Decreased excitability of motor axons contributes substantially to contraction fatigability during neuromuscular electrical stimulation
Bibliographic record
Abstract
The present study was designed to (i) determine the time course of changes in motor axon excitability during and after neuromuscular electrical stimulation (NMES); and (ii) characterize the relationship between contraction fatigability, NMES frequency, and changes at the axon, neuromuscular junction, and muscle. Eight neurologically intact participants attended 3 sessions. NMES was delivered over the common peroneal nerve at 20, 40, or 60 Hz for 8 min (0.3 s “on”, 0.7 s “off”). Threshold tracking was used to measure changes in axonal excitability. Supramaximal stimuli were used to assess neuromuscular transmission and force-generating capacity of the tibialis anterior muscle. Torque decreased by 49% and 62% during 8 min of 40 and 60 Hz NMES, respectively. Maximal twitch torque decreased only during 60 Hz NMES. Motor axon excitability decreased by 14%, 27%, and 35% during 20, 40, and 60 Hz NMES, respectively. Excitability recovered to baseline immediately (20 Hz) and at 2 min (40 Hz) and 4 min (60 Hz) following NMES. Overall, decreases in axonal excitability best predicted how torque declined over 8 min of NMES. During NMES, motor axons become less excitable and motor units “drop out” of the contraction, contributing substantially to contraction fatigability and its dependence on NMES frequency. Novelty: The excitability of motor axons decreased during NMES in a frequency-dependent manner. As excitability decreased, axons failed to reach threshold and motor units dropped out of the contraction. Overall, decreased excitability best predicted how torque declined and thus is a key contributor to fatigability during NMES.
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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 | 0.000 | 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".