DUAL-TASK CHANGES IN PREFRONTAL ACTIVATION AND GAIT QUALITY IN OLDER ADULTS
Bibliographic record
Abstract
Abstract We compared the impact of performing dual-task walking on gait quality and prefrontal cortical activation assessed by functional near-infrared spectroscopy (fNIRS). We hypothesized a greater increase in fNIRS averaged over the left prefrontal cortex during dual-task walking would be associated with a greater decrease in gait quality (increased step-time variability; decreased gait speed, cadence, smoothness, and adaptability). In older adults (n=60, 75±5.8 years, 57% female), we quantified the change in fNIRS and gait metrics from single-task walking (even surface) to walking with attentional (reciting every-other letter of the alphabet) and physical (uneven surface) dual-task challenges using four 15m repetitions of each task. Gait metrics were computed from a tri-axial accelerometer at the lower-back. Changes in fNIRS from single to dual-task walking were not associated with changes in gait quality for both attentional and physical challenges (Spearman correlations, all p>0.08). Variability in response across individuals may contribute to our findings.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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".