Discharge patterns of neurons in the medial pontobulbar reticular formation during fictive mastication in the rabbit
Bibliographic record
Abstract
In this study, we describe functional characteristics of neurons forming networks generating oral ingestive motor behaviours. Neurons in medial reticular nuclei on the right side of the brainstem between the trigeminal and hypoglossal motor nuclei were recorded in anaesthetized and paralysed rabbits during two types of masticatory-like motor patterns induced by electrical stimulation of the left (contralateral) or right (ipsilateral) cortical masticatory areas. Sixty-seven neurons in nucleus reticularis pontis caudalis (nPontc), nucleus reticularis parvocellularis (nParv), and nucleus reticularis gigantocellularis (Rgc) were studied. These were classified as phasic or tonic depending on their firing pattern during the fictive jaw movement cycle. Phasic neurons located in the dorsal part of nPontc were active during the jaw opening phase, whilst those in dorsal nParv tended to fire during the closing phase. In most neurons, burst duration and firing frequency changed between the two motor patterns, but there was little change in phase of firing. Tonic units were mainly recorded in the ventral half of nPontc, and at the junction between Rgc and caudal nParv. Cortical inputs with short latency from the contralateral masticatory area were more frequent in phasic (82%) than tonic (44%) neurons, whilst inputs from the ipsilateral cortex were equal in the two subgroups (57% and 56%). Phasic neurons had significantly shorter mean contralateral than ipsilateral cortical latencies, whilst there was no difference among tonic neurons. Intra- and perioral primary afferent inputs activated both types of neurons at oligo-synaptic latencies. Our results show that subpopulations of neurons in medial reticular nuclei extending from the caudal part of the trigeminal motor nucleus to the rostral third of the hypoglossal motor nucleus are active during the fictive masticatory motor behaviour. Unlike masticatory neurons in the lateral tegmentum, the medial subpopulations are spatially organized according to discharge pattern.
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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".