Abstract

One of the most challenging topics in the study of human color vision is the investigation of the number of hue-selective channels that are necessary for the representation of color appearance at the post-opponent level and the bandwidth of their sensitivity. The present study aims to elucidate this issue by using a chromatic version of the notch-filtered noise (herein, notched-noise) stimulus for contrast adaptation. After adaptation to this stimulus, some color-sensitive mechanisms that selectively respond to missing hues in the notched-noise stimulus may remain sensitive, while the other mechanisms may be desensitized. The shifts in the color appearance of a gray test field after the adaptation to such a notched noise were measured using the method of adjustment. The results showed systematic shifts in the hue and saturation. They showed neither point nor line symmetric profiles with respect to the achromatic point in an isoluminant plane. The fittings of the results, obtained by using a tiny numerical model for assessing the hue-selective mechanisms, suggested that there are at least two narrowly tuned and at least three broadly tuned mechanisms. The narrowly tuned mechanisms are the most sensitive along the blue and yellow directions. The present study confirmed the variation of multiple channels at the post-opponent level and suggested that this variation may be responsible for the processing of color appearance.

© 2007 Optical Society of America

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  1. A. M. Derrington, J. Krauskopf, and P. Lennie, “Chromatic mechamisms in lateral geniculate nucleus of macaque,” J. Physiol. (London) 357, 241–265 (1984).
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    [Crossref] [PubMed]
  3. R. L. DeValois, N. P. Cottaris, S. D. Elfar, L. E. Mahon, and J. A. Wilson, “Some transformations of color information from lateral geniculate nucleus to striate cortex,” Proc. Natl. Acad. Sci. U.S.A. 97, 4997–5002 (2000).
    [Crossref]
  4. A. Hanazawa, H. Komatsu, and I. Murakami, “Neural selectivity for hue and saturation of colour in the primary visual cortex of the monkey,” Eur. J. Neurosci. 12, 1753–1763 (2000).
    [Crossref] [PubMed]
  5. D. Y. Ts’o and C. D. Gilbert, “The organization of chromatic and spatial interactions in the primate striate cortex,” J. Neurophysiol. 8, 1712–1727 (1988).
  6. P. Lennie, J. Krauskopf, and G. Sclar, “Chromatic mechanisms in striate cortex of macaque,” J. Neurosci. 10, 649–669 (1990).
    [PubMed]
  7. H. Sato, N. Katsuyama, H. Tamura, Y. Hata, and T. Tsumoto, “Broad-tuned chromatic imputs to color-selective neurons in the monkey visual cortex,” J. Neurophysiol. 72, 163–168 (1994).
    [PubMed]
  8. B. C. Kiper, S. B. Fenstemaker, and K. R. Gegenfurtner, “Chromatic properties of neurons in macaque area V2,” Visual Neurosci. 14, 1061–1072 (1997).
    [Crossref]
  9. A. W. Roe and D. Y. Ts’o, “Specificity of color connectivity between primate V1 and V2,” J. Neurophysiol. 77, 2719–2730 (1999).
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    [Crossref] [PubMed]
  11. Y. Xiao, Y. Wang, and D. J. Felleman, “A spatially organized representation of colour in macaque cortical area V2,” Nature 421, 535–539 (2003).
    [Crossref] [PubMed]
  12. J. Krauskopf, D. R. Williams, M. B. Mandler, and A. M. Brown, “Higher order color mechanisms,” Vision Res. 26, 23–32 (1986).
    [Crossref] [PubMed]
  13. M. A. Webster and J. D. Mollon, “Changes in colour appearance following post-receptoral adaptation,” Nature 349, 235–238 (1991).
    [Crossref] [PubMed]
  14. M. A. Webster and J. D. Mollon, “The influence of contrast adaptation on color appearance,” Vision Res. 34, 1993–2020 (1994).
    [Crossref] [PubMed]
  15. Q. Zaidi and A. G. Shapiro, “Adaptive orthogonalization of opponent-color signals,” Biol. Cybern. 69, 415–428 (1993).
    [Crossref] [PubMed]
  16. M. A. Webster and J. A. Wilson, “Interactions between chromatic adaptation and contrast adaptation in color appearance,” Vision Res. 40, 3801–3816 (2000).
    [Crossref] [PubMed]
  17. K. R. Gegenfurtner and D. C. Kiper, “Contrast detection in luminance and chromatic noise,” J. Opt. Soc. Am. A 9, 1880–1889 (1992).
