Effect of blood flow occlusion on corticospinal excitability during sustained low-intensity isometric elbow flexion
Bibliographic record
Abstract
Blood flow occlusion (BFO) has been used to study the influence of group III/IV muscle afferents after fatiguing exercise, but it is unknown how BFO-induced activity of these afferents affects motor cortical and motoneuronal excitability during low-intensity exercise. Therefore, the purpose of this study was to assess the acute effect of BFO on peripheral [maximal M wave (Mmax)], spinal [cervicomedullary motor evoked potential (CMEP) normalized to Mmax], and motor cortical [motor evoked potential (MEP) normalized to CMEP] excitability. Nine healthy men completed a sustained isometric contraction of the elbow flexors at 20% of maximal force under three conditions: 1) contractile failure with BFO, 2) a time-matched trial without restriction [free flow (FFiso)], and 3) contractile failure with free flow (FFfail). Time to failure for BFO (and FFiso) were ~80% shorter than that for FFfail ( P < 0.05). For FFfail and FFiso, Mmax area decreased ~17% and ~7%, respectively ( P < 0.05), with no change during BFO. CMEP/Mmax area increased ~226% and ~80% during BFO and FFfail, respectively ( P < 0.05), with no change during FFiso ( P > 0.05). The increase in normalized CMEP area was greater for BFO and FFfail compared with FFiso and for BFO compared with FFfail. MEP/CMEP area was not different among the protocols ( P > 0.05) and increased ~64% with time ( P < 0.05). It is likely that group III/IV muscle afferent feedback to the spinal cord modulates the large increase in motoneuronal excitability for the BFO compared with FFfail and FFiso protocols. NEW & NOTEWORTHY We have observed how blood flow occlusion modulates motor cortical, spinal, and peripheral excitability during and immediately after a sustained low-intensity isometric elbow flexion contraction to failure. We conclude that blood flow occlusion causes a greater and more rapid increase in motoneuronal excitability.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".