Developmental changes in motor unit activity patterns: child-adult comparison using discrete motor unit analysis
Bibliographic record
Abstract
Using global surface electromyography (sEMG) and the sEMG threshold it has been suggested that children activate their type-II motor unit (MU) to a lesser extent compared with adults. However, when age-related differences in discrete MU activation are examined using sEMG decomposition this phenomenon is not observed. Furthermore, findings from these studies are inconsistent and conflicting. Therefore, the purpose of this study was to examine differences in discrete MU activation of the vastus lateralis (VL) between boys and men during moderate-intensity knee extensions. Seventeen boys and 20 men completed two laboratory sessions. Following a habituation session, maximal voluntary isometric knee extension (MVIC) torque was determined before completing trapezoidal contractions at 70% MVIC. sEMG of the VL was captured and mathematically decomposed into individual MU action potential trains. Motor unit action potential amplitude (MUAPamp), recruitment threshold (RT), and MU firing rates (MUFR) were calculated. We observed that MUAPamp–RT slope was steeper in men compared with boys ( p < 0.05) even after accounting for fat thickness and quadriceps muscle depth. The mean MUFR and y-intercept of the MUFR–RT relationship were significantly ( p < 0.001) lower in boys than in men. The slope of the MUFR–RT relationship tended to be steeper in men, but the differences did not reach statistical significance ( p = 0.056). Overall, our results suggest that neural strategies used to produce torque are different among boys and men. Such differences may be related, in part, to boys’ lower MUFR and lesser ability to activate their higher-threshold MUs. Although, other factors (e.g., muscle composition) likely also play a role.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".