Two Interacting Olfactory Transduction Mechanisms Have Linked Polarities and Dynamics in<i>Drosophila melanogaster</i>Antennal Basiconic Sensilla Neurons
Bibliographic record
Abstract
We measured frequency response functions between concentrations of fruit odorants and individual action potentials in large basiconic sensilla of the Drosophila melanogaster antenna. A new method of randomly varying odorant concentration was combined with rapid, continuous measurement of concentration at the antenna by a miniature photoionization detector. All frequency responses decreased progressively at frequencies approaching 100 Hz, providing an upper limit for the dynamics of Drosophila olfaction. We found two distinct response patterns: excitatory band-pass frequency responses were seen with ethyl acetate, ethyl butyrate, and hexanol, whereas inhibitory low-pass responses were seen with methyl salicylate and phenylethyl acetate. Band-pass responses peaked at 1-10 Hz. Frequency responses could be well fitted by simple linear filter equations, and the fitted parameters were consistent within each of the two types of responses. Experiments with equal mixtures of excitatory and inhibitory odorants gave responses that were characteristic of the inhibitory components, indicating that interaction during transduction causes inhibitory odorants to suppress the responses to excitatory odorants. Plots of response amplitude versus odorant concentration indicated that the odorant concentrations used were within approximately linear regions of the dose response relationships. We also estimated linear information capacity from the coherence function of each recording. Although coherence was relatively high, indicating a large signal-to-noise ratio, information capacity for olfaction was much lower than comparable estimates for mechanotransduction or visual transduction because of the limited bandwidth of olfaction. These data offer new insights into transduction by primary chemoreceptors and place temporal constraints on Drosophila olfactory behavior.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".