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Colour Constancy Across the Life Span: Evidence for Compensatory Mechanisms

Overview of attention for article published in PLOS ONE, May 2013
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Title
Colour Constancy Across the Life Span: Evidence for Compensatory Mechanisms
Published in
PLOS ONE, May 2013
DOI 10.1371/journal.pone.0063921
Pubmed ID
Authors

Sophie Wuerger

Abstract

It is well known that the peripheral visual system declines with age: the yellowing of the lens causes a selective reduction of short-wavelength light and sensitivity losses occur in the cone receptor mechanisms. At the same time, our subjective experience of colour does not change with age. The main purpose of this large-scale study (nā€Š=ā€Š185) covering a wide age range of colour-normal observers (18-75 years of age) was to assess the extent to which the human visual system is able to compensate for the changes in the optical media and at which level of processing this compensation is likely to occur. We report two main results: (1) Supra-threshold parafoveal colour perception remains largely unaffected by the age-related changes in the optical media (yellowing of the lens) whereas our ability to discriminate between small colour differences is compromised with an increase in age. (2) Significant changes in colour appearance are only found for unique green settings under daylight viewing condition which is consistent with the idea that the yellow-blue mechanism is most affected by an increase in age due to selective attenuation of short-wavelength light. The data on the invariance of hue perception, in conjunction with the age-related decline in chromatic sensitivity, provides evidence for compensatory mechanisms that enable colour-normal human observers a large degree of colour constancy across the life span. These compensatory mechanisms are likely to originate at cortical sites.

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Geographical breakdown

Country Count As %
United Kingdom 3 5%
Switzerland 1 2%
Canada 1 2%
Japan 1 2%
United States 1 2%
Unknown 57 89%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 22 34%
Researcher 12 19%
Student > Bachelor 6 9%
Student > Master 6 9%
Professor 4 6%
Other 5 8%
Unknown 9 14%
Readers by discipline Count As %
Psychology 17 27%
Neuroscience 11 17%
Engineering 8 13%
Agricultural and Biological Sciences 4 6%
Computer Science 4 6%
Other 8 13%
Unknown 12 19%