Recovery of proprioceptive feedback from nerve crush
Bibliographic record
Abstract
Sensorimotor functions are restored by peripheral nerve regeneration with greater success following injuries that crush rather than sever the nerve. Better recovery following nerve crush is commonly attributed to superior reconnection of regenerating axons with their original peripheral targets. The present study was designed to estimate the fraction of stretch reflex recovery attributable to functional recovery of regenerated spindle afferents. Recovery of the spindle afferent population was estimated from excitatory postsynaptic potentials evoked by muscle stretch (strEPSPs) in motoneurons. These events were measured in cats that were anaesthetized, so that recovery of spindle afferent function, including both muscle stretch encoding and monosynaptic transmission, could be separated from other factors that act centrally to influence muscle stretch-evoked excitation of motoneurons. Recovery of strEPSPs to 70% of normal specified the extent of overall functional recovery by the population spindle afferents that regained responsiveness to muscle stretch. In separate studies, we examined recovery of the stretch reflex in decerebrate cats, and found that it recovered to supranormal levels after nerve crush. The substantial disparity in recovery between strEPSPs and stretch reflex led us to conclude that factors in addition to recovery of spindle afferents make a large contribution in restoring the stretch reflex following nerve crush.
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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) | 0.002 | 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".