Electrical Vestibular Stimuli Evoke Robust Muscle Activity in Deep and Superficial Neck Muscles in Humans
Bibliographic record
Abstract
Neck muscle activity evoked by vestibular stimuli is a clinical measure for evaluating the function of the vestibular apparatus. Cervical vestibular-evoked myogenic potentials (cVEMP) are most commonly measured in the sternocleidomastoid muscle (and more recently the splenius capitis muscle) in response to air-conducted sound, bone-conducted vibration or electrical vestibular stimuli. It is currently unknown, however, whether and how other neck muscles respond to vestibular stimuli. Here we measured activity bilaterally in the sternocleidomastoid, splenius capitis, sternohyoid, semispinalis capitis, multifidus, rectus capitis posterior, and obliquus capitis inferior using indwelling electrodes in two subjects exposed to binaural bipolar electrical vestibular stimuli. All recorded neck muscles responded to the electrical vestibular stimuli (0-100 Hz) provided they were active. Furthermore, the evoked responses were inverted on either side of the neck, consistent with a coordinated contribution of all left-right muscle pairs acting as antagonists in response to the electrically-evoked vestibular error of head motion. Overall, our results suggest that, as previously observed in cat neck muscles, broad connections exist between the human vestibular system and neck motoneurons and highlight the need for future investigations to establish their neural connections.
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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 | 0.000 |
| 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) | 0.001 | 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".