Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

Natural Image Statistics for Mouse Vision

Luca Abballe, View ORCID ProfileHiroki Asari
doi: https://doi.org/10.1101/2021.04.08.438953
Luca Abballe
1Department of Biomedical Engineering, Sapienza University of Rome, Rome RM, 00185, Italy
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Hiroki Asari
2Epigenetics and Neurobiology Unit, EMBL Rome, European Molecular Biology Laboratory, Monterotondo RM, 00015, Italy
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Hiroki Asari
  • For correspondence: asari@embl.it
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Preview PDF
Loading

Abstract

The mouse has dichromatic color vision based on two different types of opsins: short (S)- and middle (M)-wavelength-sensitive opsins with peak sensitivity to ultraviolet (UV; 360 nm) and green light (508 nm), respectively. In the mouse retina, cone photoreceptors that predominantly express the S-opsin are more sensitive to contrasts and denser towards the ventral retina, preferentially sampling the upper part of the visual field. In contrast, the expression of the M-opsin gradually increases towards the dorsal retina that encodes the lower visual field. Such a distinctive retinal organization is assumed to arise from a selective pressure in evolution to efficiently encode the natural scenes. However, natural image statistics of UV light remain largely unexplored. Here we developed a multi-spectral camera to acquire high-quality UV and green images of the same natural scenes, and examined the optimality of the mouse retina to the image statistics. We found that the local contrast and the spatial correlation were both higher in UV than in green for images above the horizon, but lower in UV than in green for those below the horizon. This suggests that the dorsoventral functional division of the mouse retina is not optimal for maximizing the bandwidth of information transmission. Factors besides the coding efficiency, such as visual behavioral requirements, will thus need to be considered to fully explain the characteristic organization of the mouse retina.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
Back to top
PreviousNext
Posted November 18, 2021.
Download PDF
Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
Natural Image Statistics for Mouse Vision
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
Natural Image Statistics for Mouse Vision
Luca Abballe, Hiroki Asari
bioRxiv 2021.04.08.438953; doi: https://doi.org/10.1101/2021.04.08.438953
Reddit logo Twitter logo Facebook logo LinkedIn logo Mendeley logo
Citation Tools
Natural Image Statistics for Mouse Vision
Luca Abballe, Hiroki Asari
bioRxiv 2021.04.08.438953; doi: https://doi.org/10.1101/2021.04.08.438953

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Neuroscience
Subject Areas
All Articles
  • Animal Behavior and Cognition (4369)
  • Biochemistry (9546)
  • Bioengineering (7068)
  • Bioinformatics (24768)
  • Biophysics (12562)
  • Cancer Biology (9924)
  • Cell Biology (14297)
  • Clinical Trials (138)
  • Developmental Biology (7930)
  • Ecology (12074)
  • Epidemiology (2067)
  • Evolutionary Biology (15954)
  • Genetics (10904)
  • Genomics (14707)
  • Immunology (9844)
  • Microbiology (23582)
  • Molecular Biology (9454)
  • Neuroscience (50692)
  • Paleontology (369)
  • Pathology (1535)
  • Pharmacology and Toxicology (2674)
  • Physiology (3998)
  • Plant Biology (8639)
  • Scientific Communication and Education (1505)
  • Synthetic Biology (2388)
  • Systems Biology (6415)
  • Zoology (1344)