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Peer-reviewedCC BYeLife

Comprehensive characterization of human color discrimination thresholds

  • Fangfang Hong1
  • Ruby Bouhassira1
  • Jason K. Chow2
  • Craig A. Sanders2
  • Michael Shvartsman3
  • Phillip Guan2
  • Alex H. Williams4,5
  • David H. Brainard1
5 affiliations
  1. 1Department of Psychology, University of Pennsylvania
  2. 2Reality Lab Research, Meta
  3. 3FAIR, Meta
  4. 4Center for Computational Neuroscience, Flatiron Institute
  5. 5Center for Neural Science, New York University
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Abstract

Color discrimination thresholds—the smallest detectable color differences—provide a benchmark for models of color vision, enable quantitative evaluation of eye diseases, and inform the design of display technologies. Despite their importance, a comprehensive characterization of these thresholds has long been considered intractable due to the psychophysical curse of dimensionality. Here, we address this challenge using a novel semiparametric Wishart process psychophysical model (WPPM), which leverages the feature that the internal noise limiting color discrimination varies smoothly across stimulus space. The model was fit to data collected with a nonparametric adaptive trial-placement procedure, enabling efficient stimulus selection. Together, through the combination of adaptive trial placement and post hoc WPPM fitting, we achieved a comprehensive characterization of color discrimination in the isoluminant plane with only ∼6000 trials per participant ( N = 8). Once fit, the WPPM allows readouts of discrimination performance for any stimulus pair. We validated these readouts against 25 probe psychometric functions, measured with an additional 6000 trials per participant held out from model fitting. In conclusion, our study provides a foundational dataset for color vision, and our approach generalizes beyond color to any domain in which the internal noise limiting performance varies smoothly across stimulus space, offering a powerful and efficient method for comprehensively characterizing various perceptual discrimination thresholds.

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Cite

BibTeXRIS
BibTeX
@article{hong2026comprehensive,
  title = {{Comprehensive characterization of human color discrimination thresholds}},
  author = {Fangfang Hong and Ruby Bouhassira and Jason K. Chow and Craig A. Sanders and Michael Shvartsman and Phillip Guan and Alex H. Williams and David H. Brainard},
  journal = {eLife},
  year = {2026},
  month = jul,
  doi = {10.7554/elife.108943.3},
  url = {https://doi.org/10.7554/elife.108943.3},
  note = {CC BY},
}
RIS
TY  - JOUR
TI  - Comprehensive characterization of human color discrimination thresholds
AU  - Fangfang Hong
AU  - Ruby Bouhassira
AU  - Jason K. Chow
AU  - Craig A. Sanders
AU  - Michael Shvartsman
AU  - Phillip Guan
AU  - Alex H. Williams
AU  - David H. Brainard
PY  - 2026
DA  - 2026/07/31
JO  - eLife
DO  - 10.7554/elife.108943.3
UR  - https://doi.org/10.7554/elife.108943.3
AB  - Color discrimination thresholds—the smallest detectable color differences—provide a benchmark for models of color vision, enable quantitative evaluation of eye diseases, and inform the design of display technologies. Despite their importance, a comprehensive characterization of these thresholds has long been considered intractable due to the psychophysical curse of dimensionality. Here, we address this challenge using a novel semiparametric Wishart process psychophysical model (WPPM), which leverages the feature that the internal noise limiting color discrimination varies smoothly across stimulus space. The model was fit to data collected with a nonparametric adaptive trial-placement procedure, enabling efficient stimulus selection. Together, through the combination of adaptive trial placement and post hoc WPPM fitting, we achieved a comprehensive characterization of color discrimination in the isoluminant plane with only ∼6000 trials per participant ( N = 8). Once fit, the WPPM allows readouts of discrimination performance for any stimulus pair. We validated these readouts against 25 probe psychometric functions, measured with an additional 6000 trials per participant held out from model fitting. In conclusion, our study provides a foundational dataset for color vision, and our approach generalizes beyond color to any domain in which the internal noise limiting performance varies smoothly across stimulus space, offering a powerful and efficient method for comprehensively characterizing various perceptual discrimination thresholds.
SN  - 2050-084X
ER  -