Kv1 K<sup>+</sup>Channels Control Purkinje Cell Output to Facilitate Postsynaptic Rebound Discharge in Deep Cerebellar Neurons
Bibliographic record
Abstract
Purkinje cells (PCs) generate the sole output of the cerebellar cortex and govern the timing of action potential discharge from neurons of the deep cerebellar nuclei (DCN). Here, we examine how voltage-gated Kv1 K+ channels shape intrinsically generated and synaptically controlled behaviors of PCs and address how the timing of DCN neuron output is modulated by manipulating PC Kv1 channels. Kv1 channels were studied in cerebellar slices at physiological temperatures with Kv1-specific toxins. Outside-out voltage-clamp recordings indicated that Kv1 channels are present in both somatic and dendritic membranes and are activated by Na+ spike-clamp commands. Whole-cell current-clamp recordings revealed that Kv1 K+ channels maintain low frequencies of Na+ spike and Ca-Na burst output, regulate the duration of plateau potentials, and set the threshold for Ca2+ spike discharge. Kv1 channels shaped the characteristics of climbing fiber (CF) responses evoked by extracellular stimulation or intracellular simulated EPSCs. In the presence of Kv1 toxins, CFs discharged spontaneously at approximately 1 Hz. Finally, "Kv1-intact" and "Kv1-deficient" PC tonic and burst outputs were converted to stimulus protocols and used as patterns to stimulate PC axons and synaptically activate DCN neurons. We found that the Kv1-intact patterns facilitated short-latency and high-frequency DCN neuron rebound discharges, whereas DCN neuron output timing was markedly disrupted by the Kv1-deficient stimulus protocols. Our results suggest that Kv1 K+ channels are critical for regulating the excitability of PCs and CFs and optimize the timing of PC outputs to generate appropriate discharge patterns in postsynaptic DCN neurons.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".