Sympathetic neural activation: an ordered affair
Bibliographic record
Abstract
Is there an ordered pattern in the recruitment of postganglionic sympathetic neurones? Using new multi-unit action potential detection and analysis techniques we sought to determine whether the activation of sympathetic vasomotor neurones during stress is governed by the size principle of recruitment. Multi-unit postganglionic sympathetic activity (fibular nerve) was collected from five male subjects at rest and during periods of elevated sympathetic stress (end-inspiratory apnoeas; 178 ± 37 s(mean ± S.D.)). Compared to baseline (0.24 ± 0.04 V), periods of elevated stress resulted in augmented sympathetic burst size (1.34 ± 0.38 V, P < 0.05). Increased burst size was directly related to both the number of action potentials within a multi-unit burst of postganglionic sympathetic activity (r = 0.88 ± 0.04, P < 0.001 in all subjects), and the amplitude of detected action potentials (r = 0.88 ± 0.06, P < 0.001 in all subjects). The recruitment of larger, otherwise silent, neurons accounted for approximately 74% of the increase in detected action potentials across burst sizes. Further, action potential conduction velocities (inverse of latencies) were increased as a function of action potential size (R² = 0.936, P = 0.001). As axon diameter is positively correlated with action potential size and conduction velocity, these data suggest that the principle of ordered recruitment based on neuronal size applies to postganglionic sympathetic vasomotor neurones. This information may be pertinent to our understanding of reflex-specific recruitment strategies in postganglionic sympathetic nerves, patterns of vasomotor control during stress, and the malleability of sympathetic neuronal properties and recruitment in health and disease.
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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) | 0.001 | 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".