Exploring the relationship between physical activity and cognitive function: an fMRI pilot study in young and older adults
Bibliographic record
Abstract
Background: There are limited studies exploring the relationship between physical activity (PA), cognitive function, and the brain processing characteristics in healthy older adults. Methods: A total of 41 participants (42.7 ± 20.5 years, 56.1% males) were included in the data analysis. The International Physical Activity Questionnaire Short Form was used to assess PA levels, and the Chinese version of the Montreal Cognitive Assessment-Basic and the Flanker task were employed to evaluate cognitive function. Furthermore, fMRI technology was utilized to examine brain activation patterns. Results: The cognitive function of the older adults was found to be significantly lower compared to the young adults. Within the older adults, those with high levels of PA exhibited significantly higher cognitive function than those with low and medium PA levels. The fMRI data showed significant differences in brain activation patterns among young adults across the different PA levels. However, such difference was not observed among older adults. Conclusion: A decline in cognitive function was observed among older adults. There was a significant correlation between the levels of PA and cognitive function in healthy older adults. The study demonstrated significant effects of PA levels on brain activation patterns in inhibitory control-related regions among young adults, while not significant among older adults. The findings suggest that neurological mechanisms driving the relationship between PA and cognitive function may differ between older and young adults.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".