Force Control and Motor Unit Firing Behavior Following Mental Fatigue in Young Female and Male Adults
Bibliographic record
Abstract
PURPOSE: The neuromuscular mechanisms leading to impaired motor performance in the presence of mental fatigue remain unclear. It is also unknown if mental fatigue differentially impacts motor performance in males and females. The purpose of this study was to assess the impact of mental fatigue on force production and motor unit firing behavior in males and females. METHODS: Nineteen participants performed 10-s isometric dorsiflexion (DF) contractions at 20 and 50% maximum voluntary contraction (MVC) before, during, and after completing 22 min of the psychomotor vigilance task (PVT), to induce mental fatigue. DF force and indwelling motor unit firing behavior of the tibialis anterior was measured prior to and immediately following the PVT, and within the first and final minutes of the PVT. RESULTS: Force steadiness and motor unit firing rate (MUFR) variability did not change during or following the PVT at either contraction intensity (p ≥ 0.16). Overall, females had more variability than males in MUFR during the 20% MVCs (15.98 ± 2.19 vs 13.64 ± 2.19%, p = 0.03), though no sex differences were identified during the 50% MVCs (p = 0.20). Mean MUFR decreased following mental fatigue in both sexes in the 20% MVC condition (14.79 ± 3.20 vs 12.92 ± 2.53 Hz, p = 0.02), but only in males during the 50% MVC condition (18.65 ± 5.21 vs 15.03 ± 2.60 Hz, p = 0.01). CONCLUSIONS: These results suggest possible sex and contraction intensity-specific neuromuscular changes in the presence of mental fatigue.
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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".