No changes in corticospinal excitability, biochemical markers, and working memory after six weeks of high‐intensity interval training in sedentary males
Bibliographic record
Abstract
A single bout of aerobic exercise modulates corticospinal excitability, intracortical circuits, and serum biochemical markers such as brain-derived neurotrophic factor (BDNF) and insulin-like growth factor 1 (IGF-1). These effects have important implications for the use of exercise in neurorehabilitation. Here, we aimed to determine whether increases in cardiorespiratory fitness (CRF) induced by 18 sessions of high-intensity interval training (HIIT) over 6 weeks were accompanied by changes in corticospinal excitability, intracortical excitatory and inhibitory circuits, serum biochemical markers and working memory (WM) capacity in sedentary, healthy, young males. We assessed motor evoked potential (MEP) recruitment curves for the first dorsal interosseous (FDI) both at rest and during tonic contraction, intracortical facilitation (ICF), and short-interval intracortical inhibition (SICI) using transcranial magnetic stimulation (TMS). We also examined serum levels of BDNF, IGF-1, total and precursor (pro) cathepsin B (CTSB), as well as WM capacity. Compared to pretraining, CRF was increased and ICF reduced after the HIIT intervention, but there were no changes in corticospinal excitability, SICI, BDNF, IGF-1, total and pro-CTSB, and WM capacity. Further, greater CRF gains were associated with larger decreases in total and pro-CTSB and, only in Val/Val carriers, with larger increases in SICI. Our findings confirm that HIIT is efficacious in promoting CRF and show that corticospinal excitability, biochemical markers, and WM are unchanged after 18 HIIT bouts in sedentary males. Understanding how aerobic exercise modulates M1 excitability is important in order to be able to use exercise protocols as an intervention, especially in rehabilitation following brain injuries.
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 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".