Researchers from the Nara Institute of Science and Technology (NAIST), Advanced Telecommunications Research Institute International, and Tamagawa University in a collaborative project have demonstrated that obsessive-compulsive disorder (OCD) can be understood as an imbalance between learning parameters, reinforcement, and punishment. Based on empirical tests of their theoretical model, they showed that when learning parameters for reinforcement and punishment are extremely imbalanced, the cycle between obsession and compulsion is strengthened. Hence, this leads to asymmetries in brain calculations that link current results to past actions, resulting in disordered behavior.

In the study, the researchers used reinforcement learning theory to model the disordered cycle associated with OCD. In this protocol, an outcome that is better than predicted becomes more likely (positive prediction error), while a result that is worse than expected is suppressed (negative prediction error). In general, a credit assignment was implemented as a memory trace, i.e., the outcome of a certain choice is available after a certain delay. Therefore, reinforcement and punishment should be assigned to recent choices within a certain time frame. Ideally, memory trace signals for past actions decay at equal speed for both positive and negative prediction errors. However, this cannot be realized in a completely discrete neural system. Using simulations, the scientists found that agents implicitly learn obsessive-compulsive behavior when the trace decay factor for memory traces of past actions related to negative prediction errors (n-) is much smaller than that related to positive prediction errors (n ). This means that, from the opposite perspective, the view of past actions is much narrower for negative prediction errors than for positive prediction errors.

To predict the test findings based on the protocol, the researcher had 45 patients with OCD and 168 healthy control subjects play a computer-based game with monetary rewards and penalties. Patients with OCD showed a much smaller n-value compared with n, as predicted by the computational characteristics of OCD. But the study also showed that this imbalanced setting of trace decay factors (n > n-) was normalized by serotonin enhancers, which are first-line medications for the treatment of OCD. 

(Source: https://www.hindustantimes.com/lifestyle/health/shedding-light-on-ocd-cycle-for-better-understanding-of-mental-behaviour-study-101662098652761.html )