Physiological characterization, localization and synaptic inputs of bursting and nonbursting neurons in the trigeminal principal sensory nucleus of the rat
Bibliographic record
Abstract
A population of neurons in the trigeminal principal sensory nucleus (NVsnpr) fire rhythmically during fictive mastication induced in the in vivo rabbit. To elucidate whether these neurons form part of the central pattern generator (CPG) for mastication, we performed intracellular recordings in brainstem slices taken from young rats. Two cell types were defined, nonbursting (63%) and bursting (37%). In response to membrane depolarization, bursting cells, which dominated in the dorsal part of the NVsnpr, fired an initial burst followed by single spikes or recurring bursts. Non-bursting neurons, scattered throughout the nucleus, fired single action potentials. Microstimulation applied to the trigeminal motor nucleus (NVmt), the reticular border zone surrounding the NVmt, the parvocellular reticular formation or the nucleus reticularis pontis caudalis (NPontc) elicited a postsynaptic potential in 81% of the neurons tested for synaptic inputs. Responses obtained were predominately excitatory and sensitive to glutamatergic antagonists DNQX and/or APV. Some inhibitory and biphasic responses were also evoked. Bicuculline methiodide or strychnine blocked the IPSPs indicating that they were mediated by GABA(A) or glycinergic receptors. About one-third of the stimulations activated both types of neurons antidromically, mostly from the masseteric motoneuron pool of NVmt and dorsal part of NPontc. In conclusion, our new findings show that some neurons in the dorsal NVsnpr display both firing properties and axonal connections which support the hypothesis that they may participate in masticatory pattern generation. Thus, the present data provide an extended basis for further studies on the organization of the masticatory CPG network.
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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 | 0.000 | 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) | 0.000 | 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".