Early life experience with natural odors modifies olfactory behavior through an associative process
Bibliographic record
Abstract
ABSTRACT Past work has shown that chronic exposure of Drosophila to intense monomolecular odors in early life leads to homeostatic adaptation of olfactory neural responses and behavioral habituation to the familiar odor. Here, we found that, in contrast, persistent exposure to natural odors in early life increases behavioral attraction selectively to familiar odors. Odor experience increases the attractiveness of natural odors that are innately attractive and decreases the aversiveness of natural odors that are innately aversive. These changes in olfactory behavior are unlikely to arise from changes in the sensitivity of olfactory neurons at the first stages of olfactory processing: odor-evoked output from antennal lobe projection neurons was unchanged by chronic exposure to natural odors in terms of olfactory sensitivity, relational distances between odors, or response dynamics. We reveal a requirement for additional features of the environment beyond the odor in establishing odor experience-dependent behavioral plasticity. Passive odor exposure in a featureless environment lacking strong reinforcing cues was insufficient to elicit changes in olfactory preference; however, the same odor exposure resulted in behavioral plasticity when food was present in the environment. Together, these results indicate that behavioral plasticity elicited by persistent exposure to natural odors in early life is mediated by an associative process. In addition, they highlight the importance of using naturalistic odor stimuli for investigating olfactory function.
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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".