Mind-body exercise improves cognitive function and modulates the function and structure of the hippocampus and anterior cingulate cortex in patients with mild cognitive impairment
Bibliographic record
Abstract
Mild cognitive impairment (MCI) is a common neurological disorder. This study aims to investigate the modulation effect of Baduanjin (a popular mind-body exercise) on MCI. 69 patients were randomized to Baduanjin, brisk walking, or an education control group for 24 weeks. The Montreal Cognitive Assessment (MoCA) and Magnetic Resonance Imaging scans were applied at baseline and at the end of the experiment. Compared to the brisk walking and control groups, the Baduanjin group experienced significantly increased MoCA scores. Amplitude of low-frequency fluctuations (ALFF) analysis showed significantly decreased ALFF values in the right hippocampus (classic low-freqency band, 0.01-0.08 Hz) in the Baduanjin group compared to the brisk walking group and increased ALFF values in the bilateral anterior cingulate cortex (ACC, slow-5 band, 0.01-0.027 Hz) in the Baduanjin group compared to the control group. Further, ALFF value changes in the right hippocampus and bilateral ACC were significantly associated with corresponding MoCA score changes across all groups. We also found increased gray matter volume in the Baduanjin group in the right hippocampus compared to the brisk walking group and in the bilateral ACC compared to the control group. In addition, there was an increased resting state functional connectivity between the hippocampus and right angular gyrus in the Baduanjin group compared to the control group. Our results demonstrate the potential of Baduanjin for the treatment of MCI.
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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) | 0.001 | 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".