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. Yet, differential diagnosis is challenging and limited to clinical interviews and self-report symptom questionnaires. We predicted that obsessions and paranoia would be associated with distinct patterns of behavior 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, although some report perseveration in patients with OCD and those with schizophrenia. Here, we analyze data gathered from the general population to assess the associations between obsessions, paranoia, and PRL task performance. Using a novel computational method – Bayesian Gaussian Graphical Modeling combined with a Hierarchical Gaussian Filter – we distinguish the impacts of paranoia and obsession on reversal learning – despite their significant correlation. We find that win-switching arises in paranoia from deficits in learning about uncertainty in the global task structure, whereas excessive switching in OCD arises from challenges in learning about uncertainty at the local choice level.