Impaired corticomuscular coherence during isometric elbow flexion contractions in humans with cervical spinal cord injury
Bibliographic record
Abstract
After spinal cord injury (SCI), the reorganization of the neuromuscular system leads to increased antagonist muscles' co-activation-that is, increased antagonist vs. agonist muscles activation ratio-during voluntary contractions. Increased muscle co-activation is supposed to result from reduced cortical influences on spinal mechanisms inhibiting antagonist muscles. The assessment of the residual interactions between cortical and muscles activity with corticomuscular coherence (CMC) in participants with SCI producing different force levels may shed new lights on the regulation of muscle co-activation. To achieve this aim, we compared the net joint torque, the muscle co-activation and the CMC ~ 10 and ~ 20 Hz with both agonist and antagonist muscles in participants with SCI and healthy participants performing actual isometric elbow flexion contractions at three force levels. For all participants, overall CMC and muscle co-activation decreased with the increase in the net joint torque, but only CMC ~ 10 Hz was correlated with muscle co-activation. Participants with SCI had greater muscle co-activation and lower CMC ~ 10 Hz, at the highest force levels. These results emphasize the importance of CMC as a mechanism that could take part in the modulation of muscle co-activation to maintain a specific force level. Lower CMC ~ 10 Hz in SCI participants may reflect the decreased cortical influence on spinal mechanisms, leading to increased muscle co-activation, although plasticity of the corticomuscular coupling seems to be preserved after SCI to modulate the force level. Clinically, the CMC may efficiently evaluate the residual integrity of the neuromuscular system after SCI and the effects of rehabilitation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".