Interstimulus Intervals and Sensory Modality Modulate the Impact of a Cognitive Task on Postural Control
Bibliographic record
Abstract
The present literature not only reveals the use of a wide variety of cognitive tasks but variability in their interaction with postural control. The question then arises, as to, whether postural control is sensitive to specific features of a cognitive task. The present experiment assessed the impact of cognitive tasks with interstimulus intervals (ISI) of varied duration and sensory modality on postural control in young adults. Seventeen participants (23.71 ± 1.99 years old) were instructed to stand on a force platform while concurrently performing cognitive tasks with ISIs of two and 5 s. The tasks were presented both, auditorily and visually. The visual tasks consisted of counting the total occurrence of a single digit. The auditory tasks consisted of counting the total occurrence of a single letter. Performing the cognitive tasks with an ISI of 2 s resulted only in an increase in the anteroposterior mean power frequency. Presenting the tasks visually also significantly reduced area of 95% confidence ellipse and AP and mediolateral sway variability. These results may suggest that ISIs can modify postural performance by altering the allocation of attentional focus. Also, presenting tasks using a visual sensory modality appears to yield lower postural sway.
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) | 0.002 | 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".