Hypothesis: Hughlings Jackson and presynaptic inhibition: is there a big picture?
Bibliographic record
Abstract
Presynaptic inhibition is a very powerful inhibitory mechanism and, despite many detailed studies, its purpose is still only partially understood. One accepted function is that, by reducing afferent inflow to the spinal cord and brainstem, the tonic level of presynaptic inhibition prevents sensory systems from being overloaded. A corollary of this function is that much of the incoming sensory data from peripheral receptors must be redundant, and this conclusion is reinforced by observations on patients with sensory neuropathies or congenital obstetric palsy in whom normal sensation may be preserved despite loss of sensory fibers. The modulation of incoming signals by presynaptic inhibition has a further function in operating a "gate" in the dorsal horn, thereby determining whether peripheral stimuli are likely to be perceived as painful. On the motor side, the finding that even minimal voluntary movement of a single toe is associated with widespread inhibition in the lumbosacral cord points to another function for presynaptic inhibition: to prevent reflex perturbations from interfering with motor commands. This last function, together with the normal suppression of muscle and cutaneous reflex activity at rest, is consistent with Hughlings Jackson's concept of evolving neural hierarchies, with each level inhibiting the one below it.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".