Electroacupuncture Modulates Resting-State Functional Connectivity in the Default Mode Network for Healthy Older Adults
Bibliographic record
Abstract
Aging involves cognitive decline and prominent alterations in brain activity. Electroacupuncture (EA), a traditional Chinese medicine approach, is demonstrated to be effective in improving cognitive function of older adults. However, the specific neural mechanism underlying this modulation effect remains unclear. In this study, we used functional magnetic resonance imaging (fMRI) to investigate whether EA could improve cognitive performance of community-dwelling older adults and whether these potential improvements are associated with the EA-induced brain functional connectivity alterations. Thirty healthy older adults were recruited and randomly assigned to the EA group and the control group. Behaviorally, we observed an EA-induced improvement in cognitive performance of older adults in the Montreal Cognitive Assessment. On a neural perspective, the EA intervention significantly increased the functional connectivity within the default mode network. Moreover, we found a positive association between the improvement in delayed memory performance and the alterations in the ventral medial prefrontal cortex-hippocampal formation connectivity in the EA group. This study extends previous findings by showing that healthy older adults exhibit neural plasticity manifested as increased functional connectivity after EA sessions, which could induce therapeutic effects in the treatment of neurodegenerative diseases.
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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".