Cognitive control in childhood-onset obsessive–compulsive disorder: a functional MRI study
Bibliographic record
Abstract
BACKGROUND: Failure to resist chronic obsessive-compulsive symptoms may denote an altered state of cognitive control. We searched for the cerebral regions engaged in this dysfunction. METHOD: Differences in brain regional activity were examined by event-related functional magnetic regional imaging (fMRI) in a group of adolescents or young adults (n = 12) with childhood-onset obsessive-compulsive disorder (OCD), relative to healthy subjects. Subjects performed a conflict task involving the presentation of two consecutive and possibly conflicting prime and target numbers. Patients' image dataset was further analysed according to resistance or non-resistance to symptoms during the scans. RESULTS: Using volume correction based on a priori hypotheses, an exploratory analysis revealed that, within the prime-target repetition condition, the OCD subjects activated more than healthy subjects a subregion of the anterior cingulate gyrus and the left parietal lobe. Furthermore, compared with 'resistant' patients, the 'non-resistant' OCD subjects activated a bilateral network including the precuneus, pulvinar and paracentral lobules. CONCLUSIONS: Higher regional activations suggest an abnormal amplification process in OCD subjects during the discrimination of repetitive visual stimuli. The regional distribution of functional changes may vary with the patients' ability to resist obsessions.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".