The Ca<sub>v</sub>3–K<sub>v</sub>4 Complex Acts as a Calcium Sensor to Maintain Inhibitory Charge Transfer during Extracellular Calcium Fluctuations
Bibliographic record
Abstract
Synaptic transmission and neuronal excitability depend on the concentration of extracellular calcium ([Ca](o)), yet repetitive synaptic input is known to decrease [Ca](o) in numerous brain regions. In the cerebellar molecular layer, synaptic input reduces [Ca](o) by up to 0.4 mm in the vicinity of stellate cell interneurons and Purkinje cell dendrites. The mechanisms used to maintain network excitability and Purkinje cell output in the face of this rapid change in calcium gradient have remained an enigma. Here we use single and dual patch recordings in an in vitro slice preparation of Sprague Dawley rats to investigate the effects of physiological decreases in [Ca](o) on the excitability of cerebellar stellate cells and their inhibitory regulation of Purkinje cells. We find that a Ca(v)3-K(v)4 ion channel complex expressed in stellate cells acts as a calcium sensor that responds to a decrease in [Ca]o by dynamically adjusting stellate cell output to maintain inhibitory charge transfer to Purkinje cells. The Ca(v)3-K(v)4 complex thus enables an adaptive regulation of inhibitory input to Purkinje cells during fluctuations in [Ca](o), providing a homeostatic control mechanism to regulate Purkinje cell excitability during repetitive afferent activity.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".