Cognitive reserve: Resting‐state functional connectivity moderates the association between white matter hyperintensity and executive function in older adults with subcortical ischemic vascular cognitive impairment
Bibliographic record
Abstract
Abstract Background Subcortical ischemic vascular cognitive impairment (SIVCI) is the most common form of vascular cognitive impairment. White matter hyperintensities (WMH) are hallmarks of SIVCI and are associated with impaired executive function. Cognitive reserve is a property of the brain that moderates an individual’s ability to maintain cognitive performance given brain injury or pathology. The neural correlates of cognitive reserve remain elusive; however, resting‐state functional connectivity (rs‐FC) in networks such as the fronto‐executive network (FEN), fronto‐parietal network (FPN) and default mode network (DMN) have been proposed as potential candidates. The role of these networks in mitigating the impact of SIVCI‐related pathology on cognition remains unclear. Therefore, we investigated whether intra‐network rs‐FC in the FEN, FPN, and DMN moderated the negative impact of WMH on executive function in older adults living with SIVCI. Method We conducted a cross‐sectional study among 38 community‐dwelling older adults with SIVCI. Executive function was assessed by the Trail Making Test (B‐A). WMH volume was quantified by T2‐weighted and proton density‐weighted structural magnetic resonance imaging (MRI) using a seed‐based method and log‐transformed before analyses. The rs‐FC was computed via a 5‐min resting‐state functional MRI scan with priori‐selected region‐of‐interest masks. A moderation analysis was conducted to assess whether intra‐network rs‐FC in the FEN, FPN and DMN moderated the association between WMH volume and executive function, adjusting for age, sex, and Montreal Cognitive Assessment (MoCA) score. Result The participants had a mean age of 74.1 years (SD = 5.5) and 71% were female; the mean MoCA score was 21.29 (SD = 2.66). Compared with individuals with lower intra‐network rs‐FC of DMN, those with greater intra‐network rs‐FC of DMN (non‐standardized b = ‐2913.64, p = 0.000) showed better Trail Making Test performance under greater WMH load. In contrast, individuals with lower intra‐network connectivity of FEN (b = 2050.34, p = 0.007) and FPN (b = 1790.81, p = 0.005) had better Trail Making Test performance under greater WMH load. Conclusion The strength of intra‐network connectivity in the FEN, FPN, and DMN moderates the impact of WMH on executive function in older adults with SIVCI. The results shed light on the potential neural basis of cognitive reserve against WMH.
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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 | 0.002 |
| 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 | 0.001 | 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".