Motor point stimulation induces more robust F‐waves than peripheral nerve stimulation
Bibliographic record
Abstract
The F-wave is a motor response induced by electrical stimulation of peripheral nerves via the antidromic firing of motor nerves, which reflects the motoneuron excitability. To induce F-waves, transcutaneous peripheral nerve stimulation (PNS) is used, which activates nerve branches via transcutaneous electrodes over the nerve branches. An alternative method to activate peripheral nerves, that is, motor point stimulation (MPS), which delivers electrical stimulation over the muscle belly, has not been used to induce F-waves. In our previous studies, we observed that MPS induced F-wave-like responses, that is, motor responses at the latency of F-waves at a supramaximal stimulation. Here, we further investigated the F-wave-like responses induced by MPS in comparison with PNS in the soleus muscle. Thirteen individuals participated in this study. We applied MPS and PNS on the participant's left soleus muscle. Using a monopolar double-pulse stimulation, the amplitude of the second H-reflex induced by PNS decreased, whereas the amplitude of the motor response at the F-wave latency induced by MPS did not decrease. These results suggest that the motor response at the F-wave latency induced by MPS was not an H-reflex but an F-wave. We also found that the F-wave induced by MPS had a greater amplitude and higher persistence and caused less pain when compared with the F-waves induced using PNS. We conclude that MPS evokes antidromic firing inducing F-waves more consistently compared with PNS.
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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 | 0.001 |
| 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) | 0.003 | 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".