Excessive Switching in OCD and Paranoia Arises From Different Deficits in Belief-Updating.

Both obsessions and paranoia are characterized by cognitive inflexibility, particularly in uncertain environments. Differential diagnosis can be challenging and depends on clinical interviews and self-report symptom questionnaires. We predicted that obsessions and paranoia would be associated with distinct suboptimal choice behavioral patterns in our well-established probabilistic reversal learning (PRL) task. Probabilistic reversal learning involves updating beliefs about rewards when contingencies change. Obsessions and paranoia have been linked to excessive switching behaviors during reversal learning; other reports have found perseveration in both OCD and schizophrenia. Here, we analyze data collected from the general population to assess associations between obsessions, paranoia, and PRL task performance. Using a recently developed computational approach - Bayesian Gaussian graphical modeling combined with a Hierarchical Gaussian Filter - we distinguish the impacts of paranoia and obsessions on reversal learning, which we find to be distinct despite the significant correlation of these clinical states. We find that win-switch behavior arises in paranoia from deficits in updating beliefs about uncertainty (i.e., volatility) in the global task structure, whereas excessive switching in OCD arises from diminished belief updating about choice-outcome associations.