Literature DB >> 28025051

Variations in normal color vision. VI. Factors underlying individual differences in hue scaling and their implications for models of color appearance.

Kara J Emery1, Vicki J Volbrecht2, David H Peterzell3, Michael A Webster4.   

Abstract

Observers with normal color vision vary widely in their judgments of color appearance, such as the specific spectral stimuli they perceive as pure or unique hues. We examined the basis of these individual differences by using factor analysis to examine the variations in hue-scaling functions from both new and previously published data. Observers reported the perceived proportion of red, green, blue or yellow in chromatic stimuli sampling angles at fixed intervals within the LM and S cone-opponent plane. These proportions were converted to hue angles in a perceptual-opponent space defined by red vs. green and blue vs. yellow axes. Factors were then extracted from the correlation matrix using PCA and Varimax rotation. These analyses revealed that inter-observer differences depend on seven or more narrowly-tuned factors. Moreover, although the task required observers to decompose the stimuli into four primary colors, there was no evidence for factors corresponding to these four primaries, or for opponent relationships between primaries. Perceptions of "redness" in orange, red, and purple, for instance, involved separate factors rather than one shared process for red. This pattern was compared to factor analyses of Monte Carlo simulations of the individual differences in scaling predicted by variations in standard opponent mechanisms, such as their spectral tuning or relative sensitivity. The observed factor pattern is inconsistent with these models and thus with conventional accounts of color appearance based on the Hering primaries. Instead, our analysis points to a perceptual representation of color in terms of multiple mechanisms or decision rules that each influence the perception of only a relatively narrow range of hues, potentially consistent with a population code for color suggested by cortical physiology.
Copyright © 2016 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Color; Color appearance; Color opponency; Factor analysis; Individual differences

Mesh:

Year:  2017        PMID: 28025051      PMCID: PMC5495633          DOI: 10.1016/j.visres.2016.12.006

Source DB:  PubMed          Journal:  Vision Res        ISSN: 0042-6989            Impact factor:   1.886


  76 in total

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Authors:  D H Peterzell; D Y Teller
Journal:  Vision Res       Date:  2000       Impact factor: 1.886

2.  Some quantitative aspects of an opponent-colors theory. III. Changes in brightness, saturation, and hue with chromatic adaptation.

Authors:  D JAMESON; L M HURVICH
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Authors:  Gokhan Malkoc; Paul Kay; Michael A Webster
Journal:  J Opt Soc Am A Opt Image Sci Vis       Date:  2005-10       Impact factor: 2.129

4.  No difference in variability of unique hue selections and binary hue selections.

Authors:  J M Bosten; A J Lawrance-Owen
Journal:  J Opt Soc Am A Opt Image Sci Vis       Date:  2014-04-01       Impact factor: 2.129

5.  Empirical evidence for unique hues?

Authors:  J M Bosten; A E Boehm
Journal:  J Opt Soc Am A Opt Image Sci Vis       Date:  2014-04-01       Impact factor: 2.129

6.  Factors underlying individual differences in the color matches of normal observers.

Authors:  M A Webster; D I MacLeod
Journal:  J Opt Soc Am A       Date:  1988-10       Impact factor: 2.129

7.  A multi-stage color model.

Authors:  R L De Valois; K K De Valois
Journal:  Vision Res       Date:  1993-05       Impact factor: 1.886

Review 8.  Color in the cortex: single- and double-opponent cells.

Authors:  Robert Shapley; Michael J Hawken
Journal:  Vision Res       Date:  2011-02-17       Impact factor: 1.886

9.  Long-term renormalization of chromatic mechanisms following cataract surgery.

Authors:  Peter B Delahunt; Michael A Webster; Lei Ma; John S Werner
Journal:  Vis Neurosci       Date:  2004 May-Jun       Impact factor: 3.241

10.  Individual Colorimetric Observer Model.

Authors:  Yuta Asano; Mark D Fairchild; Laurent Blondé
Journal:  PLoS One       Date:  2016-02-10       Impact factor: 3.240

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  13 in total

1.  Variations in normal color vision. VII. Relationships between color naming and hue scaling.

Authors:  Kara J Emery; Vicki J Volbrecht; David H Peterzell; Michael A Webster
Journal:  Vision Res       Date:  2017-01-05       Impact factor: 1.886

2.  The Verriest Lecture: Adventures in blue and yellow.

Authors:  Michael A Webster
Journal:  J Opt Soc Am A Opt Image Sci Vis       Date:  2020-04-01       Impact factor: 2.129

3.  Comparison of two methods of hue scaling.

Authors:  Courtney N Matera; Kara J Emery; Vicki J Volbrecht; Kavita Vemuri; Paul Kay; Michael A Webster
Journal:  J Opt Soc Am A Opt Image Sci Vis       Date:  2020-04-01       Impact factor: 2.129

4.  Steady-State Visual Evoked Potentials Elicited from Early Visual Cortex Reflect Both Perceptual Color Space and Cone-Opponent Mechanisms.

Authors:  Sae Kaneko; Ichiro Kuriki; Søren K Andersen
Journal:  Cereb Cortex Commun       Date:  2020-09-01

5.  The spectral identity of foveal cones is preserved in hue perception.

Authors:  Brian P Schmidt; Alexandra E Boehm; Katharina G Foote; Austin Roorda
Journal:  J Vis       Date:  2018-10-01       Impact factor: 2.240

6.  Color perception and compensation in color deficiencies assessed with hue scaling.

Authors:  Kara J Emery; Mohana Kuppuswamy Parthasarathy; Daniel S Joyce; Michael A Webster
Journal:  Vision Res       Date:  2021-02-23       Impact factor: 1.984

7.  Individual Variability in Simultaneous Contrast for Color and Brightness: Small Sample Factor Analyses Reveal Separate Induction Processes for Short and Long Flashes.

Authors:  Sae Kaneko; Ikuya Murakami; Ichiro Kuriki; David H Peterzell
Journal:  Iperception       Date:  2018-09-23

8.  Ensemble coding of color and luminance contrast.

Authors:  Siddhart Rajendran; John Maule; Anna Franklin; Michael A Webster
Journal:  Atten Percept Psychophys       Date:  2020-10-06       Impact factor: 2.199

9.  How do visual skills relate to action video game performance?

Authors:  Aline F Cretenoud; Arthur Barakat; Alain Milliet; Oh-Hyeon Choung; Marco Bertamini; Christophe Constantin; Michael H Herzog
Journal:  J Vis       Date:  2021-07-06       Impact factor: 2.240

10.  When illusions merge.

Authors:  Aline F Cretenoud; Gregory Francis; Michael H Herzog
Journal:  J Vis       Date:  2020-08-03       Impact factor: 2.240

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