Frequency response of human vestibular reflexes characterized by stochastic stimuli
Bibliographic record
Abstract
Stochastic vestibular stimulation (SVS) can be used to study the postural responses to unpredictable vestibular perturbations. The present study seeks to determine if stochastic vestibular stimulation elicits lower limb muscular responses and to estimate the frequency characteristics of these vestibulo-motor responses in humans. Fourteen healthy subjects were exposed to unpredictable galvanic currents applied on their mastoid processes while quietly standing (+/-3 mA, 0-50 Hz). The current amplitude and stimulation configuration as well as the subject's head position relative to their feet were manipulated in order to determine that: (1) the muscle responses evoked by stochastic currents are dependent on the amplitude of the current, (2) the muscle responses evoked by stochastic currents are specific to the percutaneous stimulation of vestibular afferents and (3) the lower limb muscle responses exhibit polarity changes with different head positions as previously described for square-wave galvanic vestibular stimulation (GVS) pulses. Our results revealed significant coherence (between 0 and 20 Hz) and cumulant density functions (peak responses at 65 and 103 ms) between SVS and the lower limbs' postural muscle activity. The polarity of the cumulant density functions corresponded to that of the reflexes elicited by square-wave GVS pulses. The SVS-muscle activity coherence and time cumulant functions were modulated by current amplitude, electrode position and head orientation with respect to the subject's feet. These findings strongly support the vestibular origin of the lower limb muscles evoked by SVS. In addition, specific frequency bandwidths in the stochastic vestibular signal contributed to the early (12-20 Hz) and late components (2-10 Hz) of the SVS-evoked muscular responses. These frequency-dependent SVS-evoked muscle responses support the view that the biphasic muscle response is conveyed by two distinct physiological processes.
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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".