Splenius capitis is a reliable target for measuring cervical vestibular evoked myogenic potentials in adults
Bibliographic record
Abstract
The cervical vestibular evoked myogenic potential (cVEMP) is a common and simple test of vestibulospinal reflex patency. In the clinic, cVEMPs are measured in response to loud sounds from the sternocleidomastoid (SCM) on the ventral neck, as subjects maintain an uncomfortable head posture needed to recruit SCM. Here we characterize the cVEMP in a dorsal neck turner (splenius capitis; SPL), and compare it with the SCM cVEMP. cVEMPs were recorded simultaneously via surface electromyography from SCM and SPL from 17 healthy subjects in a variety of postures, including head-turned postures adopted while either seated or standing, and the clinical posture. Like the SCM cVEMP recorded ipsilateral to the side of sound stimulation, the cVEMP on the contralateral SPL (synergistic with ipsilateral SCM) was characterized by a biphasic wave of muscle activity that began at ~ 13 ms. cVEMP reliability was higher on SPL vs. SCM in standing postures (chi-squared; P < 0.05), and equivalent results were obtained from SPL in a standing or seated posture. In 9 of the 17 subjects, we also obtained bilateral intramuscular (IM) recordings from SPL at the same time as the surface recordings. In these subjects, the initial surface response in SPL was associated with a consistent decrease in multi-unit IM SPL activity. Overall, these results demonstrate that SPL recordings offer a complimentary target for cVEMP assessments. The expression of SPL cVEMPs in simple head-turned postures may also improve the utility of cVEMP testing for vestibular assessment in children, the elderly, or non-compliant.
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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 | 0.001 | 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".