Abstract

Adults with obsessive-compulsive disorder (OCD) display perseverative behavior in stable environments but exhibit vacillating choice when payoffs are uncertain. These findings may be associated with intolerance of uncertainty and compulsive behaviors; however, little is known about the mechanisms underlying learning and decision-making in youths with OCD because research into this population has been limited. To investigate cognitive mechanisms associated with decision-making in youths with OCD by using executive functioning tasks and computational modeling. In this cross-sectional study, 50 youths with OCD (patients) and 53 healthy participants (controls) completed a probabilistic reversal learning (PRL) task between January 2014 and March 2020. A separate sample of 27 patients and 46 controls completed the Wisconsin Card Sorting Task (WCST) between January 2018 and November 2020. The study took place at the University of Cambridge in the UK. Decision-making mechanisms were studied by fitting hierarchical bayesian reinforcement learning models to the 2 data sets and comparing model parameters between participant groups. Model parameters included reward and punishment learning rates (feedback sensitivity), reinforcement sensitivity and decision consistency (exploitation), and stickiness (perseveration). Associations of receipt of serotonergic medication with performance were assessed. In total, 50 patients (29 female patients [58%]; median age, 16.6 years [IQR, 15.3-18.0 years]) and 53 controls (30 female participants [57%]; median age, 16.4 years [IQR, 14.8-18.0 years]) completed the PRL task. A total of 27 patients (18 female patients [67%]; median age, 16.1 years [IQR, 15.2-17.2 years]) and 46 controls (28 female participants [61%]; median age, 17.2 [IQR, 16.3-17.6 years]) completed the WCST. During the reversal phase of the PRL task, patients made fewer correct responses (mean [SD] proportion: 0.83 [0.16] for controls and 0.61 [0.31] for patients; 95% CI, -1.31 to -0.64) and switched choices more often following false-negative feedback (mean [SD] proportion: 0.09 [0.16] for controls vs 0.27 [0.34] for patients; 95% CI, 0.60-1.26) and true-positive feedback (mean [SD] proportion: 0.93 [0.17] for controls vs 0.73 [0.34] for patients; 95% CI, -2.17 to -1.31). Computational modeling revealed that patients displayed enhanced reward learning rates (mean difference [MD], 0.21; 95% highest density interval [HDI], 0.04-0.38) but decreased punishment learning rates (MD, -0.29; 95% HDI, -0.39 to -0.18), reinforcement sensitivity (MD, -4.91; 95% HDI, -9.38 to -1.12), and stickiness (MD, -0.35; 95% HDI, -0.57 to -0.11) compared with controls. There were no group differences on standard WCST measures and computational model parameters. However, patients who received serotonergic medication showed slower response times (mean [SD], 1420.49 [279.71] milliseconds for controls, 1471.42 [212.81] milliseconds for patients who were unmedicated, and 1738.25 [349.23] milliseconds for patients who were medicated) (control vs medicated MD, -320.26 [95% CI, -547.00 to -88.68]) and increased unique errors (mean [SD] proportion: 0.001 [0.004] for controls, 0.002 [0.004] for patients who were unmedicated, and 0.008 [0.01] for patients who were medicated) (control vs medicated MD, -0.007 [95% CI, -3.14 to -0.36]) on the WCST. The results of this cross-sectional study indicated that youths with OCD showed atypical probabilistic reversal learning but were generally unimpaired on the deterministic WCST, although unexpected results were observed for patients receiving serotonergic medication. These findings have implications for reframing the understanding of early-onset OCD as a disorder in which decision-making is associated with uncertainty in the environment, a potential target for therapeutic treatment. These results provide continuity with findings in adults with OCD.

Highlights

  • Obsessive-compulsive disorder (OCD) in adults is characterized by widespread cognitive dysfunction, in domains of cognitive flexibility and response inhibition.[1,2] Difficulties in shifting attention from ingrained thoughts and actions and inhibiting inappropriate responses are thought to promote uncontrollable obsessions and urges

  • Computational modeling revealed that patients displayed enhanced reward learning rates but decreased punishment learning rates (MD, −0.29; 95% highest density intervals (HDIs), −0.39 to −0.18), reinforcement sensitivity (MD, −4.91; 95% HDI, −9.38 to −1.12), and stickiness (MD, −0.35; 95% HDI, −0.57 to −0.11) compared with controls

  • Patients who were unmedicated, and 1738.25 [349.23] milliseconds for patients who were medicated) and increased unique errors on the Wisconsin Card Sorting Task (WCST). The results of this cross-sectional study indicated that youths with obsessive-compulsive disorder (OCD) showed atypical probabilistic reversal learning but were generally unimpaired on the deterministic WCST, unexpected results were observed for patients receiving serotonergic medication

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Summary

Introduction

Obsessive-compulsive disorder (OCD) in adults is characterized by widespread cognitive dysfunction, in domains of cognitive flexibility and response inhibition.[1,2] Difficulties in shifting attention from ingrained thoughts and actions (inflexibility) and inhibiting inappropriate responses (response disinhibition) are thought to promote uncontrollable obsessions and urges. On deterministic set-shifting tasks, such as the Wisconsin Card Sorting Task (WCST), which involves learning from consistently reliable feedback to choose cards based on a rule (eg, color) and switching behavior when feedback changes (eg, switching from color to shape), adults with OCD typically commit more perseverative errors than healthy adults because adults with OCD inappropriately attend to previously correct rules and are slower to learn new rules.[5,6,7,8,9,10,11] The inverse is apparent on probabilistic reversal learning (PRL) tasks On such tasks, participants must first identify which of 2 stimuli reliably delivers positive feedback (eg, 70% of the time) and repeatedly select the more optimal stimulus on every trial to maximize rewards. Researchers theorize that this aberrant choice switching is attributed to “overcomplicated exploration,” in which adults with OCD attempt to evaluate too many rules at once.[15]

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