Effect of the Stimulation of Sensory Inputs on the Firing of Neurons of the Trigeminal Main Sensory Nucleus in the Rat
Bibliographic record
Abstract
Mastication can be triggered by repetitive stimulation of the cortex or of sensory inputs, but is patterned by a brain stem central pattern generator (CPG). This CPG may include the dorsal part of the principal trigeminal sensory nucleus (NVsnpr), where neurons burst repetitively when the extracellular concentration of Ca(2+) ([Ca(2+)](e)) drops. We examined the effects of repetitive stimulation of sensory afferents of the trigeminal tract on activity of NVsnpr neurons recorded extracellularly in vitro under physiologic [Ca(2+)](e) (1.6 mM). Spontaneously active cells had either a tonic (n = 145) or a bursting (n = 46) firing pattern. Afferent stimulation altered burst duration and/or burst frequency in bursting cells and firing frequency in most tonic cells. In 28% of the latter, the firing pattern switched to rhythmic bursting. This effect could be mimicked by local application of N-methyl-d-aspartate and blocked by APV but not DNQX. Detailed analysis showed that rhythm indices (RIs) of 35 tonic neurons that were negative (nonrhythmic) before stimulation became significantly rhythmic (RI > or = 0.01) after stimulation. Mean and median bursting frequency of these units were 8.32 +/- 0.72 (SE) Hz and 6.25 Hz (range, 2.5-17.5 Hz). In seven instances, two units were recorded simultaneously, and cross-correlation analysis showed that firing of six pairs was rhythmic and synchronized after stimulation. Optimal stimulation parameters for eliciting rhythmic bursting consisted in 500-ms trains of pulses delivered at 40-60 Hz. Together, our results show that repetitive stimulation of sensory afferents in vitro can elicit masticatory-like rhythmic bursting in NVsnpr neurons at physiological [Ca(2+)](e).
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".