Calcium influx through N-type channels and activation of SK and TRP-like channels regulates tonic firing of neurons in rat paraventricular thalamus
Bibliographic record
Abstract
The thalamus is a major relay and integration station in the central nervous system. While there is a large body of information on the firing and network properties of neurons contained within sensory thalamic nuclei, less is known about the neurons located in midline thalamic nuclei, which are thought to modulate arousal and homeostasis. One midline nucleus that has been implicated in mediating stress responses is the paraventricular nucleus of the thalamus (PVT). Like other thalamic neurons, these neurons display two distinct firing modes, burst and tonic. In contrast to burst firing, little is known about the ionic mechanisms modulating tonic firing in these cells. Here we performed a series of whole cell recordings to characterize tonic firing in PVT neurons in acute rat brain slices. We found that PVT neurons are able to fire sustained, low-frequency, weakly accommodating trains of action potentials in response to a depolarizing stimulus. Unexpectedly, PVT neurons displayed a very high propensity to enter depolarization block, occurring at stimulus intensities that would elicit tonic firing in other thalamic neurons. The tonic firing behavior of these cells is modulated by a functional interplay between N-type Ca(2+) channels and downstream activation of small-conductance Ca(2+)-dependent K(+) (SK) channels and a transient receptor potential (TRP)-like conductance. Thus these ionic conductances endow PVT neurons with a narrow dynamic range, which may have fundamental implications for the integrative properties of this nucleus.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".