AMPA receptor exchange underlies transient memory destabilization on retrieval
Bibliographic record
Abstract
A consolidated memory can be transiently destabilized by memory retrieval, after which memories are reconsolidated within a few hours; however, the molecular substrates underlying this destabilization process remain essentially unknown. Here we show that at lateral amygdala synapses, fear memory consolidation correlates with increased surface expression of calcium-impermeable AMPA receptors (CI-AMPARs), which are known to be more stable at the synapse, whereas memory retrieval induces an abrupt exchange of CI-AMPARs to calcium-permeable AMPARs (CP-AMPARs), which are known to be less stable at the synapse. We found that blockade of either CI-AMPAR endocytosis or NMDA receptor activity during memory retrieval, both of which blocked the exchange to CP-AMPARs, prevented memory destabilization, indicating that this transient exchange of AMPARs may underlie the transformation of a stable memory into an unstable memory. These newly inserted CP-AMPARs gradually exchanged back to CI-AMPARs within hours, which coincided with the course of reconsolidation. Furthermore, blocking the activity of these newly inserted CP-AMPARs after retrieval impaired reconsolidation, suggesting that they serve as synaptic "tags" that support synapse-specific reconsolidation. Taken together, our results reveal unexpected physiological roles of CI-AMPARs and CP-AMPARs in transforming a consolidated memory into an unstable memory and subsequently guiding reconsolidation.
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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 | 0.001 |
| 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".