Resting state functional connectivity in women with bipolar disorder during clinical remission
Bibliographic record
Abstract
OBJECTIVES: Periods of euthymia in bipolar disorder (BD) serve as a valuable time to study trait-based pathophysiology. The use of resting state functional connectivity (Rs-FC) can aid in the understanding of BD pathophysiology free of task or mood state biases. The present study investigated two unexplored areas of Rs-FC research in bipolar remission: (i) Rs-FC in women, controlling for the potential influence of premenstrual symptoms, and (ii) the use of both independent component analysis (ICA) and seed-based analysis (SBA) to investigate Rs-FC. METHODS: We investigated Rs-FC of the default mode network, meso-paralimbic network and fronto-parietal network in a sample of 32 euthymic women with BD and 36 age-matched controls during the mid-follicular phase of their menstrual cycle. Rs-FC was assessed with ICA and SBA using the posterior cingulate cortex (PCC), amygdala and dorsolateral prefrontal cortex (dlPFC) as seed points for their respective resting state networks. RESULTS: In BD, compared to controls, SBAs revealed increased coupling between the PCC and the angular gyrus (P=.002, false discovery rate [FDR]-corrected) and between the right dlPFC and the brainstem (P=.03, FDR-corrected). In BD only, PCC-angular gyrus coupling was correlated with anxiety symptoms. Group differences in Rs-FC using ICA did not survive multiple comparisons. CONCLUSIONS: Negative findings from whole-brain ICA Rs-FC may reflect a state of clinical remission in BD. Heightened activation between the PCC and the angular gyrus and between the dlPFC and the brainstem may reflect (i) an abnormal trait integration of affective information during clinical remission and/or (ii) an adaptive compensatory mechanism required for clinical stabilization.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".