Cognitive reserve: Investigate the efficacy of resistance training on cognitive reserve 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) secondary to SIVCI often result in impaired executive function. Cognitive reserve is a property of the brain that allows for preserved cognitive performance given brain injury or disease. In an unpublished cross‐sectional study, we found the strength of intra‐network connectivity in fronto‐executive network (FEN), fronto‐parietal network (FPN) and default mode network (DMN) moderated the relationship between WMH and executive function in older adults with SIVCI. Thus, these networks may be involved in cognitive reserve. Exercise is hypothesized to contribute to cognitive reserve. We explored the effect of resistance training (RT) on functional connectivity (FC) in FEN, FPN, and DMN, as well as executive function, in older adults with SIVCI. Method In a 12‐month randomized controlled trial that randomized adults with SIVCI to either 2x/week of RT or 2x/week of balance and tone training (BAT; control). Resting‐state functional MRI was collected from a subset of 29 participants (RT = 14; BAT = 15) at baseline and trial completion. FC of FEN, FPN, and DMN was quantified using priori‐selected region‐of‐interest masks. Executive function was measured by Trail Making Test (TMT), Digit Symbol Substitution Test (DSST) and Stroop Test (ST). Analysis of covariance was conducted to compare differences in group means of intra‐network FC of FEN, FPN and DMN and executive function tests performance at trial completion, with baseline outcome scores as covariate. Pearson correlations were computed to determine whether changes in executive performance between baseline and trial completion were related to changes in FC in the RT group. Result At trial completion, there were no significant between‐group differences in intra‐network FC of FEN, FPN and DMN. RT significantly improved ST performance (estimated mean change[95%CI]: ‐11.322[‐22.366, ‐0.277], p = 0.045) compared with BAT; there were no significant between‐group differences in TMT and DSST. Within RT group, improved ST performance was significantly correlated with increased intra‐network FC of FEN (r = ‐0.697, p = 0.006). Conclusion RT‐induced improvement in ST performance was associated with increased intra‐network FC of FEN. More research is needed to determine whether exercise training has an effect on the neural correlates of cognitive reserve.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".