Behavioral and Cellular Tagging in Young and in Early Cognitive Aging
Bibliographic record
Abstract
The ability to maintain relevant information on a daily basis is negatively impacted by aging. However, the neuronal mechanism manifesting memory persistence in young animals and memory decline in early aging is not fully understood. A novel event, when introduced around encoding of an everyday memory task, can facilitate memory persistence in young age but not in early aging. Here, we investigated in male rats how sub-regions of the hippocampus are involved in memory representation in behavioral tagging and how early aging affects such representation by combining behavioral training in appetitive delayed-matching-to-place tasks with the “cellular compartment analysis of temporal activity by fluorescence in situ hybridization” technique. We show that neuronal assemblies activated by memory encoding were also partially activated by novelty, particularly in the distal CA1 and proximal CA3 subregions in young male rats. In early aging, both encoding- and novelty-triggered neuronal populations were significantly reduced with a more profound effect in encoding neurons. Thus, memory persistence through novelty facilitation engages overlapping hippocampal assemblies as a key cellular signature, and cognitive aging is associated with underlying reduction in neuronal activation.
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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 | 0.000 |
| 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".