Modulation of corticospinal output in agonist and antagonist proximal arm muscles during motor preparation
Bibliographic record
Abstract
Previous studies have shown modulation of corticospinal output of the agonist muscle when a known-movement is prepared but withheld until a response signal appearance, reflecting motor preparation processes. However, modulation in the antagonist muscles has not been described, despite the fact that reaching movements require precise coordination between the activation of agonist and antagonist muscles. In this study, participants performed an instructed-delay reaction time (RT) task, with randomized elbow flexion and extension movements. The aim was to assess the time course modulation of corticospinal output in two antagonist muscles, by simultaneously quantified the amplitude of motor evoked potentials (MEPs) in biceps brachii and triceps brachii, and the amplitude and direction of elbow movements evoked by transcranial magnetic stimulation (TMS). Depending on the prepared movement direction, a specific modulation of corticospinal output was observed, MEPs and TMS-evoked movements amplitude being relatively greater for extension compared to flexion. At the end of motor preparation, a decrease in MEPs amplitude was observed for both biceps brachii and triceps brachii, regardless of the prepared movement direction. In contrast, the probability of evoking movement in the flexion direction and the amplitude of TMS-evoked movement decreased at the end of preparation for flexion, but not for extension. Together, these results confirm the existence of inhibitory processes at the end of the motor preparation, probably to avoid a premature motor response. Moreover, they provide evidence of differences in the corticospinal control of elbow flexor and extensor muscles with patterns of modulation that are not necessarily reciprocal during motor preparation.
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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) | 0.000 | 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".