Motor unit recruitment when neuromuscular electrical stimulation is applied over a nerve trunk compared with a muscle belly: triceps surae
Bibliographic record
Abstract
Neuromuscular electrical stimulation (NMES) can be delivered over a nerve trunk or muscle belly and can generate contractions by activating motor (peripheral pathway) and sensory (central pathway) axons. In the present experiments, we compared the peripheral and central contributions to plantar flexion contractions evoked by stimulation over the tibial nerve vs. the triceps surae muscles. Generating contractions through central pathways follows Henneman's size principle, whereby low-threshold motor units are activated first, and this may have advantages for rehabilitation. Statistical analyses were performed on data from trials in which NMES was delivered to evoke 10-30% maximum voluntary torque 2-3 s into the stimulation (Time(1)). Two patterns of stimulation were delivered: 1) 20 Hz for 8 s; and 2) 20-100-20 Hz for 3-2-3 s. Torque and soleus electromyography were quantified at the beginning (Time(1)) and end (Time(2); 6-7 s into the stimulation) of each stimulation train. H reflexes (central pathway) and M waves (peripheral pathway) were quantified. Motor unit activity that was not time-locked to each stimulation pulse as an M wave or H reflex ("asynchronous" activity) was also quantified as a second measure of central recruitment. Torque was not different for stimulation over the nerve or the muscle. In contrast, M waves were approximately five to six times smaller, and H reflexes were approximately two to three times larger during NMES over the nerve vs. the muscle. Asynchronous activity increased by 50% over time, regardless of the stimulation location or pattern, and was largest during NMES over the muscle belly. Compared with NMES over the triceps surae muscles, NMES over the tibial nerve produced contractions with a relatively greater central contribution, and this may help reduce muscle atrophy and fatigue when NMES is used for rehabilitation.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".