Functional Integration of Adult-Generated Granule Cells into Hippocampal Memory
Bibliographic record
Abstract
Throughout adulthood new neurons are continuously added to the dentate gyrus, a hippocampal sub-region that plays a critical role in learning. Our recent studies have used immunohistochemical approaches to visualize the recruitment of these new neurons into circuits supporting water maze memories in intact animals. We showed that functional integration of these adult-generated granule cells into memory circuits proceeds in a maturation-dependent manner, with new granule cells not contributing in significant numbers until they are 4 weeks or older in age. Our current studies are designed to define the range of conditions under which adult-generated granule cells contribute to hippocampal memory formation and focus, in particular, on three issues. First, the hippocampus is involved in multiple forms of spatial and non-spatial memory: Does integration depend upon the type of memory being formed? Second, levels of adult neurogenesis decline exponentially with age and are regulated by a large number of genetic and environmental factors: Does the availability of new neurons affect their rate of incorporation? Third, the dentate gyrus is composed of neurons generated embyonically and postnatally, as well as those throughout adulthood: Are developmentally- and adult-generated neurons incorporated into memory networks at the same or different rates?
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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".