Intracranial Insights into Globus Pallidus externus (GPe) Computations in Obsessive-Compulsive Disorder

PROJECT SUMMARY Obsessive-compulsive disorder (OCD) is characterized by repetitive thoughts and behaviors, often driven by an inability to adapt behavior in response to changing environments. The basal ganglia, a network of subcortical nuclei, plays a crucial role in cognitive and motor processes, and imbalances between the direct and indirect pathways of this network is implicated in OCD. The indirect pathway is hypothesized to be hyperactive in OCD, leading to excessive suppression of behavioral flexibility. This hyperactivity may underlie the hallmark compulsive and repetitive behaviors seen in OCD, which can be interpreted as an over-reliance on habitual associations, effectively "locking" patients into rigid behavioral states This project aims to investigate the role of the external part of the globus pallidus (GPe), a key node in the indirect pathway of the basal ganglia, in compulsive choice behavior. By leveraging intracranial single-unit recordings in OCD patients undergoing deep brain stimulation (DBS) surgery, this study will assess how neural activity in the GPe contributes to adaptive and maladaptive decision-making during a reversal learning task. The goals of this study are twofold: (1) characterize the role of the GPe in adaptive and maladaptive decision-making in OCD, and (2) determine the computational contributions of GPe to the basal ganglia indirect pathway using single- unit recordings during reversal learning. Specifically, we hypothesize that neural activity in the GPe will be modulated during changes in choice selection ("switch" versus "stay" conditions), with increased firing rates observed during switch conditions. Additionally, we predict that GPe activity will differ based on the outcome valence of decisions (positive, negative, and neutral results). We will also test the hypothesis that reward prediction errors and choice confidence, estimated using reinforcement learning and Bayesian models, respectively, will be correlated with GPe firing rates. By addressing these aims, this project will generate novel insights into human GPe signaling, which has never before been recorded, offering a unique perspective on the neurobiology of compulsive behaviors. Ultimately, these findings may lead to new therapeutic targets for OCD, improving our understanding and treatment of this debilitating disorder. This research will also provide the applicant with comprehensive training in computational modeling and human electrophysiology, preparing her to become a leader in computational psychiatry.