Non‐ionotropic cross‐talk between AMPA and NMDA receptors in rodent hippocampal neurones
Bibliographic record
Abstract
Many fast excitatory synapses in the hippocampus are enriched with both AMPARs (alpha-amino-3-hydroxyl-5-methyl-4-isoxazolepropionate receptors) and NMDARs (N-methyl-D-aspartate receptors). Their proximity allows them to be activated simultaneously by the same neurotransmitter, L-glutamate. Activation of AMPARs leads to influx of sodium and calcium ions, which can increase or decrease NMDAR activity through sodium concentration-dependent cascades or a calcium-calmodulin-dependent inactivation process, respectively. Here we provide evidence that the activation of AMPARs inhibits NMDARs through a non-ionotropic mechanism. NMDA-induced current in isolated rat CA1 hippocampal cells and nucleated patches of cultured mouse hippocampal neurones decreased when AMPARs were activated. Conversely, when AMPARs were blocked, the NMDA component of glutamate-induced current increased. The inhibitory action of AMPAR activation on NMDAR-mediated current depends upon the open state of AMPA channels and rapidly diminishes after deactivation of AMPARs. The inhibitory action was independent of membrane voltage, univalent cation fluxes and calcium influx. The AMPA-NMDA cross-inhibition also occurred in evoked synaptic current in CA1 neurones from intact mouse hippocampal slices. This cross-talk may play a role in preventing overexcitation during bursting activities in the hippocampus.
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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".