Reduced Alpha Power Associated with Impaired Dual-Task Standing Performance in Older Adults with MCI
Bibliographic record
Abstract
Abstract Older adults, particularly those with mild cognitive impairment (MCI), often struggle with standing balance during dual-tasking. These difficulties arise from limited cognitive processing capacity, with MCI individuals showing greater dual-task cost than healthy older adults. While Electroencephalogram (EEG) studies have found that MCI is associated with reduced alpha power (8-13 Hz), the influence of dual-tasking on brainwave patterns and its relationship to dual-tasking standing performance remain unclear. We hypothesized that older adults with MCI would show reduced alpha power during dual-tasking compared to cognitively-intact controls, and that this reduction would also correlate with worse dual-tasking performance. We recruited 15 cognitive-intact participants (Montreal Cognitive Assessment (MoCA) score = 25-30) and ten participants with MCI (MoCA score = 21-24). Participants completed standing balance assessments while performing verbal subtractions. EEG alpha, beta, gamma, and theta power were recorded throughout the task. APDM Opal sensors were used to measure postural sway metrics synchronously with EEG recording. Older adults with MCI, as compared to cognitively-intact controls, exhibited lower alpha power, particularly in the central right (p = .003) and anterior left (p = .002) regions of the brain. Beta, theta, and gamma brain waves were not significantly different between groups. Reduced alpha power during dual-tasking was associated with increased postural sway path in older adults with MCI (r = -0.47, p = 0.01). These results suggest that reduced alpha power is correlated with worse dual-task standing performance. Future research should explore whether reduced alpha power contributes to impaired dual-task standing performance 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".