Persistent Ca<sup>2+</sup>Current Contributes to a Prolonged Depolarization in<i>Aplysia</i>Bag Cell Neurons
Bibliographic record
Abstract
Neurons may initiate behavior or store information by translating prior activity into a lengthy change in excitability. For example, brief input to the bag cell neurons of Aplysia results in an approximate 30-min afterdischarge that induces reproduction. Similarly, momentary stimulation of cultured bag cells neurons evokes a prolonged depolarization lasting many minutes. Contributing to this is a voltage-independent cation current activated by Ca(2+) entering during the stimulus. However, the cation current is relatively short-lived, and we hypothesized that a second, voltage-dependent persistent current sustains the prolonged depolarization. In bag cell neurons, the inward voltage-dependent current is carried by Ca(2+); thus we tested for persistent Ca(2+) current in primary culture under voltage clamp. The observed current activated between -40 and -50 mV exhibited a very slow decay, presented a similar magnitude regardless of stimulus duration (10-60 s), and, like the rapid Ca(2+) current, was enhanced when Ba(2+) was the permeant ion. The rapid and persistent Ca(2+) current, but not the cation current, were Ni(2+) sensitive. Consistent with the persistent current contributing to the response, Ni(2+) reduced the amplitude of a prolonged depolarization evoked under current clamp. Finally, protein kinase C activation enhanced the rapid and persistent Ca(2+) current as well as increased the prolonged depolarization when elicited by an action potential-independent stimulus. Thus the prolonged depolarization arises from Ca(2+) influx triggering a cation current, followed by voltage-dependent activation of a persistent Ca(2+) current and is subject to modulation. Such synergy between currents may represent a common means of achieving activity-dependent changes to excitability.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".