Neural adaptations to fatigue: implications for muscle strength and training
Bibliographic record
Abstract
PURPOSE: This paper investigates the neural mechanisms responsible for the increase in strength that occurs during serial isometric contractions. METHODS: A three-session design was used. Thirteen subjects (N = 13) were asked to perform five maximal isometric elbow extension strength trials to serve as baseline. After a 5-min rest, the subjects were administered a 30-trial fatigue protocol. This process was repeated two more times at 2-wk intervals. Elbow extension torque and surface electromyography (EMG) of the triceps and biceps brachii were monitored concurrently. The criterion measures were elbow extension torque, root-mean-square EMG amplitude, and mean power frequency (MPF). RESULTS: Intraclass reliability ranged from good to excellent. Within each experimental session, the fatigue protocol resulted in a decrease in maximal isometric elbow extension torque as well as biceps and triceps EMG amplitude and MPF (P < 0.05). However, the mean of the 30 trials and the magnitude of the linear decrease in elbow extension torque increased across the three sessions (P < 0.05). Biceps and triceps EMG amplitude increased and MPF decreased as the number of sessions increased (P < 0.05). CONCLUSIONS: These findings suggest that the fatigue protocol served as a training stimulus to down regulate motor-unit firing frequency.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".