Effect of caffeine on the neuromuscular system — potential as an ergogenic aid
Bibliographic record
Abstract
The ergogenic effect of caffeine on endurance exercise performance is multifactorial; however, there is evidence for an effect on both the central nervous system and the excitation-contraction coupling of skeletal muscle. The increase in exercise performance seen following intracerebroventrical caffeine injection in rats provides strong evidence for a central ergogenic effect. The central ergogenic effect is not likely related to the ability of caffeine to promote wakefulness, but could be due to an increase in the pain and effort perception threshold. There is no evidence that caffeine alters peripheral nerve conduction velocity or neuromuscular transmission, and 1 study showed that motor unit synchronization was not altered by caffeine. Studies have also shown that caffeine can have a direct effect on skeletal muscle that could be ergogenic. For example, patients with high cervical spinal cord lesions showed improvements in stimulated contractile force during cycling, in spite of the fact that they have no peripheral pain input and no sympathetic nervous system response. Two studies have found a potentiation of force production during submaximal stimulation intensities, and 1 found that the M-wave amplitude was not altered by caffeine. Together, these studies suggest that caffeine can enhance contractile force during submaximal contractions by potentiating calcium release from the ryanodine receptor, not by altering sarcoplasmic excitability. Furthermore, the potentiation of force during submaximal electrical stimulation is identical in habitual and nonhabitual caffeine consumers. In summary, the ergogenic effects of caffeine during endurance activity are mediated partly by enhanced contractile force and partly by a reduction in perceived exertion, possibly though a blunting of effort and (or) pain.
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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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".