Contribution of a Calcium‐Activated Non‐Specific Conductance to NMDA Receptor‐Mediated Synaptic Potentials in Granule Cells of the Frog Olfactory Bulb
Bibliographic record
Abstract
We studied granule cells (GCs) in the intact frog olfactory bulb (OB) by combining whole-cell recordings and functional two-photon Ca(2+) imaging in an in vitro nose-brain preparation. GCs are local interneurones that shape OB output via distributed dendrodendritic inhibition of OB projection neurones, the mitral-tufted cells (MTCs). In contrast to MTCs, GCs exhibited a Ca(2+)-activated non-specific cation conductance (I(CAN)) that could be evoked through strong synaptic stimulation or suprathreshold current injection. Photolysis of the caged Ca(2+) chelator o-nitrophenol-EGTA resulted in activation of an inward current with a reversal potential within the range -20 to +10 mV. I(CAN) in GCs was suppressed by the intracellular Ca(2+) chelator BAPTA (0.5-5.0 mM), but not by EGTA (up to 5 mM). The current persisted in whole-cell recordings for up to 1.5 h post-breakthrough, was observed during perforated-patch recordings and was independent of ionotropic glutamate and GABA(A) receptor activity. In current-clamp mode, GC responses to synaptic stimulation consisted of an initial AMPA-mediated conductance followed by a late-phase APV-sensitive plateau (100-500 ms). BAPTA-mediated suppression of I(CAN) resulted in a selective reduction of the late component of the evoked synaptic potential, consistent with a positive feedback relationship between NMDA receptor (NMDAR) current and I(CAN). I(CAN) requires Ca(2+) influx either through voltage-gated Ca(2+) channels or possibly NMDARs, both of which have a high threshold for activation in GCs, predicting a functional role for this current in the selective enhancement of strong synaptic inputs to GCs.
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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".