Hostname: page-component-8448b6f56d-c47g7 Total loading time: 0 Render date: 2024-04-20T03:04:21.960Z Has data issue: false hasContentIssue false
  • English
  • Français

Perceptual classification of chromatic modulation

Published online by Cambridge University Press:  05 April 2005

ROMAIN BOUET  and
KENNETH KNOBLAUCH
ROMAIN BOUET
Affiliation:
Institut National de la Santé et de la Recherche Médicale, Cerveau et Vision, Bron cedex, France Institut F édératif des Neurosciences de Lyon, Lyon, France
KENNETH KNOBLAUCH
Affiliation:
Institut National de la Santé et de la Recherche Médicale, Cerveau et Vision, Bron cedex, France Institut F édératif des Neurosciences de Lyon, Lyon, France
Get access Rights & Permissions [Opens in a new window]

Abstract

We measured the regions of the equiluminant plane that are exploited by observers during a Yes/No detection task. The signal was a 640-ms Gaussian modulation (σt = 160 ms) of a Gaussian spatial patch (σs = 2.4 deg) presented in chromatically bivariate uniform noise. One component of the noise was along the direction axial with the signal in color space, the other perpendicular. Four signal directions were tested: along cardinal LM and S axes and two intermediate directions to which the cardinal axes were equally sensitive. The distribution of noise chromaticities from each trial was correlated with the observers' responses and the presence and absence of the signal to build a classification image of the distribution of chromaticities on which the decision of the observer was based. The images show a narrowly selective peak in the signal direction flanked by regions with a broader selectivity. These results raise the possibility that detection judgments are mediated by both linear and nonlinear mechanisms with peak sensitivities between the cardinal directions.

