The effect of fatigue from different types of repetitive maximal-effort concentric elbow extensions on cortical and motoneuronal excitability
Bibliographic record
Abstract
Although fatigue is known to be task-dependent, the neuromuscular mechanisms underlying fatigue from repetitive, dynamic contractions remain less understood than those associated with isometric tasks. This dissertation examined the effects of fatigue on cortical and motoneuronal excitability using three types of maximal-effort, repetitive, dynamic contractions of the elbow extensors: unconstrained velocity with a resistance of 30% maximal voluntary isometric contraction (MVC) torque (Chapter 2), as well as 40°/s (Chapter 3) and 240°/s (Chapter 4) isokinetic contractions in females and males. Fatigue was characterized by reductions in peak power and MVC torque. Neuronal excitability of the triceps brachii was assessed using responses recorded with surface electromyography: motor evoked potentials (MEPs), cervicomedullary motor evoked potentials (CMEPs), and maximal compound muscle action potentials (Mmax). Cortical (MEP/CMEP), motoneuronal (CMEP/Mmax), and peripheral excitability (Mmax area) were evaluated pre-fatigue (PRE), during the fatigue task and at task termination, as well as throughout 10 min of recovery. Despite evidence of reduced power and MVC torque, cortical excitability was elevated immediately following the fatiguing task (Chapters 2) or during recovery (Chapters 3 and 4). Motoneuronal excitability was either unchanged (Chapters 2) or reduced (Chapters 3 and 4) during the fatigue task and did not recover in some cases (Chapters 3 and 4). Peripheral excitability remained mostly unchanged across protocols (Chapters 2 and 3). In some instances, neuronal excitability was altered differently in females than males by fatigue and recovery (Chapter 4). These findings indicate that fatigue induced by repetitive, concentric elbow extensions resulted in divergent time courses of cortical and motoneuronal excitability adaptations. Despite a fatigue-related increased cortical excitability, motoneuronal excitability was blunted. Collectively, this dissertation highlights the complexity of fatigue-related alterations in neuromuscular function and neuronal excitability for dynamic contractions. Additionally, this dissertation emphasizes the importance of considering the task-dependent nature of fatigue, especially as it relates to biological sex, contraction type, velocity, and recovery when evaluating and interpreting corticospinal excitability assessments.
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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 | 0.000 |
| 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".