    [Crossref] [PubMed]
  18. M. D and K. Knoblauch, “Spectral bandwidth for the detection of color,” Vision Res. 38, 3117–3128 (1998).
    [Crossref]
  19. N. Goda and M. Fujii, “Sensitivity to modulation of color distribution in multicolored textures,” Vision Res. 41, 2475–2485 (2001).
    [Crossref] [PubMed]
  20. R. T. Eskew, J. R. Newton, and F. Giulianini, “Chromatic detection and discrimination analyzed by a Bayesian classifier,” Vision Res. 41, 893–909 (2001).
    [Crossref] [PubMed]
  21. T. Hansen and K. R. Gegenfurtner, “Classification images for chromatic signal detection,” J. Opt. Soc. Am. A 22, 2081–2089 (2005).
    [Crossref]
  22. R. M. Boynton and C. X. Olson, “Locating basic colors in the OSA color space,” Color Res. Appl. 12, 94–105 (1987).
    [Crossref]
  23. K. Amano, K. Uchikawa, and I. Kuriki, “Characteristics of color memory for natural scenes,” J. Opt. Soc. Am. A 19, 1501–1514 (2002).
    [Crossref]
  24. M. A. Webster, G. Malkoc, A. C. Bilson, and S. M. Webster, “Color contrast and contextual influences on color appearance,” J. Vision 2, 505–519 (2002).
    [Crossref]
  25. K. S. Cardinal and D. C. Kiper, “The detection of colored Glass patterns,” J. Vision 3, 199–208 (2003).
    [Crossref]
  26. M.-J. F. Mandelli and D. C. Kiper, “The local and global processing of chromatic Glass patterns,” J. Vision 5, 405–416 (2005).
    [Crossref]
  27. J. A. Wilson and E. Switkes, “Integration of differing chromaticities in early and midlevel spatial vision,” J. Opt. Soc. Am. A 22, 2169–2181 (2005).
    [Crossref]
  28. T. Hansen and K. R. Gegenfurtner, “Higher level chromatic mechanisms for image segmentation,” J. Vision 6, 239–259 (2006).
    [Crossref]
  29. R. D. Patterson, “Auditory filter shapes derived with noise stimuli,” J. Acoust. Soc. Am. 59, 640–654 (1976).
    [Crossref] [PubMed]
  30. K. T. Mullen and M. A. Losada, “The spatial tuning of color and luminance peripheral vision measured with notch filtered noise masking,” Vision Res. 39, 721–731 (1999).
    [Crossref] [PubMed]
  31. D. Beer and D. I. A. MacLeod, “Pre-exposure to contrast selectively compresses the achromatic half-axes of color space,” Vision Res. 40, 3083–3088 (2000).
    [Crossref] [PubMed]
  32. V. C. Smith and J. Pokorny, “Spectral sensitivity of the foveal cone photopigments between 400 and 500nm,” Vision Res. 15, 161–171 (1975).
    [Crossref] [PubMed]
  33. D. I. A. MacLeod and R. M. Boynton, “Chromaticity diagram showing cone excitation by stimuli of equal luminance,” J. Opt. Soc. Am. 69, 1183–1186 (1979).
    [Crossref] [PubMed]
  34. K. R. Dobkins, G. R. Stoner, and T. D. Albright, “Perceptual, oculomotor, and neural responses to moving color plaids,” Perception 27, 681–709 (1998).
    [Crossref]
  35. T. Takeuchi, K. K. De, and J. L. Hardy, “The influence of color on the perception of luminance motion,” Vision Res. 43, 1159–1175 (2003).
    [Crossref] [PubMed]
  36. S. Nishida, J. Watanabe, I. Kuriki, and T. Tokimoto, “Human visual system integrates color signals along a motion trajectory,” Curr. Biol. 17, 366–372 (2007).
    [Crossref] [PubMed]
  37. C. Chubb, G. Sperling, and J. A. Solomon, “Texture interactions determine perceived contrast,” Proc. Natl. Acad. Sci. U.S.A. 86, 9631–9635 (1989).
    [Crossref] [PubMed]
  38. H. Akaike, “A new look at the statistical model identification,” IEEE Trans. Autom. Control 19, 716–723 (1974).
    [Crossref]
  39. Q. Zaidi and D. Halevy, “Visual mechanisms that signal the direction of color changes,” Vision Res. 33, 1037–1051 (1993).
    [Crossref] [PubMed]
  40. H. Komatsu, “Mechanisms of central color vision,” Curr. Opin. Neurobiol. 8, 503–508 (1998).
    [Crossref] [PubMed]
  41. A. J. Ahumada, “Perceptual classification images from Vernier acuity masked by noise,” Prog. Aerosp. Sci. 26, 18 (1996).
  42. R. L. DeValois, K. K. DeValois, E. Switkes, and L. Mahon, “Hue scaling of isoluminant and cone-specific lights,” Vision Res. 37, 885–897 (1997).
    [Crossref]
  43. M. A. Webster, E. Miyahara, G. Malkoc, and V. E. Raker, “Variations in normal color vision. II. Unique hues,” J. Opt. Soc. Am. A 17, 1545–1555 (2000).
    [Crossref]

