Abstract 70: Rich-Club Behaviour and Analyses in the Human Brain Connectome as Novel Early Biomarkers of Cognitive Decline
Bibliographic record
Abstract
Introduction: Transient ischemic attack (TIA) patients have an increased risk of early dementia, but the mechanism is unclear. One potential mechanism is the damaging effects of microvascular disease on brain networks. Rich club is a phenomenon where highly connected nodes form a “rich club” amongst themselves, thus playing an important role in global brain network communication. In this study we aim to determine 1) whether the prominence of the rich club effect declines greater in TIA patients than controls over time, and 2) the relationship of rich club prominence with cognition. Methods: TIA patients (n=47) and controls (n=43) underwent DTI imaging and cognitive assessment at baseline, 1-year, 3-year, and 5-year. Whole-brain tractography utilizing constrained spherical deconvolution was performed to construct whole-brain connectomes for both groups at all available timepoints. The maximum normalized rich club coefficient (Φ max ) was used as an indicator of the prominence of the rich club effect. Independent-sample T-tests were used to compare Φ max cross-sectionally, while a linear mixed effect (LME) model was used to examine the longitudinal change in Φ max in TIA patients vs. controls, while controlling for covariates including age, sex, WMH volume, whole-brain volume, and peak width of skeletonized mean diffusivity. Results: TIA patients had a mean age of 63.94 ( SD =8.62) and 20 females. Controls had a mean age of 60.73 (8.16) and 29 females. The prominence of the rich club was not significantly different between TIA patients and controls at baseline or 1-year ( p >0.05). However, TIA patients showed a significantly less prominent rich club at 3-year and 5-year compared to controls ( p =0.047 and 0.018, respectively). TIA patients exhibited a significantly greater decrease in rich club prominence over time, relative to controls ( p =0.023), after accounting for covariates. Longitudinal LME models showed no association between changes in rich club prominence and changes in cognition ( p >0.05 for all cognitive domains). Conclusion: In this study, we show a decrease in rich club prominence in TIA patients compared to controls which might identify their increased risk of cognitive impairment, and the potential benefits of aggressive vascular risk reduction.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".