In this talk, I will present my recent work that elucidates neurocomputational mechanisms of reinforcement learning in patients 　　with obsessive-compulsive and gambling disorders (OCD and GD, respectively). Compared with healthy controls, patients with OCD learned less from worse-than-expected outcomes, with attenuated representations of the negative reward prediction error in the dmPFC and dorsal striatum. Furthermore, patients with GD exhibited excessive/deficient learning from better/worse-than-expected outcomes, respectively, reflecting the enhanced representation of positive reward prediction error in the insula. These findings provide a potential account of abnormal compulsive behaviors in those mental disorders.

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