2007 (1)

S. Nishida, J. Watanabe, I. Kuriki, and T. Tokimoto, “Human visual system integrates color signals along a motion trajectory,” Curr. Biol. 17, 366–372 (2007).
[Crossref] [PubMed]

2006 (1)

T. Hansen and K. R. Gegenfurtner, “Higher level chromatic mechanisms for image segmentation,” J. Vision 6, 239–259 (2006).
[Crossref]

2005 (3)

2003 (4)

K. S. Cardinal and D. C. Kiper, “The detection of colored Glass patterns,” J. Vision 3, 199–208 (2003).
[Crossref]

T. Wachtler, T. J. Sejnowski, and T. D. Albright, “Representation of color stimuli in awake macaque primary visual cortex,” Neuron 37, 681–691 (2003).
[Crossref] [PubMed]

Y. Xiao, Y. Wang, and D. J. Felleman, “A spatially organized representation of colour in macaque cortical area V2,” Nature 421, 535–539 (2003).
[Crossref] [PubMed]

T. Takeuchi, K. K. De, and J. L. Hardy, “The influence of color on the perception of luminance motion,” Vision Res. 43, 1159–1175 (2003).
[Crossref] [PubMed]

2002 (2)

K. Amano, K. Uchikawa, and I. Kuriki, “Characteristics of color memory for natural scenes,” J. Opt. Soc. Am. A 19, 1501–1514 (2002).
[Crossref]

M. A. Webster, G. Malkoc, A. C. Bilson, and S. M. Webster, “Color contrast and contextual influences on color appearance,” J. Vision 2, 505–519 (2002).
[Crossref]

2001 (2)

N. Goda and M. Fujii, “Sensitivity to modulation of color distribution in multicolored textures,” Vision Res. 41, 2475–2485 (2001).
[Crossref] [PubMed]

R. T. Eskew, J. R. Newton, and F. Giulianini, “Chromatic detection and discrimination analyzed by a Bayesian classifier,” Vision Res. 41, 893–909 (2001).
[Crossref] [PubMed]

2000 (5)

D. Beer and D. I. A. MacLeod, “Pre-exposure to contrast selectively compresses the achromatic half-axes of color space,” Vision Res. 40, 3083–3088 (2000).
[Crossref] [PubMed]

M. A. Webster and J. A. Wilson, “Interactions between chromatic adaptation and contrast adaptation in color appearance,” Vision Res. 40, 3801–3816 (2000).
[Crossref] [PubMed]

R. L. DeValois, N. P. Cottaris, S. D. Elfar, L. E. Mahon, and J. A. Wilson, “Some transformations of color information from lateral geniculate nucleus to striate cortex,” Proc. Natl. Acad. Sci. U.S.A. 97, 4997–5002 (2000).
[Crossref]

A. Hanazawa, H. Komatsu, and I. Murakami, “Neural selectivity for hue and saturation of colour in the primary visual cortex of the monkey,” Eur. J. Neurosci. 12, 1753–1763 (2000).
[Crossref] [PubMed]

M. A. Webster, E. Miyahara, G. Malkoc, and V. E. Raker, “Variations in normal color vision. II. Unique hues,” J. Opt. Soc. Am. A 17, 1545–1555 (2000).
[Crossref]

1999 (2)

A. W. Roe and D. Y. Ts’o, “Specificity of color connectivity between primate V1 and V2,” J. Neurophysiol. 77, 2719–2730 (1999).

K. T. Mullen and M. A. Losada, “The spatial tuning of color and luminance peripheral vision measured with notch filtered noise masking,” Vision Res. 39, 721–731 (1999).
[Crossref] [PubMed]

1998 (3)

K. R. Dobkins, G. R. Stoner, and T. D. Albright, “Perceptual, oculomotor, and neural responses to moving color plaids,” Perception 27, 681–709 (1998).
[Crossref]

M. D and K. Knoblauch, “Spectral bandwidth for the detection of color,” Vision Res. 38, 3117–3128 (1998).
[Crossref]

H. Komatsu, “Mechanisms of central color vision,” Curr. Opin. Neurobiol. 8, 503–508 (1998).
[Crossref] [PubMed]

1997 (2)

