Parallel neural pathways in higher visual centers of the Drosophila brain that mediate wavelength-specific behavior
Bibliographic record
Abstract
Compared with connections between the retinae and primary visual centers, relatively less is known in both mammals and insects about the functional segregation of neural pathways connecting primary and higher centers of the visual processing cascade. Here, using the Drosophila visual system as a model, we demonstrate two levels of parallel computation in the pathways that connect primary visual centers of the optic lobe to computational circuits embedded within deeper centers in the central brain. We show that a seemingly simple achromatic behavior, namely phototaxis, is under the control of several independent pathways, each of which is responsible for navigation towards unique wavelengths. Silencing just one pathway is enough to disturb phototaxis towards one characteristic monochromatic source, whereas phototactic behavior towards white light is not affected. The response spectrum of each demonstrable pathway is different from that of individual photoreceptors, suggesting subtractive computations. A choice assay between two colors showed that these pathways are responsible for navigation towards, but not for the detection itself of, the monochromatic light. The present study provides novel insights about how visual information is separated and processed in parallel to achieve robust control of an innate 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 | 0.000 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".