Functional Microstructure of Ca <sub>V</sub> -Mediated Calcium Signaling in the Axon Initial Segment
Bibliographic record
Abstract
The axon initial segment (AIS) is a specialized neuronal compartment in which synaptic input is converted into action potential (AP) output. This process is supported by a diverse complement of sodium, potassium, and calcium channels (Ca V ). Different classes of sodium and potassium channels are scaffolded at specific sites within the AIS, conferring unique functions, but how calcium channels are functionally distributed within the AIS is unclear. Here, we use conventional two-photon laser scanning and diffraction-limited, high-speed spot two-photon imaging to resolve AP-evoked calcium dynamics in the AIS with high spatiotemporal resolution. In mouse layer 5 prefrontal pyramidal neurons, calcium influx was mediated by a mix of Ca V 2 and Ca V 3 channels that differentially localized to discrete regions. Ca V 3 functionally localized to produce nanodomain hotspots of calcium influx that coupled to ryanodine-sensitive stores, whereas Ca V 2 localized to non-hotspot regions. Thus, different pools of Ca V s appear to play distinct roles in AIS function. SIGNIFICANCE STATEMENT The axon initial segment (AIS) is the site where synaptic input is transformed into action potential (AP) output. It achieves this function through a diverse complement of sodium, potassium, and calcium channels (Ca V ). While the localization and function of sodium channels and potassium channels at the AIS is well described, less is known about the functional distribution of Ca V s. We used high-speed two-photon imaging to understand activity-dependent calcium dynamics in the AIS of mouse neocortical pyramidal neurons. Surprisingly, we found that calcium influx occurred in two distinct domains: Ca V 3 generates hotspot regions of calcium influx coupled to calcium stores, whereas Ca V 2 channels underlie diffuse calcium influx between hotspots. Therefore, different Ca V classes localize to distinct AIS subdomains, possibly regulating distinct cellular processes.
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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 | 0.000 |
| 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".