R. L. DeValois, K. K. DeValois, E. Switkes, and L. Mahon, “Hue scaling of isoluminant and cone-specific lights,” Vision Res. 37, 885–897 (1997).
[Crossref]

B. C. Kiper, S. B. Fenstemaker, and K. R. Gegenfurtner, “Chromatic properties of neurons in macaque area V2,” Visual Neurosci. 14, 1061–1072 (1997).
[Crossref]

1996 (1)

A. J. Ahumada, “Perceptual classification images from Vernier acuity masked by noise,” Prog. Aerosp. Sci. 26, 18 (1996).

1994 (2)

H. Sato, N. Katsuyama, H. Tamura, Y. Hata, and T. Tsumoto, “Broad-tuned chromatic imputs to color-selective neurons in the monkey visual cortex,” J. Neurophysiol. 72, 163–168 (1994).
[PubMed]

M. A. Webster and J. D. Mollon, “The influence of contrast adaptation on color appearance,” Vision Res. 34, 1993–2020 (1994).
[Crossref] [PubMed]

1993 (2)

Q. Zaidi and A. G. Shapiro, “Adaptive orthogonalization of opponent-color signals,” Biol. Cybern. 69, 415–428 (1993).
[Crossref] [PubMed]

Q. Zaidi and D. Halevy, “Visual mechanisms that signal the direction of color changes,” Vision Res. 33, 1037–1051 (1993).
[Crossref] [PubMed]

1992 (1)

1991 (1)

M. A. Webster and J. D. Mollon, “Changes in colour appearance following post-receptoral adaptation,” Nature 349, 235–238 (1991).
[Crossref] [PubMed]

1990 (1)

P. Lennie, J. Krauskopf, and G. Sclar, “Chromatic mechanisms in striate cortex of macaque,” J. Neurosci. 10, 649–669 (1990).
[PubMed]

1989 (1)

C. Chubb, G. Sperling, and J. A. Solomon, “Texture interactions determine perceived contrast,” Proc. Natl. Acad. Sci. U.S.A. 86, 9631–9635 (1989).
[Crossref] [PubMed]

1988 (1)

D. Y. Ts’o and C. D. Gilbert, “The organization of chromatic and spatial interactions in the primate striate cortex,” J. Neurophysiol. 8, 1712–1727 (1988).

1987 (1)

R. M. Boynton and C. X. Olson, “Locating basic colors in the OSA color space,” Color Res. Appl. 12, 94–105 (1987).
[Crossref]

1986 (1)

J. Krauskopf, D. R. Williams, M. B. Mandler, and A. M. Brown, “Higher order color mechanisms,” Vision Res. 26, 23–32 (1986).
[Crossref] [PubMed]

1984 (1)

A. M. Derrington, J. Krauskopf, and P. Lennie, “Chromatic mechamisms in lateral geniculate nucleus of macaque,” J. Physiol. (London) 357, 241–265 (1984).

1982 (1)

J. Krauskopf, D. R. Williams, and D. W. Heeley, “The cardinal directions of color space,” Vision Res. 22, 1123–1131 (1982).
[Crossref] [PubMed]

1979 (1)

1976 (1)

R. D. Patterson, “Auditory filter shapes derived with noise stimuli,” J. Acoust. Soc. Am. 59, 640–654 (1976).
[Crossref] [PubMed]

1975 (1)

V. C. Smith and J. Pokorny, “Spectral sensitivity of the foveal cone photopigments between 400 and 500nm,” Vision Res. 15, 161–171 (1975).
[Crossref] [PubMed]

1974 (1)

H. Akaike, “A new look at the statistical model identification,” IEEE Trans. Autom. Control 19, 716–723 (1974).
[Crossref]

Ahumada, A. J.

A. J. Ahumada, “Perceptual classification images from Vernier acuity masked by noise,” Prog. Aerosp. Sci. 26, 18 (1996).

Akaike, H.

H. Akaike, “A new look at the statistical model identification,” IEEE Trans. Autom. Control 19, 716–723 (1974).
[Crossref]

Albright, T. D.

T. Wachtler, T. J. Sejnowski, and T. D. Albright, “Representation of color stimuli in awake macaque primary visual cortex,” Neuron 37, 681–691 (2003).
[Crossref] [PubMed]

K. R. Dobkins, G. R. Stoner, and T. D. Albright, “Perceptual, oculomotor, and neural responses to moving color plaids,” Perception 27, 681–709 (1998).
[Crossref]

Amano, K.

Beer, D.

D. Beer and D. I. A. MacLeod, “Pre-exposure to contrast selectively compresses the achromatic half-axes of color space,” Vision Res. 40, 3083–3088 (2000).
[Crossref] [PubMed]

Bilson, A. C.

