Literature DB >> 16001064

Dynamic predictive coding by the retina.

Toshihiko Hosoya1, Stephen A Baccus, Markus Meister.   

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.

Mesh:

Year:  2005        PMID: 16001064     DOI: 10.1038/nature03689

Source DB:  PubMed          Journal:  Nature        ISSN: 0028-0836            Impact factor:   49.962


  150 in total

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10.  Deep Learning Models of the Retinal Response to Natural Scenes.

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Journal:  Adv Neural Inf Process Syst       Date:  2016
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