Connectivity of cone photoreceptor telodendria in the zebrafish retina
Bibliographic record
Abstract
The connectivity amongst photoreceptors is critical to their function, as it underpins lateral inhibition and effective translation of stimuli into neural signals. Despite much work characterizing second-order interneurons in the outer retina, the synapses directly connecting photoreceptors have often been overlooked. Telodendria are fine processes that connect photoreceptor pedicles. They have been observed in diverse vertebrate groups, yet their roles in vision remain speculative. Here, we visualize telodendria via fluorescent protein expression in photoreceptor subtypes. We characterized short wavelength cone telodendria in adult and larval zebrafish retina. Additionally, in the larval retina, we investigated rod telodendria and UV cone telodendria in mutant and transgenic retinas with altered complements of cone types. In the adult retina, telodendria are twice as abundant and branch almost twice as often on blue cones compared to UV cones. Pedicles of neighboring UV and blue cones typically converge into contiguous pairs, despite the regular spacing of their cell bodies. In contrast to adults, larval UV cone telodendria are more numerous (1.3 times) than blue cone telodendria. UV cone telodendria are not detectably affected by ablation of blue cones, and are reduced twofold in mutant larval retina with few UV cones. We thus saw no evidence that telodendria increase in number in the absence of their typical cellular neighbors. We also found that larval rod telodendria are less abundant than short wavelength cone telodendria. In summary, we describe the development and morphology of zebrafish photoreceptor synaptic connectivity toward appreciating the function of telodendria in visual signal processing.
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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".