M. A. Webster, G. Malkoc, A. C. Bilson, and S. M. Webster, “Color contrast and contextual influences on color appearance,” J. Vision 2, 505–519 (2002).
[Crossref]

Boynton, R. M.

Brown, A. M.

J. Krauskopf, D. R. Williams, M. B. Mandler, and A. M. Brown, “Higher order color mechanisms,” Vision Res. 26, 23–32 (1986).
[Crossref] [PubMed]

Cardinal, K. S.

K. S. Cardinal and D. C. Kiper, “The detection of colored Glass patterns,” J. Vision 3, 199–208 (2003).
[Crossref]

Chubb, C.

C. Chubb, G. Sperling, and J. A. Solomon, “Texture interactions determine perceived contrast,” Proc. Natl. Acad. Sci. U.S.A. 86, 9631–9635 (1989).
[Crossref] [PubMed]

Cottaris, N. P.

R. L. DeValois, N. P. Cottaris, S. D. Elfar, L. E. Mahon, and J. A. Wilson, “Some transformations of color information from lateral geniculate nucleus to striate cortex,” Proc. Natl. Acad. Sci. U.S.A. 97, 4997–5002 (2000).
[Crossref]

D, M.

M. D and K. Knoblauch, “Spectral bandwidth for the detection of color,” Vision Res. 38, 3117–3128 (1998).
[Crossref]

De, K. K.

T. Takeuchi, K. K. De, and J. L. Hardy, “The influence of color on the perception of luminance motion,” Vision Res. 43, 1159–1175 (2003).
[Crossref] [PubMed]

Derrington, A. M.

A. M. Derrington, J. Krauskopf, and P. Lennie, “Chromatic mechamisms in lateral geniculate nucleus of macaque,” J. Physiol. (London) 357, 241–265 (1984).

DeValois, K. K.

R. L. DeValois, K. K. DeValois, E. Switkes, and L. Mahon, “Hue scaling of isoluminant and cone-specific lights,” Vision Res. 37, 885–897 (1997).
[Crossref]

DeValois, R. L.

R. L. DeValois, N. P. Cottaris, S. D. Elfar, L. E. Mahon, and J. A. Wilson, “Some transformations of color information from lateral geniculate nucleus to striate cortex,” Proc. Natl. Acad. Sci. U.S.A. 97, 4997–5002 (2000).
[Crossref]

R. L. DeValois, K. K. DeValois, E. Switkes, and L. Mahon, “Hue scaling of isoluminant and cone-specific lights,” Vision Res. 37, 885–897 (1997).
[Crossref]

Dobkins, K. R.

K. R. Dobkins, G. R. Stoner, and T. D. Albright, “Perceptual, oculomotor, and neural responses to moving color plaids,” Perception 27, 681–709 (1998).
[Crossref]

Elfar, S. D.

R. L. DeValois, N. P. Cottaris, S. D. Elfar, L. E. Mahon, and J. A. Wilson, “Some transformations of color information from lateral geniculate nucleus to striate cortex,” Proc. Natl. Acad. Sci. U.S.A. 97, 4997–5002 (2000).
[Crossref]

Eskew, R. T.

R. T. Eskew, J. R. Newton, and F. Giulianini, “Chromatic detection and discrimination analyzed by a Bayesian classifier,” Vision Res. 41, 893–909 (2001).
[Crossref] [PubMed]

Felleman, D. J.

Y. Xiao, Y. Wang, and D. J. Felleman, “A spatially organized representation of colour in macaque cortical area V2,” Nature 421, 535–539 (2003).
[Crossref] [PubMed]

Fenstemaker, S. B.

B. C. Kiper, S. B. Fenstemaker, and K. R. Gegenfurtner, “Chromatic properties of neurons in macaque area V2,” Visual Neurosci. 14, 1061–1072 (1997).
[Crossref]

Fujii, M.

N. Goda and M. Fujii, “Sensitivity to modulation of color distribution in multicolored textures,” Vision Res. 41, 2475–2485 (2001).
[Crossref] [PubMed]

Gegenfurtner, K. R.

T. Hansen and K. R. Gegenfurtner, “Higher level chromatic mechanisms for image segmentation,” J. Vision 6, 239–259 (2006).
[Crossref]

T. Hansen and K. R. Gegenfurtner, “Classification images for chromatic signal detection,” J. Opt. Soc. Am. A 22, 2081–2089 (2005).
[Crossref]

B. C. Kiper, S. B. Fenstemaker, and K. R. Gegenfurtner, “Chromatic properties of neurons in macaque area V2,” Visual Neurosci. 14, 1061–1072 (1997).
[Crossref]

K. R. Gegenfurtner and D. C. Kiper, “Contrast detection in luminance and chromatic noise,” J. Opt. Soc. Am. A 9, 1880–1889 (1992).
[Crossref] [PubMed]

Gilbert, C. D.

