Learning-Induced Metaplasticity? Associative Training for Early Odor Preference Learning Down-Regulates Synapse-Specific NMDA Receptors via mGluR and Calcineurin Activation
Bibliographic record
Abstract
Rat pups readily form a 24-h associative odor preference after a single trial of odor paired with intermittent stroking. Recent evidence shows that this training trial, which normally increases AMPA receptor responses in the anterior piriform cortex both 3 and 24 h following training, induces a down-regulation of NMDA receptors 3 h later followed by NMDA receptor up-regulation at 24 h. When retrained with the same odor at 3 h, rat pups unlearn the original odor preference. Unlearning can be prevented by blocking NMDA receptors during retraining. Here, the mechanisms that initiate NMDA receptor down-regulation are assessed. Blocking mGluR receptors or calcineurin during training prevents down-regulation of NMDA receptors 3 h following training. Blocking NMDA receptors during training does not affect NMDA receptor down-regulation. Thus, down-regulation can be engaged separately from associative learning. When unlearning occurs, AMPA and NMDA receptor levels at 24 h are reset to control levels. Calcineurin blockade during retraining prevents unlearning consistent with the role of NMDA receptor down-regulation. The relationship of these events to the metaplasticity and plasticity mechanisms of long-term depression and depotentiation is discussed. We suggest a possible functional role of NMDA receptor down-regulation in offline stabilization of learned odor representations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".