Stability of recent and remote contextual fear memory
Bibliographic record
Abstract
Following initial encoding, memories undergo a prolonged period of reorganization. While such reorganization may occur in many different memory systems, its purpose is not clear. Previously, we have shown that recall of recent contextual fear memories engages the dorsal hippocampus (dHPC). In contrast, recall of remote contextual fear memories engages a number of different cortical regions, including the anterior cingulate cortex (ACC). To examine whether this reorganization leads to greater memory stability, we examined reconsolidation of 1 d-old (recent) and 36 d-old (remote) contextual fear memory in mice. We infused the protein synthesis inhibitor, anisomycin (ANI), into either the dHPC or ACC immediately following retrieval of either a recent or remote contextual fear memory. In the dHPC, ANI infusions disrupted subsequent expression of recent, but not remote, contextual fear memory. Similar infusions into the ACC had no effect on either recent or remote contextual fear memories, whereas systemically applied ANI blocked subsequent remote memory expression when long re-exposure durations were used. Together, these data suggest that as memories mature they become increasingly stable. Furthermore, the dissociation between the effects of systemically and centrally administered ANI on remote memory suggests that stability is due, in part, to the distributed nature of remote contextual fear 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".