Spinal excitability is increased in the torque-depressed isometric steady state following active muscle shortening
Bibliographic record
Abstract
Torque depression (TD) is the reduction in steady-state isometric torque following active muscle shortening when compared with a purely isometric contraction at the same muscle length and level of activation. The purpose of the present study was to assess spinal and supraspinal excitability in the TD state during submaximal contractions of the dorsiflexors. Eleven young (24 ± 2 yrs) males performed 16 contractions at a constant level of electromyographic activity (40% of maximum). Half of the contractions were purely isometric (8 s at an ankle angle of 100°), whereas the other half induced TD (2 s isometric at 140°, a 1 s shortening phase at 40° s−1and 5 s at 100°). Motor evoked potentials (MEPs), cervicomedullary motor evoked potentials (CMEPs) and compound muscle action potentials (M-waves) were recorded from tibialis anterior during the TD steady-state and purely isometric contractions. When compared with values in the purely isometric condition, following active shortening, there was a 13% decrease in torque (p < 0.05), with a 10% increase in normalized CMEP amplitude (CMEP/Mmax) (p < 0.05) and no change in normalized MEP amplitude (MEP/CMEP) in the TD state (p > 0.05). These findings indicate that during voluntary contractions in the TD state, the history-dependent properties of muscle can increase spinal excitability and influence voluntary control of submaximal torque production.
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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) | 0.001 | 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".