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Adaptation of retinal processing to image contrast and spatial scale

Author

Listed:
  • Stelios M. Smirnakis

    (Harvard University)

  • Michael J. Berry

    (Harvard University)

  • David K. Warland

    (Harvard University)

  • William Bialek
  • Markus Meister

    (Harvard University)

Abstract

Owing to the limited dynamic range of a neuron's output, neural circuits are faced with a trade-off between encoding the full range of their inputs and resolving gradations among those inputs. For example, the ambient light level varies daily over more than nine orders of magnitude1, whereas the firing rate of optic nerve fibres spans less than two2. This discrepancy is alleviated by light adaptation3: as the mean intensity increases, the retina becomes proportionately less sensitive. However, image statistics other than the mean intensity also vary drastically during routine visual processing. Theory predicts that an efficient visual encoder should adapt its strategy not only to the mean, but to the full shape of the intensity distribution4–6. Here we report that retinal ganglion cells, the output neurons of the retina, adapt to both image contrast—the range of light intensities—and to spatial correlations within the scene, even at constant mean intensity. The adaptation occurs on a scale of seconds, one hundred times more slowly than the immediate light response, and involves 2–5-fold changes in the firing rate. It is mediated within the retinal network: two independent sites of modulation after the photo-receptor cells appear to be involved. Our results demonstrate a remarkable plasticity in retinal processing that may contribute to the contrast adaptation of human vision7.

Suggested Citation

  • Stelios M. Smirnakis & Michael J. Berry & David K. Warland & William Bialek & Markus Meister, 1997. "Adaptation of retinal processing to image contrast and spatial scale," Nature, Nature, vol. 386(6620), pages 69-73, March.
    • Handle: RePEc:nat:nature:v:386:y:1997:i:6620:d:10.1038_386069a0
    DOI: 10.1038/386069a0
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    Citations

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    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. 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.
    3. Mark L Ioffe & Michael J Berry II, 2017. "The structured ‘low temperature’ phase of the retinal population code," PLOS Computational Biology, Public Library of Science, vol. 13(10), pages 1-31, October.
    4. 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.
    5. Joanna Bryson, 2008. "Embodiment versus memetics," Mind & Society: Cognitive Studies in Economics and Social Sciences, Springer;Fondazione Rosselli, vol. 7(1), pages 77-94, June.
    6. Sungho Hong & Brian Nils Lundstrom & Adrienne L Fairhall, 2008. "Intrinsic Gain Modulation and Adaptive Neural Coding," PLOS Computational Biology, Public Library of Science, vol. 4(7), pages 1-11, July.
    7. Jason S Prentice & Olivier Marre & Mark L Ioffe & Adrianna R Loback & Gašper Tkačik & Michael J Berry II, 2016. "Error-Robust Modes of the Retinal Population Code," PLOS Computational Biology, Public Library of Science, vol. 12(11), pages 1-32, November.
    8. 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.
    9. Katherine R. Storrs & Barton L. Anderson & Roland W. Fleming, 2021. "Unsupervised learning predicts human perception and misperception of gloss," Nature Human Behaviour, Nature, vol. 5(10), pages 1402-1417, October.

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