Habituation of the GVS-evoked lower leg muscle response during free standing
Bibliographic record
Abstract
Galvanic vestibular stimulation (GVS) modulates the firing of vestibular afferents (Goldberg et al. 1984) and consequently results in whole-body postural responses (Fitzpatrick & Day 2004). Similar to other sensory systems, the vestibular system habituates to repeated stimuli in both animals and humans. The habituation phenomenon is characterized by a response decrement to a repeating stimulus that is not associated with adaptation or fatigue. Although adaptation to GVS has been observed (St. George et al. 2011), there is limited evidence demonstrating habituation of postural responses associated with repetitive GVS. The purpose of this study was to determine whether the vestibular-evoked myogenic responses habituate in lower leg muscles. Participants stood upright with their eyes closed and head turned 90° to the right while surface electromyography was recorded from the left medial gastrocnemius and soleus. Participants were exposed to a predetermined order (balanced latin square) of sinusoidal GVS consisting of eight different frequencies (0.125–16.0Hz) presented over 6-min trials (single frequency per trial). Habituation of the muscle responses to the vestibular signal was quantified using frequency (coherence) and time (cumulant density) domain correlations. The GVS-induced myogenic responses decreased in both muscles throughout the trials. Myogenic responses elicited by 4 and 8Hz stimuli habituated to a greater extent than other frequencies tested. Our findings indicate that GVS-evoked myogenic responses habituate and that the habituation process is frequency-dependent. Considering that GVS provides a way to quantify vestibular control of muscles, future experiments should take into account the possibility of habituation while analyzing GVS-evoked responses.
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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) | 0.002 | 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".