D. Y. Ts’o and C. D. Gilbert, “The organization of chromatic and spatial interactions in the primate striate cortex,” J. Neurophysiol. 8, 1712–1727 (1988).

Giulianini, F.

R. T. Eskew, J. R. Newton, and F. Giulianini, “Chromatic detection and discrimination analyzed by a Bayesian classifier,” Vision Res. 41, 893–909 (2001).
[Crossref] [PubMed]

Goda, N.

N. Goda and M. Fujii, “Sensitivity to modulation of color distribution in multicolored textures,” Vision Res. 41, 2475–2485 (2001).
[Crossref] [PubMed]

Halevy, D.

Q. Zaidi and D. Halevy, “Visual mechanisms that signal the direction of color changes,” Vision Res. 33, 1037–1051 (1993).
[Crossref] [PubMed]

Hanazawa, A.

A. Hanazawa, H. Komatsu, and I. Murakami, “Neural selectivity for hue and saturation of colour in the primary visual cortex of the monkey,” Eur. J. Neurosci. 12, 1753–1763 (2000).
[Crossref] [PubMed]

Hansen, T.

T. Hansen and K. R. Gegenfurtner, “Higher level chromatic mechanisms for image segmentation,” J. Vision 6, 239–259 (2006).
[Crossref]

T. Hansen and K. R. Gegenfurtner, “Classification images for chromatic signal detection,” J. Opt. Soc. Am. A 22, 2081–2089 (2005).
[Crossref]

Hardy, J. L.

T. Takeuchi, K. K. De, and J. L. Hardy, “The influence of color on the perception of luminance motion,” Vision Res. 43, 1159–1175 (2003).
[Crossref] [PubMed]

Hata, Y.

H. Sato, N. Katsuyama, H. Tamura, Y. Hata, and T. Tsumoto, “Broad-tuned chromatic imputs to color-selective neurons in the monkey visual cortex,” J. Neurophysiol. 72, 163–168 (1994).
[PubMed]

Heeley, D. W.

J. Krauskopf, D. R. Williams, and D. W. Heeley, “The cardinal directions of color space,” Vision Res. 22, 1123–1131 (1982).
[Crossref] [PubMed]

Katsuyama, N.

H. Sato, N. Katsuyama, H. Tamura, Y. Hata, and T. Tsumoto, “Broad-tuned chromatic imputs to color-selective neurons in the monkey visual cortex,” J. Neurophysiol. 72, 163–168 (1994).
[PubMed]

Kiper, B. C.

B. C. Kiper, S. B. Fenstemaker, and K. R. Gegenfurtner, “Chromatic properties of neurons in macaque area V2,” Visual Neurosci. 14, 1061–1072 (1997).
[Crossref]

Kiper, D. C.

M.-J. F. Mandelli and D. C. Kiper, “The local and global processing of chromatic Glass patterns,” J. Vision 5, 405–416 (2005).
[Crossref]

K. S. Cardinal and D. C. Kiper, “The detection of colored Glass patterns,” J. Vision 3, 199–208 (2003).
[Crossref]

K. R. Gegenfurtner and D. C. Kiper, “Contrast detection in luminance and chromatic noise,” J. Opt. Soc. Am. A 9, 1880–1889 (1992).
[Crossref] [PubMed]

Knoblauch, K.

M. D and K. Knoblauch, “Spectral bandwidth for the detection of color,” Vision Res. 38, 3117–3128 (1998).
[Crossref]

Komatsu, H.

A. Hanazawa, H. Komatsu, and I. Murakami, “Neural selectivity for hue and saturation of colour in the primary visual cortex of the monkey,” Eur. J. Neurosci. 12, 1753–1763 (2000).
[Crossref] [PubMed]

H. Komatsu, “Mechanisms of central color vision,” Curr. Opin. Neurobiol. 8, 503–508 (1998).
[Crossref] [PubMed]

Krauskopf, J.

