The effects of aerobic exercise intensity on memory in older adults
Bibliographic record
Abstract
Aerobic exercise may enhance memory in older adults. However, the optimal intensity and underlying mechanism are unclear. This community-based study examined the effect of aerobic exercise intensity on memory and general cognitive abilities. Brain-derived neurotrophic factor (BDNF) was examined as a potential mechanism. Sixty-four sedentary older adults participated in 1 of 3 groups: (i) high-intensity interval training (HIIT); (ii) moderate continuous training (MCT); or (iii) stretching control (CON). Prior to and following the intervention, high-interference memory was assessed using a Mnemonic Similarity task and executive functions were assessed using Go Nogo and Flanker tasks. HIIT led to the greatest memory performance compared with MCT and CON (F [2,55] = 6.04, p = 0.004) and greater improvements in memory correlated with greater increases in fitness (r s (46) = 0.27, p = 0.03). Exercise intensity seemed to matter less for executive functioning, as positive trends were observed for both HIIT and MCT. No significant differences in BDNF were found between groups. Overall, these results suggest that aerobic exercise may enhance memory in older adults, with the potential for higher intensity exercise to yield the greatest benefit. While our findings suggest that BDNF does not regulate these adaptations, the mechanisms remain to be determined. Novelty High-intensity interval training results in the greatest memory performance in inactive older adults compared with moderate continuous training or stretching. Improvement in fitness correlates with improvement in memory performance.
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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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".