Keywords

Color visionColor discriminationColor mechanismsPsychophysicsSignal-detection theory
Type
Research Article
Information
Visual Neuroscience , Volume 21 , Issue 3 , May 2004 , pp. 283 - 289
Copyright
© 2004 Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Ahumada, A.J. (2002). Classification image weights and internal noise level estimation. Journal of Vision 2, 121–131.Google Scholar
Ahumada, A.J. & Lovell, J. (1971). Stimulus features in signal detection, Journal of the Acoustical Society of America 49, 1751–1756.Google Scholar
Bouet, R. & Knoblauch, K. (2003). Spectral bandwidths of colour detection mechanisms revisited. Perception, 32 (Suppl.), 39–40.Google Scholar
Cardinal, K.S. & Kiper, D.C. (2003). The detection of colored Glass spatterns. Journal of Vision 3(3), 199–208.Google Scholar
Dacey, D.M. & Lee, B.B. (1994). The “blue-on” opponent pathway in primate retina originates from a distinct bistratified ganglion cell type. Nature 367, 731–735.Google Scholar
Dartnall, H.J.A., Bowmaker, J.K., & Mollon, J.D. (1983). Human visual pigments: Microspectrophotometric results from the eyes of seven persons. Proceedings of the Royal Society B (London) 220, 115–130.Google Scholar
Derrington, A.M., Krauskopf, J., & Lennie, P. (1984). Chromatic mechanisms in lateral geniculate nucleus of macaque. Journal of Physiology 357, 241–265.Google Scholar
DeValois, R.L., Abramov, I., & Jacobs, G.H. (1966). Analysis of of response patterns of LGN cells. Journal of the Optical Society of America 56, 966–977.Google Scholar
DeValois, R.L., Cottaris, N.P., Elfar, S.D., Mahon, L.E., & Wilson, J.A. (2000). Some transformations of color information from lateral geniculate nucleus to striate cortex. Proceedings of the National Academy of Sciences of the U.S.A. 97, 4997–5002.Google Scholar
D'Zmura, M. (1991). Color in visual search. Vision Research 31, 951–966.Google Scholar
D'Zmura, M. & Knoblauch, K. (1998). Spectral bandwidths for the detection of color. Vision Research 38, 3117–3128.Google Scholar
Eskew, R.T., Jr., Newton, J.R., & Giulianini, F. (2001). Chromatic detection and discrimination analyzed by a Bayesian classifier. Vision Research 41, 893–909.Google Scholar
Gegenfurtner, K.R. & Kiper, D.C. (1992). Contrast detection in luminance and chromatic noise. Journal of Optical Society of America A 9, 1880–1888.Google Scholar
Giulianini, F. & Eskew, R.T., Jr. (1998). Chromatic masking in the (ΔL/L, ΔM/M) plane of cone-contrast space reveals only two detection mechanisms. Vision Research 38, 3913–3926.Google Scholar
Goda, N. & Fuji, M. (2001). Sensitivity to modulation of color distribution in multicolored textures. Vision Research 41, 2475–2485.Google Scholar
Hansen, T. & Gegenfurtner, K. (2003). Classification images for chromatic signal detection. Perception 32 (Suppl.), 40.Google Scholar
Hays, W.L. (1973). Statistics for the Social Sciences, 2nd edition. New York: Holt, Rinehart and Winston.
Kaiser, P. & Boynton, R.M. (1996). Human Color Vision, 2nd edition. Washington, DC: Optical Society of America.
Kiper, D.C., Fenstemaker, S.B., & Gegenfurtner, K.R. (1997). Chromatic properties of neurons in macaque area V2. Visual Neuroscience 14, 1061–1072.Google Scholar
Knoblauch, K. (2002). Color Vision. In Yantis, S. (volume editor) and Pashler, H. (series editor), Stevens' Handbook of Experimental Psychology, 3rd edition, New York: Wiley.
Krauskopf, J., Williams, D.R., & Heeley, D.W. (1982). Cardinal directions in color space. Vision Research 22, 1123–1131.Google Scholar
Krauskopf, J., Williams, D.R., Mandler, M.B., & Brown, A.M. (1986). Higher order color mechanisms. Vision Research 26, 23–32.Google Scholar
Lennie, P., Krauskopf, J., & Sklar, G. (1990). Chromatic mechanisms in striate cortex of macaque. Journal of Neuroscience 10, 649–669.Google Scholar
MacLeod, D.I.A. & Boynton, R.M. (1979). Chromaticity diagram showing cone excitation by stimuli of equal luminance. Journal of the Optical Society of America 69, 1183–1186.Google Scholar
Monaci, G., Menegaz, G., Süsstrunck, S., & Knoblauch K. (2004). Chromatic contrast detection in spatial chromatic noise. Visual Neuroscience 21, 291–294.Google Scholar
Nathans, J., Thomas, D., & Hogness, D.S. (1986). Molecular genetics of human color vision: The genes encoding blue, green and red pigments. Science 232, 193–202.Google Scholar
Sankeralli, M.J. & Mullen, K.T. (1997). Postreceptoral chromatic detection mechanisms revealed by noise masking in three-dimensional cone contrast space. Journal of the Optical Society of America A 14, 2633–2646.Google Scholar
Schnapf, J.L., Kraft, T.W., & Baylor, D.A. (1987). Spectral sensitivity of human cone photoreceptors. Nature 325, 439–441.Google Scholar
Shapley, R. (1990) Visual sensitivity and parallel retinocortical channels. Annual Review of Psychology 41, 635–658.Google Scholar
Stiles, W.S. (1953). Further studies of visual mechanisms by the two-colour threshold method. Reprinted from Colloq. Probl. Opt. Vis., (U.I.P.A.P., Madrid, Vol. 1, 1953, pp. 65–103) in Mechanisms of Colour Vision, Selected Papers of W.S. Stiles, F.R.S. with a new introductory essay. Academic Press, London (1978).
Webster, M.A. & Mollon, J.D. (1994). The influence of contrast adaptation on color appearance. Vision Research 34, 1993–2020.Google Scholar
Wyszecki, G. & Stiles, W.S. (1982). Color Science: Concepts and Methods, Quantitative Data and Formulae. New York: Wiley.
Zeki, S. (1980). The representation of colour in the cerebral cortex. Nature 284, 412–418.Google Scholar