Critical considerations of the contribution of the corticomotoneuronal pathway to central fatigue
Bibliographic record
Abstract
Neural drive originating in higher brain areas reaches exercising limb muscles through the corticospinal-motoneuronal pathway, which links the motor cortex and spinal motoneurones. The properties of this pathway have frequently been observed to change during fatiguing exercise in ways that could influence the development of central fatigue (i.e. the progressive reduction in voluntary muscle activation). However, based on differences in motor cortical and motoneuronal excitability between exercise modalities (e.g. single-joint vs. locomotor exercise), there is no characteristic response that allows for a categorical conclusion about the effect of these changes on functional impairments and performance limitations. Despite the lack of uniformity in findings during fatigue, there is strong evidence for marked 'inhibition' of motoneurones as a direct result of voluntary drive. Endogenous forms of neuromodulation, such as via serotonin released from neurones, can directly affect motoneuronal output and central fatigue. Exogenous forms of neuromodulation, such as brain stimulation, may achieve a similar effect, although the evidence is weak. Non-invasive transcranial direct current stimulation can cause transient or long-lasting changes in cortical excitability; however, variable results across studies cast doubt on its claimed capacity to enhance performance. Furthermore, with these studies, it is difficult to establish a cause-and-effect relationship between brain responsiveness and exercise performance. This review briefly summarizes changes in the corticomotoneuronal pathway during various types of exercise, and considers the relevance of these changes for the development of central fatigue, as well as the potential of non-invasive brain stimulation to enhance motor cortical excitability, motoneuronal output and, ultimately, exercise performance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".