Extracting phase-dependent human vestibular reflexes during locomotion using both time and frequency correlation approaches
Bibliographic record
Abstract
Daily activities, such as walking, may require dynamic modulation of vestibular input onto motoneurons. This dynamic modulation is difficult to identify in humans due to limitations in the delivery and analysis of current vestibular probes, such as galvanic vestibular stimulation. Stochastic vestibular stimulation, however, provides an alternative method to extract human vestibular reflexes. Here, we used time-dependent coherence and time-dependent cross-correlation, coupled with stochastic vestibular stimulation, to investigate the phase dependency of human vestibular reflexes during locomotion. We found that phase-dependent activity from the medial gastrocnemius muscles is correlated with the vestibular signals over the 2- to 20-Hz bandwidth during the stance phase of locomotion. Vestibular-gastrocnemius coherence and time-dependent cross-correlations reached maximums at 21 ± 4 and 23 ± 8% of the step cycle following heel contact and before the period of maximal electromyographic activity (38 ± 5%). These results demonstrate 1) the effectiveness of these techniques in extracting the phase-dependent modulation of vestibulomuscular coupling during a cyclic task; 2) that vestibulomuscular coupling is phasically modulated during locomotion; and 3) that the period of strongest vestibulomuscular coupling does not correspond to the period of maximal electromyographic activity in the gastrocnemius. Therefore, we have shown that stochastic vestibular stimulation, coupled with time-frequency decomposition, provides an effective tool to assess the contribution of vestibular ex-afference to the muscular control during locomotion.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".