The time dependent nature of triphasic EMG generation
Bibliographic record
Abstract
Muscles involved in rapid, targeted movements often display a triphasic (Agonist-Antagonist-Agonist) EMG pattern. Some authors have suggested the entire pattern is programmed in advance and initiated as a unit (e.g. Wadman et al., 1979). However evidence from TMS studies has suggested that the Antagonist (ANT) may be prepared separately from Agonist-1 (AG1) (MacKinnon & Rothwell, 2000) with execution of the bursts occurring serially (Irlbacher et al., 2006). Using a startling acoustic stimulus (SAS), which triggers prepared motor commands at short latency (Carlsen et al., 2012), we previously showed independent ANT triggering for a short amplitude movement by presenting the SAS at AG1 onset (Forgaard et al., 2012). Triggering by startle did not occur for longer movements, presumably because the ANT was not sufficiently prepared at this relatively early time point. In the present study we further investigated the time course of ANT readiness by presenting a SAS later in a longer movement. Eleven participants performed ballistic elbow extensions to a 60° target. In 21% of trials a SAS was delivered randomly either with the “go” signal, at AG1 onset, or 70 ms before estimated ANT onset. ANT was triggered early when the SAS was delivered 70 ms prior to its normal onset (p < .05), but not when it was presented with the “go” signal, or at AG1 onset. The present data support the suggestion that components of the triphasic pattern are generated serially and the time at which the ANT burst is fully prepared depends on movement amplitude.Acknowledgments: NSERC
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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) | 0.005 | 0.001 |
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".