Functional connectivity alterations between default mode network and occipital cortex in patients with obsessive-compulsive disorder (OCD)
Bibliographic record
Abstract
Introduction A meta-analysis by Gürsel et al. (2018) found altered functional connectivity in OCD patients within and between default mode (DMN), salience (SN), and frontoparietal networks (FPN), as well as evidence for aberrant fronto-striatal circuitry. Objectives Testing the replicability of meta-analysis rsfMRI findings in OCD patients. Methods We measured functional connectivity during resting-state fMRI in a sample of OCD patients (n=24) and controls matched for age and sex (n=33). The CONN toolbox implemented in SPM was used to perform seed-to-voxel analysis using 30 seed regions based on the previous meta-analytic findings. Results OCD patients showed reduced functional connectivity between SN and DMN compared to controls, replicating previous findings. We did not observe significant group differences of functional connectivity within the DMN, SN, or FPN. The strongest finding consisted of altered connectivity between DMN and SN to the visual network. OCD patients showed reduced functional connectivity between the left lateral parietal seed (LPl) and the inferior lateral occipital pole left (iLOCl) compared to controls. Furthermore, the LPl was found to be hyperconnected with the right superior lateral occipital cortex (sLOCr) and the right precuneus. This finding was positively correlated to OCD symptom severity, especially compulsions. Conclusions Our findings replicated partly the meta-analysis findings, specifically reduced connectivity between SN and DMN. Using seeds based on the meta-analysis, we identified aberrations between the SN and, in particular, the DMN to the visual network. This raises the question about the visual system’s involvement in OCD symptoms and the abnormal connectivity of a unimodal region to the multimodal DMN. Disclosure No significant relationships.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".