Natural environment statistics in the upper and lower visual field are reflected in mouse retinal specializations.

ON/OFF pathways color vision convolutional autoencoder efficient encoding mouse vision natural movies natural scene statistics retina ultraviolet light visual ecology

Journal

Current biology : CB
ISSN: 1879-0445
Titre abrégé: Curr Biol
Pays: England
ID NLM: 9107782

Informations de publication

Date de publication:
09 08 2021
Historique:
received: 10 01 2021
revised: 06 04 2021
accepted: 11 05 2021
pubmed: 10 6 2021
medline: 7 4 2022
entrez: 9 6 2021
Statut: ppublish

Résumé

Pressures for survival make sensory circuits adapted to a species' natural habitat and its behavioral challenges. Thus, to advance our understanding of the visual system, it is essential to consider an animal's specific visual environment by capturing natural scenes, characterizing their statistical regularities, and using them to probe visual computations. Mice, a prominent visual system model, have salient visual specializations, being dichromatic with enhanced sensitivity to green and UV in the dorsal and ventral retina, respectively. However, the characteristics of their visual environment that likely have driven these adaptations are rarely considered. Here, we built a UV-green-sensitive camera to record footage from mouse habitats. This footage is publicly available as a resource for mouse vision research. We found chromatic contrast to greatly diverge in the upper, but not the lower, visual field. Moreover, training a convolutional autoencoder on upper, but not lower, visual field scenes was sufficient for the emergence of color-opponent filters, suggesting that this environmental difference might have driven superior chromatic opponency in the ventral mouse retina, supporting color discrimination in the upper visual field. Furthermore, the upper visual field was biased toward dark UV contrasts, paralleled by more light-offset-sensitive ganglion cells in the ventral retina. Finally, footage recorded at twilight suggests that UV promotes aerial predator detection. Our findings support that natural scene statistics shaped early visual processing in evolution.

Identifiants

pubmed: 34107304
pii: S0960-9822(21)00676-X
doi: 10.1016/j.cub.2021.05.017
pii:
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

3233-3247.e6

Commentaires et corrections

Type : CommentIn

Informations de copyright

Copyright © 2021 Elsevier Inc. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of interests The authors declare no competing interests.

Auteurs

Yongrong Qiu (Y)

Institute for Ophthalmic Research, University of Tübingen, 72076 Tübingen, Germany; Centre for Integrative Neuroscience (CIN), University of Tübingen, 72076 Tübingen, Germany; Graduate Training Centre of Neuroscience (GTC), International Max Planck Research School, University of Tübingen, 72076 Tübingen, Germany.

Zhijian Zhao (Z)

Institute for Ophthalmic Research, University of Tübingen, 72076 Tübingen, Germany; Centre for Integrative Neuroscience (CIN), University of Tübingen, 72076 Tübingen, Germany.

David Klindt (D)

Institute for Ophthalmic Research, University of Tübingen, 72076 Tübingen, Germany; Centre for Integrative Neuroscience (CIN), University of Tübingen, 72076 Tübingen, Germany; Graduate Training Centre of Neuroscience (GTC), International Max Planck Research School, University of Tübingen, 72076 Tübingen, Germany.

Magdalena Kautzky (M)

Division of Neurobiology, Faculty of Biology, LMU Munich, 82152 Planegg-Martinsried, Germany; Graduate School of Systemic Neurosciences (GSN), LMU Munich, 82152 Planegg-Martinsried, Germany.

Klaudia P Szatko (KP)

Institute for Ophthalmic Research, University of Tübingen, 72076 Tübingen, Germany; Centre for Integrative Neuroscience (CIN), University of Tübingen, 72076 Tübingen, Germany; Graduate Training Centre of Neuroscience (GTC), International Max Planck Research School, University of Tübingen, 72076 Tübingen, Germany; Bernstein Centre for Computational Neuroscience, 72076 Tübingen, Germany.

Frank Schaeffel (F)

Institute for Ophthalmic Research, University of Tübingen, 72076 Tübingen, Germany.

Katharina Rifai (K)

Institute for Ophthalmic Research, University of Tübingen, 72076 Tübingen, Germany; Carl Zeiss Vision International GmbH, 73430 Aalen, Germany.

Katrin Franke (K)

Institute for Ophthalmic Research, University of Tübingen, 72076 Tübingen, Germany; Centre for Integrative Neuroscience (CIN), University of Tübingen, 72076 Tübingen, Germany; Bernstein Centre for Computational Neuroscience, 72076 Tübingen, Germany.

Laura Busse (L)

Division of Neurobiology, Faculty of Biology, LMU Munich, 82152 Planegg-Martinsried, Germany; Bernstein Centre for Computational Neuroscience, 82152 Planegg-Martinsried, Germany. Electronic address: busse@biologie.uni-muenchen.de.

Thomas Euler (T)

Institute for Ophthalmic Research, University of Tübingen, 72076 Tübingen, Germany; Centre for Integrative Neuroscience (CIN), University of Tübingen, 72076 Tübingen, Germany; Bernstein Centre for Computational Neuroscience, 72076 Tübingen, Germany. Electronic address: thomas.euler@cin.uni-tuebingen.de.

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