Experience-dependent persistent expression of zif268during rest is preserved in the aged dentate gyrus
Bibliographic record
Abstract
BACKGROUND: Aging is typically accompanied by memory decline and changes in hippocampal function. Among these changes is a decline in the activity of the dentate gyrus (DG) during behavior. Lasting memory, however, is thought to also require recapitulation of recent memory traces during subsequent rest - a phenomenon, termed memory trace reactivation, which is compromised in hippocampal CA1 with progressive age. This process has yet to be assessed in the aged DG, despite its prominent role in age-related memory impairment. Using zif268 transcription to measure granule cell recruitment, DG activity in adult and aged animals was assessed both during spatial exploration and as animals remained at rest in the home cage in order to detect potential memory-related replay. RESULTS: Consistent with the observation of memory trace reactivation in DG, the probability that an individual granule cell transcribes zif268 during rest in the animal's home cage is increased by recent experience in a novel environment. Surprisingly, a comparable increase was observed in the probability of granule cells in the aged DG expressing zif268 during rest. Moreover, no significant age-related difference was observed in the number of granule cells expressing zif268 during rest. Thus, the number and pattern of granule cell expression of zif268 during rest is preserved in aged animals, despite a significant decline in exploration-related zif268 expression. CONCLUSIONS: These data lead to the hypothesis that the input the aged DG receives from backprojections from CA3 (the region widely hypothesized to mediate reactivation) remains functionally intact despite loss of innervation from the perforant path.
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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".