Inputs to nucleus pontis caudalis from adjacent trigeminal areas
Bibliographic record
Abstract
Recent studies suggest that the nucleus pontis caudalis (nPontc) plays a role in patterning mastication through interactions with the adjacent lateral tegmentum. In this study, we used in vitro intracellular recording and staining to describe the basic membrane properties and morphology of nPontc neurones and to further explore interactions with adjacent structures, using coronal sections of the brainstem of 78 rats, aged 9-28 days. Neurones were large, with dendrites that spread in all directions, and about 64% fired tonically even in the absence of synaptic inputs. Tonic neurones were predominant in the centre of the nucleus. Electrical stimulation of all regions of the nPontc produced mixed excitatory and inhibitory effects on interneurones of lateral tegmental nuclei. Focal inactivation of the dorsal nPontc with injections of tetrodotoxin also had mixed effects on the spontaneous firing of both interneurones and motoneurones but similar injections in the ventral nPontc produced mostly increases of firing. Sixty-five percent of nPontc neurones received synaptic inputs from the lateral tegmental areas and most of these (68%) were excitatory and mediated by glutamatergic receptors. Inhibitory postsynaptic potentials were mediated by GABA(A) or glycinergic receptors. Although most responses occurred at relatively long latencies (> 2 ms), they could follow relatively high-frequency stimulation (> 50 Hz). Excitatory and inhibitory connections between ipsi- and contralateral nPontc neurones were also documented, which could contribute to bilateral coordination of jaw movements. This study provides evidence that the nPontc exerts both tonic and phasic influences on the premotor components of the masticatory central pattern generator.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".