Traditional Chinese Mind-Body Exercise Baduanjin Modulate Gray Matter and Cognitive Function in Older Adults with Mild Cognitive Impairment: A Brain Imaging Study
Bibliographic record
Abstract
BACKGROUND: Previous studies found traditional Chinese mind-body exercise Baduanjin could modulate cognition of community older adults. OBJECTIVE: This study aims to investigate the effect of 6 months of Baduanjin exercise on brain structure and cognitive function in older adults with mild cognitive impairment (MCI). METHODS: The MCI older adults were randomly assigned into either Baduanjin training, brisk walking training or usual physical activity control group. Magnetic Resonance Imaging (MRI), Montreal Cognitive Assessment (MoCA) and Wechsler Memory Scale-Chinese Revised (WMS-CR) were applied to measure gray matter volume (GMV), global cognitive ability and memory at baseline and end of intervention. RESULTS: Compared to usual physical activity, Baduanjin exercise significantly improved MoCA, WMS-CR scores, WMS-MQ, and mental control and comprehension memory subscores of the WMS-CR; significantly increased the GMV in the temporal gyrus, frontal gyrus, parietal gyrus, medial occipital gyrus, cingulate gyrus and angular gyrus after 6 months of intervention. Compared to brisk walking, Baduanjin significantly improved MoCA scores and picture reproduction subscores of memory, and significantly increased the GMV in the right frontal gyrus, precentral gyrus, occipital gyrus. Furthermore, the increased GMV in the right medial temporal gyrus was significantly associated with improvement in the MoCA scores. CONCLUSION: The present study suggested that regular Baduanjin training could have a positive effect in increasing brain gray matter and improving cognitive function in older adults with 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) | 0.000 | 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".