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Neuron (1)

T. Wachtler, T. J. Sejnowski, and T. D. Albright, “Representation of color stimuli in awake macaque primary visual cortex,” Neuron 37, 681–691 (2003).
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R. L. DeValois, N. P. Cottaris, S. D. Elfar, L. E. Mahon, and J. A. Wilson, “Some transformations of color information from lateral geniculate nucleus to striate cortex,” Proc. Natl. Acad. Sci. U.S.A. 97, 4997–5002 (2000).
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[Crossref]

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[Crossref] [PubMed]

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T. Takeuchi, K. K. De, and J. L. Hardy, “The influence of color on the perception of luminance motion,” Vision Res. 43, 1159–1175 (2003).
[Crossref] [PubMed]

K. T. Mullen and M. A. Losada, “The spatial tuning of color and luminance peripheral vision measured with notch filtered noise masking,” Vision Res. 39, 721–731 (1999).
[Crossref] [PubMed]

D. Beer and D. I. A. MacLeod, “Pre-exposure to contrast selectively compresses the achromatic half-axes of color space,” Vision Res. 40, 3083–3088 (2000).
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B. C. Kiper, S. B. Fenstemaker, and K. R. Gegenfurtner, “Chromatic properties of neurons in macaque area V2,” Visual Neurosci. 14, 1061–1072 (1997).
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Figures (12)

Fig. 1
Fig. 1 Basic concept of the chromatic notched-noise stimulus used in the present study. The horizontal axis represents the chromatic axis that stimulates L and M cones differentially without altering S-cone responses; the vertical axis represents the other chromatic axis that selectively varies S-cone responses (see text for details). Gray circles on the dotted circle are hues selected by equal angular steps ( 6 deg ) in this plane except the range of the notch. The center direction of the notch represents the center hue of excluded colors, and the notch width represents the range of excluded hues. A center-of-gravity symbol in the third quadrant shows the approximate location of the mean chromaticity of colors employed in the notched-noise stimulus, which is approximately 13% of the radius from the origin when the notch width is 60 deg in this color space.

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Fig. 2
Fig. 2 Schematic view of stimulus. A fixation point was presented at the center of screen. Adapting and matching fields were presented on either the left or right side of the fixation point with the distance of 4.5 deg in visual angle to the center of the area. Adapting and matching fields were separated from the uniform gray background with a thin dark gap. Each adapting and matching field subtended 5.8 deg × 5.8 deg in visual angle. Inside the adapting area was a mosaic pattern tiled with square elements. The element size was selected from among 0.09, 0.36, and 0.72 deg depending on the experimental condition. The screen subtended 36 deg × 27 deg .

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Fig. 3
Fig. 3 Sequence of stimulus presentation. The adapting stimulus was presented, with noise on only one side of fixation, for 30 s for initial adaptation. A short blank period followed the adaptation, and the test stimulus was presented for 1 s on the side where the adapting noise had appeared. Subjects were allowed to start adjusting the color of the matching field (presented on the side not previously adapted to noise) at the beginning of stimulus presentation. A blank period of 3.5 s followed to allow subjects’ adjustments. A 5 s top-up adaptation period followed when the subject did not reach to a satisfactory match, and the pairs of 5 s of top-up adaptation and 5 s of matching phase ( 0.5 s of blank, 1 s of test stimulus presentation, and 3.5 s of blank with adjustment) were repeated until the subject reached a satisfactory match.

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Fig. 4
Fig. 4 Aftereffect of adaptation to isotropic noise. The meanings of the horizontal and vertical axes representations are identical to that in Fig. 1. Test stimuli were 12 hues of colors shown as open circles on the dotted-line circle. Thin radial lines indicate the direction of the test hue. The resulting matches (solid circles) differed from the test only in saturation and not in hue, as shown by their alignment with the thin radial lines; this implies that adaptation to isotropic-noise stimulus did not evoke any hue shift. However, there are continuous changes in the magnitude of the radius (saturation). These distortions are fit with an ellipsoid, and the fitting parameters were used to calibrate the data in Figs. 4, 6. For subject IK, a single ellipsoid was used to compensate for the distortion. For subject AM, the upper and bottom half were fit using different ellipses. The compensation was made so that the saturation (distance from origin) of the matches in the notched-noise condition could be expressed as a multiple of the saturation needed in the isotropic-noise condition.

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Fig. 5
Fig. 5 Color asymmetry after notched-noise adaptation for two subjects. Axes are the same as in Fig. 1. For each subject, four panels show the results from different notch-center directions: top right, 45 deg ; top left, 135 deg ; bottom left, 225 deg ; bottom right, 315 deg . Dotted oblique lines represent the center direction of notch. Solid and open circles represent the matched color for high ( threshold × 40 ) and low ( threshold × 20 ) saturation conditions, respectively. Crosses near the origin represent the result of matching for a gray test stimulus. For both subjects, symbols are shifted toward the direction of notch center, but the center of deviation is biased slightly away from the center of the notch.

