Distribution and density of contacts from noradrenergic and serotonergic boutons on the dendrites of neck flexor motoneurons in the adult cat
Bibliographic record
Abstract
Serotonergic (5-HT) and noradrenergic (NA) input to spinal motoneurons is essential for generating plateau potentials and self-sustained discharges. Extensor motoneurons are densely innervated by 5-HT and NA synapses and have robust plateau potentials and self-sustained discharges. Conversely, plateau potentials and self-sustained discharges are very rare in flexor motoneurons. The most likely reasons for this difference are that flexor motoneurons have few 5-HT and NA synapses and/or they are distributed distant to the channels responsible for plateau potentials and self-sustained discharges. However, the distribution of 5-HT and NA synapses on flexor motoneurons is unknown. Here we describe the distribution and density of 5-HT and NA synapses on motoneurons that innervate the flexor neck muscle, rectus capitis anterior (RCA), in the adult cat. Using a combination of intracellular staining, fluorescent immunohistochemistry, and 3D reconstruction techniques, we found that 5-HT and NA synapses are widely distributed throughout the dendritic trees of RCA motoneurons, albeit with a strong bias to small-diameter dendrites and to medial dendrites in the case of NA contacts. The number of 5-HT and NA contacts per motoneuron ranged, respectively, from 381 to 1,430 and from 642 to 1,382, which is 2.3- and 1.4-fold less than neck extensor motoneurons (Montague et al., J Comp Neurol 2013;521:638-656). These results suggest that 5-HT and NA synapses on flexor motoneurons may provide a powerful means of amplifying synaptic currents without incurring plateau potentials or self-sustained discharges. This feature is well suited to meet the biomechanical demands imposed on flexor muscles during different motor tasks.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".