Posttraining Ablation of Adult-Generated Olfactory Granule Cells Degrades Odor–Reward Memories
Bibliographic record
Abstract
Proliferation of neural progenitor cells in the subventricular zone leads to the continuous generation of new olfactory granule cells (OGCs) throughout life. These cells synaptically integrate into olfactory bulb circuits after ∼2 weeks and transiently exhibit heightened plasticity and responses to novel odors. Although these observations suggest that adult-generated OGCs play important roles in olfactory-related memories, global suppression of olfactory neurogenesis does not typically prevent the formation of odor-reward memories, perhaps because residual OGCs can compensate. Here, we used a transgenic strategy to selectively ablate large numbers of adult-generated OGCs either before or after learning in mice. Consistent with previous studies, pretraining ablation of adult-generated OGCs did not prevent the formation of an odor-reward memory, presumably because existing OGCs can support memory formation in their absence. However, ablation of a similar cohort of adult-generated OGCs after training impaired subsequent memory expression, indicating that if these cells are available at the time of training, they play an essential role in subsequent expression of odor-reward memories. Memory impairment was associated with the loss of adult-generated OGCs that were >10 d in age and did not depend on the developmental stage in which they were generated, suggesting that, once sufficiently mature, OGCs generated during juvenility and adulthood play similar roles in the expression of odor-reward memories. Finally, ablation of adult-generated OGCs 1 month after training did not produce amnesia, indicating that adult-generated OGCs play a time-limited role in the expression of odor-reward memories.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".