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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Biophysical neural adaptation mechanisms enable artificial neural networks to capture dynamic retinal computation
Temporal pattern recognition in retinal ganglion cells is mediated by dynamical inhibitory synapses
Nonlinear receptive fields evoke redundant retinal coding of natural scenes
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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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Hosoya, T., Baccus, S. & Meister, M. Dynamic predictive coding by the retina. Nature 436, 71β77 (2005). https://doi.org/10.1038/nature03689
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DOI: https://doi.org/10.1038/nature03689
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