Abnormal functional–structural cingulum connectivity in mania: combined functional magnetic resonance imaging‐diffusion tensor imaging investigation in different phases of bipolar disorder
Bibliographic record
Abstract
OBJECTIVE: The objective of the study was to investigate the relationship between structural connectivity (SC) and functional connectivity (FC) in the cingulum in bipolar disorder (BD) and its various phases. METHOD: We combined resting-state functional magnetic resonance imaging and probabilistic tractographic diffusion tensor imaging to investigate FC and SC of the cingulum and its portions, the SC-FC relationship, and their correlations with clinical and neurocognitive measures on sustained attention in manic (n = 21), depressed (n = 20), and euthymic (n = 20) bipolar patients and healthy controls (HC) (n = 42). RESULTS: First, we found decreased FC between the anterior and posterior parts of the cingulum in manic patients when compared to depressed patients and HC. Second, we observed decreased SC of the cingulum bundle, particularly in its anterior part, in manic patients when compared to HC. Finally, alterations in the cingulum FC (but not SC) correlated with clinical severity scores while changes in the cingulum SC (but not FC) were related with neurocognitive deficits in sustained attention in BD. CONCLUSION: We demonstrate for the first time a reduction in FC and concomitantly in SC of the cingulum in mania, which correlated with psychopathological and neurocognitive parameters, respectively, in BD. This supports the central role of cingulum connectivity specifically in mania.
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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".