Older and stronger object memories are selectively destabilized by reactivation in the presence of new information
Bibliographic record
Abstract
Reactivation can destabilize previously consolidated memories, rendering them vulnerable to disruption and necessitating a process of reconsolidation in order for them to be maintained. This process of destabilization and reconsolidation has commonly been cited as a means by which established memories can be updated or modified. However, little direct evidence exists to support this view. The present study addressed this issue by analyzing the influence of novel salient information present at the time of memory reactivation on the likelihood of the reactivated memory to become destabilized and vulnerable to disruption. Rats explored sample objects and, some time later, received systemic injections of the N-methyl-D-aspartic acid (NMDA) receptor antagonist MK-801 or saline prior to memory reactivation. When object memories were relatively young or weakly encoded, MK-801 significantly disrupted reconsolidation regardless of the reactivation conditions. However, increasing the amount of sample object exploration or the interval between the sample phase and reactivation abolished the effect of MK-801 on reconsolidation unless salient novel contextual information was present during memory reactivation. These results highlight the dynamic nature of memory storage and retrieval and indicate an important interaction between the age and strength of a memory, its probability of being destabilized upon reactivation, and the stimulus conditions during reactivation. The essential involvement of novel encoding in destabilizing certain memories supports the idea that the reconsolidation process enables modification of existing memories.
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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 | 0.001 |
| 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".