Increased corticospinal excitability prior to arm cycling is due to enhanced supraspinal but not spinal motoneurone excitability
Bibliographic record
Abstract
Human studies have not assessed supraspinal or spinal motoneurone excitability in the quiescent state prior to a rhythmic and alternating cyclical motor output. The purpose of the current study was to determine whether supraspinal and (or) spinal motoneurone excitability was modulated in humans prior to arm cycling when compared with rest with no intention to move. We hypothesized that corticospinal excitability would be enhanced prior to arm cycling due, in part, to increased spinal motoneurone excitability. Supraspinal and spinal motoneurone excitability were assessed via transcranial magnetic stimulation (TMS) of the motor cortex and transmastoid stimulation of the corticospinal tract, respectively. Surface electromyography recordings of TMS motor evoked potentials (MEPs) and cervicomedullary MEPs (CMEPs) were made from the relaxed biceps brachii muscle prior to rhythmic arm cycling and at rest with no intention to move. The amplitude of the MEPs was greater (mean increase: +9.8% of maximal M wave; p = 0.006) and their onset latencies were shorter (mean decrease: -1.5 ms; p < 0.05) prior to cycling when compared with rest. The amplitudes of the CMEPs at any of 3 stimulation intensities were not different between conditions. We conclude that premovement enhancement of corticospinal excitability is greater prior to arm cycling than at rest because of increases in supraspinal but not spinal motoneurone excitability.
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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) | 0.002 | 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".