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Dryad

Two-photon calcium recordings of cones

Cite this dataset

Yoshimatsu, Takeshi et al. (2021). Two-photon calcium recordings of cones [Dataset]. Dryad. https://doi.org/10.5061/dryad.pzgmsbcmk

Abstract

For colour vision, retinal circuits separate information about intensity and wavelength. This requires circuit-level comparison of at least two spectrally distinct photoreceptors. However, many vertebrates use all four ‘ancestral’ photoreceptors (‘red’, ‘green’, ‘blue’, ‘UV’), and in those cases the nature and implementation of this computation remains poorly understood. Here, we establish the complete circuit architecture of outer retinal circuits underlying colour processing in the tetrachromatic larval zebrafish, which involves all four ancestral cone types and three types of horizontal cells. Our findings reveal that the synaptic outputs of red- and green-cones efficiently rotate the encoding of natural daylight in a principal component analysis (PCA)-like manner to yield primary achromatic and spectrally-opponent axes, respectively. Together, these two cones capture 91.3% of the spectral variance in natural light. Next, blue-cones are tuned so as to capture most remaining variance when opposed to green-cones. Finally, UV-cones present a UV-achromatic axis for prey capture. We note that fruit flies – the only other tetrachromat species where comparable circuit-level information is available - use essentially the same strategy to extract spectral information from their relatively blue-shifted terrestrial visual world. Together, our results suggest that rotating colour space into primary achromatic and chromatic axes at the eye’s first synapse may be a fundamental principle of colour vision when using more than two spectrally well-separated photoreceptor types.

Methods

The data was collected from zebrafish larvae (7 days post-fertilisation) expressing SyGCaMP6f in each cone type. SyGCaMP6f fluorescent images during visual stimulation were recorded on a custom built two-photon microscope. Detailed information is in the manuscript.

Funding

European Research Council, Award: ERC-StG “NeuroVisEco” 677687

Wellcome Trust, Award: Investigator Award in Science 220277/Z20/Z

UK Research and Innovation, Award: BBSRC

Federal Ministry of Education and Research, Award: 01GQ1601

German Research Foundation, Award: BE5601/4-1

Leverhulme Trust, Award: PLP-2017-005

Lister Institute of Preventive Medicine

Marie Curie Sklodowska Actions individual fellowship, Award: (“ColourFish” 748716

McNair Medical Foundation

Welch Foundation, Award: Q-2016-20190330

National Institutes of Health, Award: R01EB027145

National Science Foundation, Award: NeuroNex 1707359

National Institutes of Health, Award: EY01730

UK Research and Innovation, Award: BB/R014817/1

German Research Foundation, Award: EXC 2064 – 390727645

National Science Foundation, Award: IdeasLab 1935265

National Institutes of Health, Award: U01NS113294

Federal Ministry of Education and Research, Award: 01IS18052C

Federal Ministry of Education and Research, Award: 01IS18039A

Deutsche Forschungsgemeinschaft, Award: BE5601/4-1

Marie Curie Sklodowska Actions individual fellowship, Award: (“ColourFish” 748716

McNair Medical Foundation