Somatosensory paths proceeding to spinal cord and brain — centripetal and centrifugal control for human movement
Bibliographic record
Abstract
The flow of fast-conducting somatosensory information proceeding from the human leg, and entering sensorimotor control processes, is modulated according to the demands of limb movement. Both centripetal (proceeding in from sensory receptor discharge) and centrifugal (proceeding out from motor control centres) convergences can cause modulation, as seen in human, dog, and cat studies. Spinal H-reflexes appear to be strongly centripetally modulated in magnitude, as do initial somatosensory-evoked potentials recorded from the scalp following transmission in fast-conducting afferents from the leg. From the brain and from locomotor pattern-generators, there is also centrifugal control onto fast-conducting somatosensory pathways from the leg, both serving spinal reflexes and ascending to the brain. One expression of the centrifugal control appears to be pattern-generator modulation of cutaneous reflexes. Centrifugal control also can be seen premovement, as spinal H-reflex facilitation. Further, it can be observed as reduction of reception at somatosensory cerebral cortex, when motor learning has occurred or when stimuli are less salient for the task. Fourteen research developments have been identified that involve the generalizability of effects, specific mechanisms, and somatosensory modulation in predictive control.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".