Altered response to risky decisions and reward in patients with obsessive–compulsive disorder
Bibliographic record
Abstract
Background: Patients with obsessive–compulsive disorder (OCD) employ ritualistic behaviours to reduce or even neutralize the anxiety provoked by their obsessions. The presence of excessive rumination and indecision has motivated the view of OCD as a disorder of decision-making. Most studies have focused on the “cold,” cognitive aspects of decision-making. This study expands current understanding of OCD by characterizing the abnormalities associated with affective, or “hot” decision-making. Methods: We performed a functional MRI study in a sample of 34 patients with OCD and 33 sex- and age-matched healthy controls, during which participants made 2-choice gambles taking varying levels of risk. Results: During risky decisions, patients showed significantly reduced task-related activation in the posterior cingulum, lingual gyrus and anterior cingulate cortex. We identified significant group × risk interactions in the calcarine cortex, precuneus, amygdala and anterior cingulate cortex. During the outcome phase, patients with OCD showed stronger activation of the orbitofrontal cortex, anterior cingulate cortex and putamen in response to unexpected losses. Limitations: The group of patients not receiving medication was very small (n = 5), which precluded us from assessing the effect of medication on risk-taking behaviour in these patients. Conclusion: Obsessive–compulsive disorder is associated with abnormal brain activity patterns during risky decision-making in a set of brain regions that have been consistently implicated in the processing of reward prediction errors. Alterations in affective “hot” processes implicated in decision-making may contribute to increased indecisiveness and intolerance to uncertainty in patients with OCD.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".