Relationships of time‐varying resting state network stability and cognitive function along the Alzheimer’s disease spectrum
Bibliographic record
Abstract
Abstract Background Resting‐state functional connectivity (rsFC) neuroimaging studies of Alzheimer’s Disease (AD) have reported alterations in network community structure and time‐varying rsFC (tvFC). However, the temporal stability of community organization in tvFC has not been investigated. Therefore, the purpose of this work was to characterize the relationship of tvFC and cognitive function (CF) along the spectrum of AD progression. Methods Data were part of the Indiana Alzheimer Disease Center and Indiana Memory and Aging study cohorts, randomly split into discovery and validation samples (Table1). After standard preprocessing, rsFC (10min acquisition) and tvFC (∼60sec tapered, partially overlapping windows) were estimated for two cortical brain region parcellations (200 and 300 nodes). Modularity was estimated for rsFC and for all tvFC windows, across a range of community scales, with final network stability metric calculated as area under the curve of the mean temporal agreement across scales, within and between seven canonical resting‐state networks (RSNs). The Montreal Cognitive Assessment score was used as an index of overall CF. Spearman partial correlation (adjusted for age, education, and sex) was used to investigate relationships of tvFC stability with CF. Results No significant relationships were identified between CF and rsFC or tvFC community structure metrics (quality and number of communities). For tvFC, temporal stability of two network blocks, between visual‐frontoparietal and within ventral attention, showed significant associations with CF across both samples and both parcellations. Additionally, in the 300‐node parcellation, visual network metrics correlated with CF (Figure1). CF was negatively associated with tvFC community stability of regions belonging to different RSNs (Figure1A) and positively with regions within RSNs (Figure1B,C). Conclusion Overall, these findings demonstrate a loss in the stability of RSNs in tvFC with decreasing CF. The networks identified here are generally implicated in cognitive control as well as orientation and attention to salient stimuli. These findings demonstrate that tvFC stability (independent of community and parcellation size) is related to CF along a spectrum of AD risk. Temporal dynamics at rest have potential as a biomarker to characterize progression in prodromal AD. Longitudinal studies are needed to assess the predictive validity of RSN dynamics.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".