Aerobic exercise increases hippocampal volume in older women with probable mild cognitive impairment: a 6-month randomised controlled trial
Bibliographic record
Abstract
BACKGROUND: Mild cognitive impairment (MCI) is a well-recognised risk factor for dementia and represents a vital opportunity for intervening. Exercise is a promising strategy for combating cognitive decline by improving brain structure and function. Specifically, aerobic training (AT) improved spatial memory and hippocampal volume in healthy community-dwelling older adults. In older women with probable MCI, we previously demonstrated that resistance training (RT) and AT improved memory. In this secondary analysis, we investigated: (1) the effect of RT and AT on hippocampal volume and (2) the association between change in hippocampal volume and change in memory. METHODS: 86 women aged 70-80 years with probable MCI were randomly assigned to a 6-month, twice-weekly programme of: (1) AT, (2) RT or (3) balance and tone training (BAT; ie, control). At baseline and trial completion, participants performed a 3T MRI scan to determine hippocampal volume. Verbal memory and learning were assessed by Rey's Auditory Verbal Learning Test. RESULTS: Compared with the BAT group, AT significantly improved left, right and total hippocampal volumes (p≤0.03). After accounting for baseline cognitive function and experimental group, increased left hippocampal volume was independently associated with reduced verbal memory and learning performance as indexed by loss after interference (r=0.42, p=0.03). CONCLUSIONS: Aerobic training significantly increased hippocampal volume in older women with probable MCI. More research is needed to ascertain the relevance of exercise-induced changes in hippocampal volume on memory performance in older adults with MCI. TRAIL REGISTRATION NUMBER: NCT00958867.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".