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Fig. 6
Fig. 6 Distance of matched color from the origin. Zero on the horizontal axis represents the notch-center direction shown in Fig. 4. The shaded area around the horizontal axis of zero in each panel represents the range of the notch. The shaded area around zero represents the range of the notch. The vertical axis shows the distance of the matched color from the color that matched the gray test stimulus. Solid and open symbols correspond to the test conditions with higher and lower saturations, respectively. Angular direction (horizontal-axis value) of each symbol was calculated after the alignment of the achromatic point (crosses in Fig. 5).

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Fig. 7
Fig. 7 Color matches to a gray test stimulus after adaptation to notched noise. The direction of the notch varied with 30 deg step starting from 0 deg in the hue angle (shown by thin dotted lines). Horizontal and vertical axes are the same as in Fig. 4. Solid circles represent the mean of the matched color for each notch direction. They show slight and systematic deviation from the thin dotted lines. Moreover, note that the shape of the matched hue locus is asymmetric in this space.

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Fig. 8
Fig. 8 Relationships between notch-center and matched-hue directions. Horizontal and vertical axes represent the notch-center and matched-hue directions, respectively. Solid circles represent the mean of the matched result. There are systematic relationships similar among subjects.

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Fig. 9
Fig. 9 Data are replotted from Fig. 8, but the vertical axis represents the difference between the vertical and horizontal axis values in Fig. 8. There are systematic trends showing two peaks and troughs. One peak is small at around 45 deg , and the other is at approximately 240 deg . Since this pattern is not horizontally symmetric with 180 deg , this result implies that the resulting hue shifts are not a scaling distortion along some particular axis (see text for details).

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Fig. 10
Fig. 10 Result of adaptation to uniform field and to the notched-noise stimulus with different mosaic-element sizes. Different subjects are indicated by initials. Panels (a), (b), and (c) show the result of the uniform-field adaptation with the same chromaticity as the notched-noise stimulus used in experiment 2. There are slight modulations in saturation, but the angular directions of the symbols are aligned along the dotted lines. Panels (d), (e), and (f) show the result of notched-noise adaptation with a different mosaic-element size. Different symbols represent the results from different mosaic-element sizes; open circles, solid circles, and open triangles represent 0.9, 0.36 (same as in Fig. 5), and 0.72 deg conditions, respectively.

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Fig. 11
Fig. 11 Hue shifts for both uniform and notched-noise stimulus adaptation. The symbols are the same as those in Fig. 10. The symbols connected with the dotted and solid lines are for the uniform-field and the 0.36 deg element-size conditions, respectively. The smallest element-size condition (open circles) shows virtually the same hue shift as the uniform-field condition, but the shifts are of smaller magnitude than those for the larger element-size conditions.

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Fig. 12
Fig. 12 Confirmation of contrast adaptation to the oblique direction of cardinal-color space (Derrington et al. [1]). Horizontal and vertical axes represent the color axis in the L–M direction and the luminance axis, respectively. The scales of the axes are normalized by the magnitude of the discrimination threshold. Panels (a) and (b) show the results from two subjects after adaptation to the chromatic contrast modulation in 45 – 225 deg in this plane. Panels (c) and (d) show the results from the same subjects after adaptation to chromatic contrast modulation in the 135 – 315 deg direction. Open circles represent the result of color matching after contrast adaptation to the uniform field with temporal modulation in chromatic contrast at 1 Hz , and solid squares represent the result of color matching after adaptation to dynamic random-mosaic presentation of colors along the adaptation axis at 20 fps . The magnitude of the effect is relatively small in dynamic random-mosaic adaptation, but the distortions of the matched hue locus along the axis of contrast adaptation are similar to the contrast adaptation to the 1 Hz uniform stimulus.

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Tables (1)

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Table 1 Estimated Peak-Hue Directions and Bandwidths of Hue-Selective Mechanisms

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Equations (12)

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L c o n t = Δ L L w ,
S c o n t = Δ S S w ,
L color = ( 1 + Δ L max * cos ( hue − angle ) ) × L w ,
M color = L w + M w − L color ,
S color = ( 1 + Δ S max * sin ( hue − angle ) ) × S w ,
f i ( θ ) = a i G ( θ − μ i , σ i ) ,
G ( x , σ ) = 1 2 π σ e − ( x ∕ σ ) 2 .
∑ i = 1 M a i cos ( μ i ) = 0 ,
∑ i = 1 M a i sin ( μ i ) = 0 ,
b i = [ ∑ j = 1 N N f i ( θ j ) ] − c ,
Δ L L w = ∑ i = 1 M b i a i cos ( μ i ) ,
Δ S S w = ∑ i = 1 M b i a i sin ( μ i ) ,

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