Unlearning: NMDA Receptor-Mediated Metaplasticity in the Anterior Piriform Cortex Following Early Odor Preference Training in Rats
Bibliographic record
Abstract
Here we demonstrate metaplastic effect of a change in NMDA receptor (NMDAR) number in the anterior piriform cortex (aPC) in rat induced by a 10 min pairing of peppermint odor + stroking, which significantly modifies later learning and memory. Using isolated synaptoneurosomes, we found NR1 receptor downregulation 3 h after training and upregulation at 24 h. Consistent with the NR1 pattern, the NMDAR-mediated EPSP was smaller at 3 h and larger at 24 h. Subunit composition was unchanged. Whereas LTP was reduced at both times by training, LTD was facilitated only at 3 h. Behaviorally, pups, given a pairing of peppermint + stroking 3 h after an initial peppermint + stroking training, lost the normally acquired peppermint preference 24 h later. To probe the pathway specificity of this unlearning effect, pups were trained first with peppermint and then, at 3 h, given a second training with peppermint or vanillin. Pups given peppermint training at both times lost the learned peppermint preference. Pups given vanillin retraining at 3 h had normal peppermint preference. Downregulating NR1 with siRNA prevented odor preference learning. Finally, the NMDAR antagonist MK-801 blocked the LTD facilitation seen 3 h after training, and giving MK-801 before the second peppermint training trial eliminated the loss of peppermint odor preference. A training-associated reduction in NMDARs facilitates LTD 3 h later; training at the time of LTD facilitation reverses an LTP-dependent odor preference. Experience-dependent, pathway-specific metaplastic effects in a cortical structure have broad implications for the optimal spacing of learning experiences.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".