Vestibulospinal influences on lower limb motoneurons
Bibliographic record
Abstract
Galvanic vestibular stimulation (GVS) is a research tool used to activate the vestibular system in human subjects. When a low-intensity stimulus (1-4 mA) is delivered percutaneously to the vestibular nerve, a transient electromyographic response is observed a short time later in lower limb muscles. Typically, galvanically evoked responses are present when the test muscle is actively engaged in controlling standing balance. However, there is evidence to suggest that GVS may be able to modulate the activity of lower limb muscles when subjects are not in a free-standing situation. The purpose of this review is to examine 2 studies from our laboratory that examined the effects of GVS on the lower limb motoneuron pool. For instance, a monopolar monaural galvanic stimulus modified the amplitude of the ipsilateral soleus H-reflex. Furthermore, bipolar binaural GVS significantly altered the onset of activation and the initial firing frequency of gastrocnemius motor units. The following paper examines the effects of GVS on muscles that are not being used to maintain balance. We propose that GVS is modulating motor output by influencing the activity of presynaptic inhibitory mechanisms that act on the motoneuron pool.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 | 0.001 |
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".