Memory Destabilization and Reconsolidation Dynamically Regulate the PKMζ Maintenance Mechanism
Bibliographic record
Abstract
Useful memory must balance between stability and malleability. This puts effective memory storage at odds with plasticity processes, such as reconsolidation. What becomes of memory maintenance processes during synaptic plasticity is unknown. Here we examined the fate of the memory maintenance protein PKMζ during memory destabilization and reconsolidation in male rats. We found that NMDAR activation and proteasome activity induced a transient reduction in PKMζ protein following retrieval. During reconsolidation, new PKMζ was synthesized to re-store the memory. Failure to synthesize new PKMζ during reconsolidation impaired memory but uninterrupted PKMζ translation was not necessary for maintenance itself. Finally, NMDAR activation was necessary to render memories vulnerable to the amnesic effect of PKMζ-antisense. These findings outline a transient disruption and renewal of the PKMζ memory maintenance mechanism during plasticity. We argue that dynamic changes in PKMζ protein levels can serve as an exemplary model of the molecular changes underlying memory destabilization and reconsolidation. SIGNIFICANCE STATEMENT Maintenance of long-term memory relies on the persistent activity of PKMζ. However, after retrieval, memories can become transiently destabilized and must be reconsolidated within a few hours to persist. During this period of plasticity, what happens to maintenance processes, such as those involving PKMζ, is unknown. Here we describe dynamic changes to PKMζ expression during both destabilization and reconsolidation of auditory fear memory in the amygdala. We show that destabilization induces a NMDAR- and proteasome-dependent loss of synaptic PKMζ and that reconsolidation requires synthesis of new PKMζ. This work provides clear evidence that memory destabilization disrupts ongoing synaptic maintenance processes which are restored during 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 | 0.001 |
| 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".