A Genetic Screen for Olfactory Habituation Mutations in Drosophila: Analysis of Novel Foraging Alleles and an Underlying Neural Circuit
Bibliographic record
Abstract
Habituation is a form of non-associative learning that enables animals to reduce their reaction to repeated harmless stimuli. When exposed to ethanol vapor, Drosophila show an olfactory-mediated startle response characterized by a transient increase in locomotor activity. Upon repeated exposures, this olfactory startle attenuates with the characteristics of habituation. Here we describe the results of a genetic screen to identify olfactory startle habituation (OSH) mutants. One mutation is a transcript specific allele of foraging (for) encoding a cGMP-dependent kinase. We show this allele of for reduces expression of a for-T1 isoform expressed in the head and functions normally to inhibit OSH. We localize for-T1 function to a limited set of neurons that include olfactory receptor neurons (ORNs) and the mushroom body (MB). Overexpression of for-T1 in ORNs inhibits OSH, an effect also seen upon synaptic silencing of the ORNs; for-T1 may therefore function in ORNs to decrease synaptic release upon repeated exposure to ethanol vapor. Overall, this work contributes to our understanding of the genes and neurons underlying olfactory habituation in Drosophila.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".