Provocation of obsessive–compulsive symptoms: a quantitative voxel-based meta-analysis of functional neuroimaging studies
Bibliographic record
Abstract
OBJECTIVE: Recent functional magnetic resonance imaging (fMRI) and positron emission tomography (PET) studies based on the symptom provocation paradigm have explored neural correlates of the cognitive and emotional processes associated with the emergence of obsessive-compulsive disorder (OCD) symptoms. Although most studies showed the involvement of cortico-subcortical loops originating in the orbitofrontal cortex and the anterior cingulate cortex, an increased activity within numerous other regions of the brain has inconsistently been reported across studies. To provide a quantitative estimation of the cerebral activation patterns related to the performance of the symptom provocation task by OCD patients, we conducted a voxel-based meta-analysis. METHODS: We searched the PubMed and MEDLINE databases for studies that used fMRI and PET and that were based on the symptom provocation paradigm. We entered data into a paradigm-driven activation likelihood estimation meta-analysis. RESULTS: We found significant likelihoods of activation in cortical and subcortical regions of the orbitofrontal and anterior cingulate loops. The left dorsal frontoparietal network, including the dorsolateral prefrontal cortex and precuneus, and the left superior temporal gyrus also demonstrated significant likelihoods of activation. CONCLUSION: Consistent results across functional neuroimaging studies suggest that the orbitofrontal and anterior cingulate cortices are involved in the mediation of obsessive-compulsive symptoms. Based on recent literature, we suggest that activations within the dorsal frontoparietal network might be related to patients' efforts to resist the obsessive processes induced by the provocation task. Further research should elucidate the specific neural correlates of the various cognitive and emotional functions altered in 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 | 0.029 | 0.043 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.012 | 0.047 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".