Corticospinal control of antagonistic muscles in the cat
Bibliographic record
Abstract
We recently suggested that movement-related inter-joint muscle synergies are recruited by selected excitation and selected release from inhibition of cortical points. Here we asked whether a similar cortical mechanism operates in the functional linking of antagonistic muscles. To this end experiments were done on ketamine-anesthetized cats. Intracortical microstimulation (ICMS) and intramuscular electromyographic recordings were used to find and characterize wrist, elbow and shoulder antagonistic motor cortical points. Simultaneous ICMS applied at two cortical points, each evoking activity in one of a pair of antagonistic muscles, produced co-contraction of antagonistic muscle pairs. However, we found an obvious asymmetry in the strength of reciprocal inhibition; it was always significantly stronger on physiological extensors than flexors. Following intravenous injection of a single bolus of strychnine, a cortical point at which only a physiological flexor was previously activated also elicited simultaneous activation of its antagonist. This demonstrates that antagonistic corticospinal neurons are closely grouped, or intermingled. To test whether releasing a cortical point from inhibition allows it to be functionally linked with an antagonistic cortical point, one of three GABA(A) receptor antagonists, bicuculline, gabazine or picrotoxin, was injected iontophoretically at one cortical point while stimulation was applied to an antagonistic cortical point. This coupling always resulted in co-contraction of the represented antagonistic muscles. Thus, antagonistic motor cortical points are linked by excitatory intracortical connections held in check by local GABAergic inhibition, with reciprocal inhibition occurring at the spinal level. Importantly, the asymmetry of cortically mediated reciprocal inhibition would appear significantly to bias muscle maps obtained by ICMS in favor of physiological flexors.
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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) | 0.001 | 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".