of obsessive-compulsive disorder using a computational approach.

 Focusing on "reinforcement learning", which is said to be learning that the brain performs so that it becomes easier to select actions with higher value, we created a computational model that regards the process of reinforcement learning as a kind of calculation.When we conducted simulations and analyzes using various learning parameters in this computational model, we found that the learning parameters, which express the characteristics of ``how much past behavior is associated with learning,'' are extremely unbalanced (current results are lower than expected). It was found that obsessive-compulsive symptoms may be learned unnoticed when the parameter for the bad case is extremely smaller than the parameter for the better than expected case.

 When the learning parameters of obsessive-compulsive disorder patients were actually measured and estimated in a choice task, it was confirmed that they showed unbalanced learning parameters compared to healthy subjects, as predicted by the computational model.Furthermore, with regard to behavioral therapy and drug therapy, which are the first-line treatment methods, it was found in simulations using a computational model that behavioral therapy, in which people practice not to perform compulsions even if they have obsessive thoughts, can improve obsessive-compulsive symptoms. In addition, we succeeded in finding a relationship in which the imbalance in learning parameters was eliminated as the dose of a serotonin reuptake inhibitor, a therapeutic drug, was increased.

 It can be said that these results have brought about great progress in understanding the underlying mechanisms of obsessive-compulsive symptoms and treatment methods.In the future, by evaluating learning parameters before treatment, there is a possibility that it can be applied to optimize treatment according to patient characteristics.

Paper information:[Cell Reports] Memory trace imbalance in reinforcement and punishment systems can reinforce implicit choices leading to obsessive-compulsive behavior

Tamagawa University

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