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Dynamic predictive coding by the retina

Nature volume 436, pages 7177 (07 July 2005) | Download Citation

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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.

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Acknowledgements

We thank members of the Meister laboratory, H. Sompolinsky and D. Fisher for advice. This work was supported by grants from the National Eye Institute (M.M. and S.A.B.) and the Human Frontier Science Program (T.H.).Author Contributions T.H. and M.M. planned the study, T.H. and S.A.B. performed the experiments, and T.H. and M.M. completed the analysis and wrote the manuscript.

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Author notes

    • Toshihiko Hosoya
    •  & Stephen A. Baccus

    †Present addresses: RIKEN Brain Science Institute, 2-1 Hirosawa, Wako-shi, Saitama 351-0198, Japan (T.H.); Department of Neurobiology, Stanford University, Stanford, California 94305, USA (S.A.B.)

Affiliations

  1. Department of Molecular and Cellular Biology, Harvard University, Cambridge, Massachusetts 02138, USA

    • Toshihiko Hosoya
    • , Stephen A. Baccus
    •  & Markus Meister

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Reprints and permissions information is available at npg.nature.com/reprintsandpermissions. The authors declare no competing financial interests.

Corresponding author

Correspondence to Markus Meister.

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    Supplementary Notes

    This contains Supplementary Methods and Legends to accompany Supplementary Figures S1-S3

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https://doi.org/10.1038/nature03689

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