Memory Retrieval Requires Ongoing Protein Synthesis and NMDA Receptor Activity-Mediated AMPA Receptor Trafficking
Bibliographic record
Abstract
Whereas consolidation and reconsolidation are considered dynamic processes requiring protein synthesis, memory retrieval has long been considered a passive readout of previously established plasticity. However, previous findings suggest that memory retrieval may be more dynamic than previously thought. This study therefore aimed at investigating the molecular mechanisms underlying memory retrieval in the rat. Infusion of protein synthesis inhibitors (rapamycin or anisomycin) in the amygdala 10 min before memory retrieval transiently impaired auditory fear memory expression, suggesting ongoing protein synthesis is required to enable memory retrieval. We then investigated the role of protein synthesis in NMDA receptor activity-mediated AMPA receptor trafficking. Coinfusion of an NMDA receptor antagonist (ifenprodil) or infusion of an AMPA receptor endocytosis inhibitor (GluA23Y) before rapamycin prevented this memory impairment. Furthermore, rapamycin transiently decreased GluA1 levels at the postsynaptic density (PSD), but did not affect extrasynaptic sites. This effect at the PSD was prevented by an infusion of GluA23Y before rapamycin. Together, these data show that ongoing protein synthesis is required before memory retrieval is engaged, and suggest that this protein synthesis may be involved in the NMDAR activity-mediated trafficking of AMPA receptors that takes place during memory retrieval.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".