Retinal Region of Polarization Sensitivity Switches during Ontogeny of Rainbow Trout
Bibliographic record
Abstract
Polarization sensitivity (PS) in vertebrate vision is controversial, perhaps because its underlying mechanism has remained obscure. An issue that might have added to the controversy is that rainbow trout (Oncorhynchus mykiss), which have served as the primary model system for polarization-based orientation, lose their ability to orient relative to celestial polarized-light patterns when parr (fry) transform into migratory smolts (juveniles), which would benefit most from polarization-based orientation. Here we addressed two key questions: (1) what is the mechanism underling PS?, and (2) how can the paradoxical loss of PS in trout smolts be reconciled? We assessed PS from optic nerve recordings in parr and smolts and found that the retinal region with enhanced PS shifted from the ventral retina in parr to the dorsal retina in smolts. This adaptation may allow fish to use the most reliable polarization field encountered at each life stage, the celestial polarization field in the shallow-swimming parr and the depth-insensitive underwater polarization field in the deep-swimming smolts. In addition, we assessed spectral sensitivity across the retina and during ontogeny and fit a cascade retinal model to PS data. We found that differential contribution of two cone detectors with orthogonal PS could drive the variation in PS and that feedback from horizontal cells to cones could explain the differential amplification of PS. This elegant arrangement, in which weak PS of cones is amplified and tuned by retinal networks, allows for PS without interfering with sampling of other visual information and illustrates how sensory systems may simultaneously process disparate aspects of physical environments.
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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 | 0.001 |
| 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".