Reduced visual feedback enhances the benefit of rhythmic auditory stimuli
Bibliographic record
Abstract
Rhythmic auditory stimuli (RAS) have been proposed to improve motor performance in populations with sensorimotor impairments. However, the reasons for the reported benefits are poorly understood. One idea is that RAS may supplement when other sensory input is diminished. The current experiment tested this idea by removing vision during a reaching task. We hypothesized that any improvements in movement performance would be enhanced when visual input was removed. Twelve young adults from the university community performed reaching movements to two targets in four possible RAS conditions: sound before; sound during; sound throughout; no sound; all with and without vision. Sound and vision conditions were blocked and counterbalanced while target location was randomized. Reaching movements were recorded using three-dimensional motion capture (Optotrak 3D Investigator, Northern Digital Inc.) and vision was occluded using PLATO Visual Occlusion Spectacles (Translucent Technologies Inc.). Dependent variables were analyzed using a 4 sound by 2 vision repeated measures ANOVA. No vision conditions yielded longer reaction times, more variable movement times and increased endpoint error compared to full vision conditions. Conditions where the metronome was heard before movement initiation (before and throughout), yielded significantly shorter reaction times compared to no sound and sound during conditions. This suggests that the RAS prior to movement initiation helps enhance the movement planning phase. Sound presented before movement initiation had a larger effect on endpoint variable error when vision was not available, supporting the hypothesis that individuals rely more on the RAS when other sensory input is diminished.Acknowledgments: Funding for this research was provided by the Natural Sciences and Engineering Research Council of Canada.
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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 | 0.002 |
| 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) | 0.003 | 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".