M1 muscarinic receptor activation reverses age-related memory updating impairment in mice
Bibliographic record
Abstract
Previously consolidated memories can become temporarily labile upon reactivation. Reactivation-based memory updating is chiefly studied in young subjects, so we aimed to assess this process across the lifespan. To do this, we developed a behavioural paradigm wherein a reactivated object memory is updated with contextual information; 3-month-old and 6-month-old male C57BL/6 mice displayed object memory updating, but 12-month-old mice did not. We found that M1 muscarinic acetylcholine receptor signaling during reactivation was necessary for object memory updating in the young mice. Next, we targeted this mechanism in an attempt to facilitate object memory updating in aging mice. Remarkably, systemic pharmacological M1 receptor activation reversed the age-related deficit. Quantification of cholinergic system markers within perirhinal cortex revealed subtle cellular changes that may contribute to differential performance across age groups. These findings suggest that natural cholinergic change across the lifespan contributes to inflexible memory in the aging brain. • Memory reactivation can signal an opportunity to update previously stored memory. • Muscarinic receptor activity gates post-reactivation object memory updating in mice. • Healthy and moderately aged mice display an object memory updating impairment. • An M1 muscarinic receptor agonist can reverse age-related memory updating deficits.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".