Fatigue Modulates The Effect Of Group III/IV Muscle Afferents On GABAB-Mediated Inhibition And Corticospinal Excitability
Bibliographic record
Abstract
PURPOSE: To investigate the influence of group III/IV muscle afferents on GABAB-mediated long-interval inhibition (LII) during cycling exercise in the absence and presence of locomotor muscle fatigue. METHODS: Nine recreationally active males performed brief, non-fatiguing (NFC; 30 s) and fatiguing (FC; 5 min) cycling exercise (80% Wpeak) under control-conditions (CTRL) and with lumbar intrathecal fentanyl (FENT) impairing feedback from group III/IV leg muscle afferents. Single and paired transcranial magnetic stimulation (TMS, TMS-TMS) and single and paired TMS-cervicomedullary stimulation (CMS, TMS-CMS) were used during NFC and at the start and end of FC to evaluate cortical versus spinal contributions to LII (LIITMS, LIICMS). RESULTS: While fentanyl blockade did not alter motor-evoked potentials (MEPs) during NFC, cervicomedullary-evoked motor potentials (CMEPs) were 15±10% higher (P<0.05), resulting in a 7±5% decrease in MEP/CMEP in FENT compared to CTRL (P<0.05). Furthermore, fentanyl blockade during NFC increased LIITMS by 26±15% (P<0.05) without affecting LIICMS (P=0.3). During FC in CTRL, MEPs remained unchanged during the 5 minutes of exercise whereas CMEPs increased by 12±6% (P<0.05) resulting in an 8±3% decrease in MEP/CMEP (P<0.05). This paralleled a 33±11% increase in LIITMS (P<0.05), but no change in LIICMS. During FC in FENT, MEPs, CMEPs, LIITMS and LIICMS remained unchanged (P>0.2). CONCLUSION: These findings suggest that in the absence of fatigue, group III/IV muscle afferents may facilitate the excitability of motor cortical cells by limiting the activation of GABAB intracortical inhibitory interneurons. In contrast, in the presence of fatigue, these afferents may disfacilitate the excitability of motor cortical cells by enhancing the activation of GABAB intracortical inhibitory interneurons.
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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) | 0.002 | 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".