Impairment of arbitration between model-based and model-free reinforcement learning in obsessive–compulsive disorder - Ruan, Zhongqiang; Seger, Carol A.; Yang, Qiong; Kim, Dongjae; Lee, Sang Wan; Chen, Qi; Peng, Ziwen (Frontiers in Psychiatry, 2023)
Introduction: Obsessive-compulsive disorder (OCD) is characterized by an imbalance between goal-directed and habitual learning systems in behavioral control, but it is unclear whether these impairments are due to a single system abnormality of the goal-directed system, or due to an impairment in a separate arbitration mechanism that selects which system controls behavior at each point in time. Methods: 30 OCD patients and 120 healthy controls performed 2-choice, 3-stage Markov decision-making paradigm. Reinforcement learning models were used to estimate goal-directed learning (as model based reinforcement learning) and habitual learning (as model free reinforcement learning). 29 high Obsessive–Compulsive Inventory-Revised (OCI-R) score controls, 31 low OCI-R score controls and all 30 OCD patients were selected for the analysis. Results: OCD patients showed less appropriate strategy choice than controls regardless of whether the OCI-R scores in the control subjects were high (p = 0.012) or low (p < 0.001), specifically showing greater model-free strategy use in task conditions where the model-based strategy was optimal. Furthermore, OCD patients (p = 0.001) and control subjects with high OCI-R scores (H-OCI-R; p = 0.009) both showed greater system switching rather than consistent strategy use in task conditions where model-free use was optimal. Conclusions: These findings indicated an impaired arbitration mechanism for flexible adaptation to environmental demands in both OCD patients as well as healthy individuals reporting high OCI-R scores.