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Quantification of color vision with cone contrast sensitivity

Published online by Cambridge University Press:  05 April 2005

JEFF RABIN
JEFF RABIN
Affiliation:
College of Optometry, Pacific University, and U.S. Army Aeromedical Research Laboratory, Fort Rucker
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Abstract

Human color vision is based fundamentally on three separate cone photopigments. Hereditary color deficiency, which affects up to 10% of males, results from an absorption shift or lack of L or M cone phototoreceptors. While hereditary S cone deficiency is rare, decreased S cone sensitivity occurs early in eye disease, underscoring the importance of quantifying S cone function. Our purpose is to describe a novel approach for quantifying human color vision based on the photopigments of normal color vision. Colored letters, visible to a single cone type, are presented in graded steps of cone contrast to determine the threshold for letter recognition. This approach quantifies normal color vision, indicates type and severity of hereditary deficiency, and reveals sensitivity decrements in various diseases.

Keywords

Contrast sensitivityCone contrastColor visionVisual acuity
Type
Research Article
Information
Visual Neuroscience , Volume 21 , Issue 3 , May 2004 , pp. 483 - 485
Copyright
© 2004 Cambridge University Press

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References

REFERENCES

Adams, A.J. (1982). Chromatic and luminosity processing in retinal disease. American Journal of Optometry and Physiological Optics 59, 954–960.Google Scholar
Bailey, I.L., Bullimore, M.A., Raasch, T.W., & Taylor, H.R. (1991). Clinical grading and the effects of scaling. Investigative Ophthalmology and Visual Science 32, 422–432.Google Scholar
Carroll, J., Neitz, J., & Neitz, M. (2003). Estimates of L:M cone ratio from ERG flicker photometry and genetics. Journal of Vision 2, 531–542.Google Scholar
Cole, G.R. & Hine, T. (1992). Computation of cone contrasts for color vision research. Behavior Research Methods, Instruments, and Computers 24, 22–27.Google Scholar
Greenstein, V.C., Hood, D.C., Ritch, R., Steinberger, D., & Carr, R.E. (1989). S (Blue) cone pathway vulnerability in retinitis pigmentosa, diabetes and glaucoma. Investigative Ophthalmology and Visual Science 30, 1732–1737.Google Scholar
Mollon, J.D. & Reffin, J.P. (1989). A computer-controlled colour vision test that combines principles of Chibret and Stilling. Journal of Physiology 414, 5P.Google Scholar
Rabin, J. (1996). Cone specific measures of human color vision. Investigative Ophthalmology and Visual Science 37, 2771–2774.Google Scholar
Regan, B.C., Reffin, J.P., & Mollon, J.D. (1994). Luminance noise and the rapid determination of discrimination ellipses in colour deficiency. Vision Research 34, 1279–1299.CrossRefGoogle Scholar
Sakmar, T.P. (2003). In Adler's Physiology of the Eye: Clinical Application (10th Edition), ed. Kaufan, P.L. & Alm, A., Ch 23: Color Vision, pp. 583–584. St. Louis: Mosby.
Smith, V.C. & Pokorny, J. (1975). Spectral sensitivity of the foveal cone pigments between 400 and 500 nm. Vision Research 15, 161–171.CrossRefGoogle Scholar