BRAIN ACTIVITY DURING DUAL-TASK STANDING IN OLDER ADULTS WITH MILD COGNITIVE IMPAIRMENT
Bibliographic record
Abstract
Abstract Performance of a cognitive task while standing disrupts balance in older adults. This disruption is exaggerated in those with mild cognitive impairment (MCI). Moreover, older adults with MCI who exhibit greater dual-task ‘cost’ are more likely to develop falls and dementia. EEG studies suggest that cognitive-motor dual-tasking is associated with brain activity fluctuations originating from central brain regions at specific frequencies, particularly in the alpha-band (8–13 Hz). We hypothesized that older adults with MCI would demonstrate decreased EEG alpha power during dual-task standing compared to healthy controls, and that decreased alpha power would be associated with elevated dual-task cost. We recorded postural sway and EEG in 14 participants with MCI [Montreal Cognitive Assessment (MoCA) < 25] and 16 healthy older adults [MoCA>25] as they completed trials of standing with and without serial subtractions. Postural sway metrics were derived, and from EEG we calculated absolute alpha-, theta-, and beta-band powers within a-priori defined regions-of-interest: the left and right anterior, central, and posterior regions. Repeated Measures ANOVA demonstrated that participants with MCI exhibited decreased alpha power in the central regions during dual-task standing compared to healthy controls (p= 0.01). No significant difference was observed for theta and beta-band powers between participants with MCI and healthy controls. In those with MCI, lower alpha power during dual-task standing correlated with increased dual-task cost to postural sway path (worse balance) (r=-0.4, p=0.03). These results provide preliminary evidence that specific patterns of brain activity during dual-tasking are disrupted in MCI and this is associated with elevated dual-task costs.
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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) | 0.001 | 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".