IDEAS home Printed from https://ideas.repec.org/a/nat/nature/v436y2005i7047d10.1038_nature03689.html
   My bibliography  Save this article

Dynamic predictive coding by the retina

Author

Listed:
  • Toshihiko Hosoya

    (Harvard University
    RIKEN Brain Science Institute)

  • Stephen A. Baccus

    (Harvard University
    Stanford University)

  • Markus Meister

    (Harvard University)

Abstract

Retinal ganglion cells convey the visual image from the eye to the brain. They generally encode local differences in space and changes in time rather than the raw image intensity. This can be seen as a strategy of predictive coding, adapted through evolution to the average image statistics of the natural environment. Yet animals encounter many environments with visual statistics different from the average scene. Here we show that when this happens, the retina adjusts its processing dynamically. The spatio-temporal receptive fields of retinal ganglion cells change after a few seconds in a new environment. The changes are adaptive, in that the new receptive field improves predictive coding under the new image statistics. We show that a network model with plastic synapses can account for the large variety of observed adaptations.

Suggested Citation

  • Toshihiko Hosoya & Stephen A. Baccus & Markus Meister, 2005. "Dynamic predictive coding by the retina," Nature, Nature, vol. 436(7047), pages 71-77, July.
    • Handle: RePEc:nat:nature:v:436:y:2005:i:7047:d:10.1038_nature03689
    DOI: 10.1038/nature03689
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/nature03689
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1038/nature03689?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Miguel Maravall & Rasmus S Petersen & Adrienne L Fairhall & Ehsan Arabzadeh & Mathew E Diamond, 2007. "Shifts in Coding Properties and Maintenance of Information Transmission during Adaptation in Barrel Cortex," PLOS Biology, Public Library of Science, vol. 5(2), pages 1-12, January.
    2. Matthias S Keil & Agata Lapedriza & David Masip & Jordi Vitria, 2008. "Preferred Spatial Frequencies for Human Face Processing Are Associated with Optimal Class Discrimination in the Machine," PLOS ONE, Public Library of Science, vol. 3(7), pages 1-5, July.
    3. Marcus H C Howlett & Robert G Smith & Maarten Kamermans, 2017. "A novel mechanism of cone photoreceptor adaptation," PLOS Biology, Public Library of Science, vol. 15(4), pages 1-28, April.
    4. Gabriel D Puccini & Maria V Sanchez-Vives & Albert Compte, 2007. "Integrated Mechanisms of Anticipation and Rate-of-Change Computations in Cortical Circuits," PLOS Computational Biology, Public Library of Science, vol. 3(5), pages 1-13, May.
    5. Jian K Liu & Tim Gollisch, 2015. "Spike-Triggered Covariance Analysis Reveals Phenomenological Diversity of Contrast Adaptation in the Retina," PLOS Computational Biology, Public Library of Science, vol. 11(7), pages 1-30, July.
    6. Johnatan Aljadeff & Ronen Segev & Michael J Berry II & Tatyana O Sharpee, 2013. "Spike Triggered Covariance in Strongly Correlated Gaussian Stimuli," PLOS Computational Biology, Public Library of Science, vol. 9(9), pages 1-12, September.
    7. Matthias S Keil, 2009. "“I Look in Your Eyes, Honey”: Internal Face Features Induce Spatial Frequency Preference for Human Face Processing," PLOS Computational Biology, Public Library of Science, vol. 5(3), pages 1-13, March.
    8. Krishnamurthy V. Vemuru, 2022. "Implementation of the Canny Edge Detector Using a Spiking Neural Network," Future Internet, MDPI, vol. 14(12), pages 1-12, December.
    9. Tristan G. Heintz & Antonio J. Hinojosa & Sina E. Dominiak & Leon Lagnado, 2022. "Opposite forms of adaptation in mouse visual cortex are controlled by distinct inhibitory microcircuits," Nature Communications, Nature, vol. 13(1), pages 1-14, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:nature:v:436:y:2005:i:7047:d:10.1038_nature03689. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.