Spike Patterning by Ca<sup>2+</sup>-Dependent Regulation of a Muscarinic Cation Current in Entorhinal Cortex Layer II Neurons
Bibliographic record
Abstract
In entorhinal cortex layer II neurons, muscarinic receptor activation promotes depolarization via activation of a nonspecific cation current (I(NCM)). Under muscarinic influence, these neurons also develop changes in excitability that result in activity-dependent induction of delayed firing and bursting activity. To identify the membrane processes underlying these phenomena, we examined whether I(NCM) may undergo activity-dependent regulation. Our voltage-clamp experiments revealed that appropriate depolarizing protocols increased the basal level of inward current activated during muscarinic stimulation and suggested that this effect was due to I(NCM) upregulation. In the presence of low buffering for intracellular Ca(2+), this upregulation was transient, and its decay could be followed by a phase of I(NCM) downregulation. Both up- and downregulation were elicited by depolarizing stimuli able to activate voltage-gated Ca(2+) channels (VGCC); both were sensitive to increasing concentrations of intracellular Ca(2+)-chelating agents with downregulation being abolished at lower Ca(2+)-buffering capacities; both were reduced or suppressed by VGCC block or in the absence of extracellular Ca(2+). These data indicate that relatively small increases in [Ca(2+)](i) driven by firing activity can induce upregulation of a basal muscarinic depolarizing-current level, whereas more pronounced [Ca(2+)](i) elevations can result in I(NCM) downregulation. We propose that the interaction of activity-dependent positive and negative feedback mechanisms on I(NCM) allows entorhinal cortex layer II neurons to exhibit emergent properties, such as delayed firing and enhanced or suppressed responses to repeated stimuli, that may be of importance in the memory functions of the temporal lobe and in the pathophysiology of epilepsy.
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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) | 0.000 | 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 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".