Age differences in electrocortical dynamics during uneven terrain walking
Bibliographic record
Abstract
Walking on uneven terrain becomes more difficult as we age, and gait becomes less automatic. Using mobile brain imaging via high-density electroencephalography (EEG) can provide insight into the neural mechanisms contributing to reduced mobility capability with aging. The objective of this study was to quantify age differences in electrocortical dynamics during uneven terrain walking, both averaged across many strides and variations within a stride. We included 31 young adults and 71 older adults for analysis. All participants walked on an uneven terrain treadmill with four levels of terrain difficulty at their self-selected speed. Compared with younger adults, older adults exhibited a greater increase in step duration variability and mediolateral sacral excursion variability as the terrain became more uneven. We identified multiple brain regions involved during walking on uneven terrain. Regardless of age group, walking on uneven terrain compared with flat terrain led to a widespread change of electrocortical dynamics in the brain, especially in the alpha (8-13 Hz) and beta (13-30 Hz) band power. In the parieto-occipital region, younger adults experienced a greater reduction in alpha and beta power with increasing terrain unevenness than older adults. We also assessed how intra-stride power fluctuations changed with terrain unevenness and age group. Greater intra-stride power spectral fluctuations in the occipital area were associated with greater terrain unevenness for younger adults, but not for older adults. In summary, older adults showed a greater increase in gait variability than younger adults as the terrain became more uneven, but exhibited a lack of modulation of parieto-occipital activity in response to terrain unevenness. The lack of task-related power modulation may suggest reduced cortical network flexibility in older adults. The absence of increased parieto-occipital activity when walking on uneven versus flat surfaces in older adults may also indicate that, unlike younger adults, older adults already heavily rely on visual processes during flat surface walking and may, therefore, have reduced occipital modulation range remaining to cope with the visuomotor processing demands of walking on uneven surfaces.
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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 | 0.000 | 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".