NMDA receptors in axons: there's no coincidence
Bibliographic record
Abstract
In the textbook view, N-methyl-d-aspartate (NMDA) receptors are postsynaptically located detectors of coincident activity in Hebbian learning. However, controversial presynaptically located NMDA receptors (preNMDARs) have for decades been repeatedly reported in the literature. These preNMDARs have typically been implicated in the regulation of short-term and long-term plasticity, but precisely how they signal and what their functional roles are have been poorly understood. The functional roles of preNMDARs across several brain regions and different forms of plasticity can differ vastly, with recent discoveries showing key involvement of unusual subunit composition. Increasing evidence shows preNMDAR can signal through both ionotropic action by fluxing calcium and in metabotropic mode even in the presence of magnesium blockade. We argue that these unusual properties may explain why controversy has surrounded this receptor type. In addition, the expression of preNMDARs at some synapse types but not others can underlie synapse-type-specific plasticity. Last but not least, preNMDARs are emerging therapeutic targets in disease states such as neuropathic pain. We conclude that axonally located preNMDARs are required for specific purposes and do not end up there by accident.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.003 | 0.011 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".