The Effects of Combined Cognitive and Physical Interventions on EEG Spectral Power in Elderly Individuals With Cognitive Decline
Bibliographic record
Abstract
Background and Purpose: Cognitive decline in the elderly, including conditions like subjective cognitive decline, mild cognitive impairment, and Alzheimer's disease, poses significant challenges to public health, adversely affecting quality of life and increasing healthcare costs.This study evaluated the effects of a 12-week cognitive and physical intervention on cognitive function and electroencephalography (EEG) spectral power in elderly participants.Methods: Sixty-six participants aged 60-85 years were recruited, with a subset of 16 undergoing EEG assessments before and after the intervention.The program combined cognitive training with physical exercises designed to enhance memory, attention, executive function, and physical fitness.EEG data were analyzed for changes in spectral power across various frequency bands.Results: While no significant improvements were observed in cognitive tests (Korean Mini-Mental State Examination [K-MMSE], Korean Montreal Cognitive Assessment [K-MoCA]), exercise capacity (Five Times Sit-to-Stand Test) significantly improved.EEG analysis revealed an increase in delta power at the O1 and O2 channels and a decrease in alpha power at several brain regions, including F7, Fz, F4, Pz, and O2.Also, the delta activity in O1 and the alpha activity in Pz showed correlations with K-MMSE and K-MoCA, respectively.Conclusions: The 12-week intervention led to significant changes in EEG spectral power, specifically an increase in delta power and a decrease in alpha power.These findings suggest that combined cognitive and physical interventions may enhance brain function in elderly individuals with cognitive decline.Further research is needed to confirm these findings and explore their clinical implications.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".