恐怖の再発と潜在原因モデル―計算論的精神医学入門―

抄録

Computational psychiatry is an interdisciplinary field that applies computational approaches to the research of mental disorders. The four types of generative models used in computational psychiatry and the benefits of using generative models were explained. As an example of computational psychiatry research, a latent cause model in the return of fear was explained. Latent causal models are generative models of the process by which organisms infer latent causes from observed data, and can explain fear conditioning. As the future challenges in computational psychiatry, the making open of data, analysis codes, and materials and methods for accumulating knowledge about computational psychiatry were discussed.