Specific T-type calcium channel isoforms are associated with distinct burst phenotypes in deep cerebellar nuclear neurons
Bibliographic record
Abstract
T-type calcium channels are thought to transform neuronal output to a burst mode by generating low voltage-activated (LVA) calcium currents and rebound burst discharge. In this study we assess the expression pattern of the three different T-type channel isoforms (Ca(v)3.1, Ca(v)3.2, and Ca(v)3.3) in cerebellar neurons and focus on their potential role in generating LVA spikes and rebound discharge in deep cerebellar nuclear (DCN) neurons. We detected expression of one or more Ca(v)3 channel isoforms in a wide range of cerebellar neurons and selective expression of different isoforms in DCN cells. We further identify two classes of large-diameter DCN neurons that exhibit either a strong or weak capability for rebound discharge, despite the ability to generate LVA spikes when calcium currents are pharmacologically isolated. By correlating the Ca(v)3 channel expression pattern with the electrophysiological profile of identified DCN cells, we show that Ca(v)3.1 channels are expressed in isolation in DCN-burst cells, whereas Ca(v)3.3 is expressed in DCN-weak burst cells. Ca(v)3.1-expressing DCN cells correspond to excitatory or GABAergic neurons, whereas Ca(v)3.3-expressing cells are non-GABAergic. The Ca(v)3 class of LVA calcium channels is thus expressed in specific combinations in a wide range of cerebellar neurons but contributes to rebound burst discharge in only a select number of cell classes.
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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".