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Adaptive Colour Contrast Coding in the Salamander Retina Efficiently Matches Natural Scene Statistics

Overview of attention for article published in PLOS ONE, October 2013
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Title
Adaptive Colour Contrast Coding in the Salamander Retina Efficiently Matches Natural Scene Statistics
Published in
PLOS ONE, October 2013
DOI 10.1371/journal.pone.0079163
Pubmed ID
Authors

Genadiy Vasserman, Elad Schneidman, Ronen Segev

Abstract

The visual system continually adjusts its sensitivity to the statistical properties of the environment through an adaptation process that starts in the retina. Colour perception and processing is commonly thought to occur mainly in high visual areas, and indeed most evidence for chromatic colour contrast adaptation comes from cortical studies. We show that colour contrast adaptation starts in the retina where ganglion cells adjust their responses to the spectral properties of the environment. We demonstrate that the ganglion cells match their responses to red-blue stimulus combinations according to the relative contrast of each of the input channels by rotating their functional response properties in colour space. Using measurements of the chromatic statistics of natural environments, we show that the retina balances inputs from the two (red and blue) stimulated colour channels, as would be expected from theoretical optimal behaviour. Our results suggest that colour is encoded in the retina based on the efficient processing of spectral information that matches spectral combinations in natural scenes on the colour processing level.

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The data shown below were compiled from readership statistics for 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Malaysia 1 4%
Finland 1 4%
Portugal 1 4%
Germany 1 4%
Unknown 19 83%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 26%
Researcher 5 22%
Student > Master 4 17%
Student > Bachelor 2 9%
Student > Postgraduate 2 9%
Other 2 9%
Unknown 2 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 7 30%
Neuroscience 4 17%
Psychology 2 9%
Computer Science 1 4%
Veterinary Science and Veterinary Medicine 1 4%
Other 4 17%
Unknown 4 17%