Staircase Currents in Motoneurons: Insight into the Spatial Arrangement of Calcium Channels in the Dendritic Tree
Bibliographic record
Abstract
In spinal motoneurons, activation of dendritically located depolarizing conductances can lead to amplification of synaptic inputs and the production of plateau potentials. Immunohistochemical and computational studies have implicated dendritic CaV1.3 channels in this amplification and suggest that CaV1.3 channels in spinal motoneurons may be organized in clusters in the dendritic tree. Our goal was to provide physiological evidence for the presence of multiple discrete clusters of voltage-gated calcium channels in spinal motoneurons and to explore the spatial arrangement of these clusters in the dendritic tree. We recorded voltage-gated calcium currents from spinal motoneurons in slices of mature mouse spinal cords. We demonstrate that single somatic voltage-clamp steps can elicit multiple inward currents with varying delays to onset, resulting in a current with a "staircase"-like appearance. Recordings from cultured dorsal root ganglion cells at different stages of neurite development provide evidence that these currents arise from the unclamped portions of the dendritic tree. Finally, both voltage- and current-clamp data were used to constrain computer models of a motoneuron. The resultant simulations impose two conditions on the spatial distribution of CaV channels in motoneuron dendrites: one of asymmetry relative to the soma and another of spatial separation between clusters of CaV channels. We propose that this compartmentalization would provide motoneurons with the ability to process multiple sources of input in parallel and integrate this processed information to produce appropriate trains of action potentials for the intended motor behavior.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".