Effects of Lactate on Corticospinal Excitability: A Scoping Review
Bibliographic record
Abstract
Aerobic exercise has been shown to impact corticospinal excitability (CSE), however the mechanism(s) by which this occurs is unclear. Some evidence suggests an increase in blood lactate concentration resulting from exercise may be what is driving these changes in corticospinal excitability. The extent of literature examining this effect and whether it is consistent across the literature is unknown. As such, the objective of this scoping review was to summarize the existing literature examining the effect of lactate on corticospinal excitability and to determine any trend(s) in the effect. Embase, CINAHL, Medline, SPORTDiscus, and PsycInfo were systematically searched to retrieve original research reporting on blood lactate concentration and measures of corticospinal excitability associated with aerobic or high intensity interval exercise. Two reviewers independently determined study eligibility, and one reviewer extracted data from all eligible studies. The database search yielded 717 papers of which 9 were determined eligible. Multiple studies in which participants completed high intensity and/or exhaustive exercise showed a correlation between large increases in blood lactate concentration and increased corticospinal excitability, however several other studies noted no difference in corticospinal excitability following an increase in blood lactate concentration. This review showed that the existing body of literature is small and highly variable in both methods and results, therefore we can draw limited conclusions about the role of lactate, however based on the evidence available lactate does not appear to be the key player in the modulation of CSE. In addition, evidence from other literature supports moderate intensity aerobic exercise as a modulator of neuroplasticity, suggesting that there may be other key factors contributing to the changes in the brain following exercise.
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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 | 0.011 | 0.061 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.014 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".