Functional connectivity alterations in women with subjective cognitive decline
Bibliographic record
Abstract
Background: Alzheimer's disease (AD) is an incurable neurodegenerative disorder, which disproportionately affects women. Along the continuum of dementia, those who experience subjective cognitive decline (SCD) are thought to be the earliest group at risk for development of AD. Objective: The current study investigated differences in functional connectivity between healthy older women and older women with SCD in multiple resting-state functional connectivity networks. This study also examined whether additional differences existed between women with and without SCD, in various demographic variables, lifestyle factors, and medical comorbidities. Methods: 3T high-resolution resting-state functional MRI (fMRI) scans were retrieved for 25 healthy older women and 25 older women who self-report SCD from the Women's Healthy Ageing Program (WHAP). A seed-based approach was executed in FMRIB's Software Library (FSL) to examine significant differences in functional connectivity within the default mode network (DMN), frontoparietal network (FPN), and salience network (SN) between groups. Group comparisons were conducted between women with SCD and healthy women on various demographic variables, lifestyle factors, and medical comorbidities. Results: Findings revealed significant increases in functional connectivity in the DMN and FPN in older women with SCD compared to healthy older women. Conclusions: Women with self-reported SCD had increased functional connectivity, with no significant differences were detected between groups on comparisons of various demographic variables, lifestyle factors, and medical comorbidities.
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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 | 0.000 | 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) | 0.002 | 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".