Transcranial Magnetic Stimulation Inter‐Pulse Interval Does Not Influence Corticospinal Excitability to the Biceps Brachii During Submaximal Isometric Elbow Flexion
Bibliographic record
Abstract
Previous research on resting muscles has shown that inter-pulse interval (IPI) duration influences transcranial magnetic stimulation (TMS) responses, which can introduce serious confounding variables into investigations if not accounted for. However, it is far less clear how IPI influences TMS responses in active muscles. Thus, the purpose of this study was to examine the relationship between IPI and corticospinal excitability during submaximal isometric elbow flexion. Corticospinal excitability to the biceps and triceps brachii was measured using motor evoked potentials (MEPs) elicited via TMS. Stimulation intensity was set to 120% of the biceps brachii's active motor threshold while participants produced 10% of their biceps' maximal muscle activity. TMS was delivered as separate trains of five stimulations, with experimental conditions differing between IPIs of 4, 6, 8, 10, 12 or 14 s. Results demonstrated that IPI had no influence on MEP amplitudes for either the biceps or triceps. However, when MEP amplitudes were expressed as a unitless ratio to pre-stimulus muscle activity, a main effect of time was found for the biceps; MEP amplitudes progressively decreased with successive stimulations (MEP 1:32.8 ± 5.9; MEP 5:27.7 ± 4.3, p < 0.05). These results suggest that IPI is unlikely to represent a confounding variable in TMS studies utilizing active contractions. However, studies looking to compare the amplitudes of single MEPs over time should be aware of the possibility that amplitudes may decrease with continuous stimulation. Future research should seek to examine even longer IPIs and explore the influence of higher stimulation intensities.
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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 | 0.002 |
| 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".