Adult neurogenesis in natural populations
Bibliographic record
Abstract
The dogma that the adult brain produces no new neurons has been overturned, but the critics are still asking, so what? Is adult neurogenesis a biologically relevant phenomenon, or is it perhaps harmful because it disrupts the existing neuronal circuitry? Considering that the phenomenon is evolutionarily conserved in all mammalian species examined to date and that its relevance has been well documented in non-mammalian species, it seems self-evident that neurogenesis in adult mammals must have a role. In birds, it has been established that neurogenesis varies dramatically with seasonal changes in song production. In chickadees, the learning behaviour related to finding stored food is also correlated with seasonal adult neurogenesis. Such studies are still nonexistent in mammals, but the related evidence suggests that neurogenesis does vary seasonally in hamsters and shows sexual differences in meadow voles. To promote studies on natural populations asking fundamental questions of the purpose and function of neurogenesis, we organized a Workshop on "Hippocampal Neurogenesis in Natural Populations" in Toronto in May 2000. The Workshop highlighted recent discoveries in neurogenesis from the lab, and focused on its functional consequences. The consensus at the Workshop was that demonstration of a role for neurogenesis in natural behaviours will ultimately be essential if we are to understand the purpose and function of neurogenesis in humans.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".