L/m cone ratios in human trichromats assessed by psychophysics, electroretinography, and retinal densitometry

Jan Kremers, Hendrik P.N. Scholl, Holger Knau, Tos T.J.M. Berendschot, Tomoaki Usui, Lindsay T. Sharpe

Research output: Contribution to journalArticlepeer-review

100 Scopus citations


Estimates of the relative numbers of long-wavelength-sensitive (L) and middle-wavelength-sensitive (M) cones vary considerably among normal trichromats and depend significantly on the nature of the experimentalmethod employed. Here we estimate L/M cone ratios in a population of normal observers, using three psychophysical tasks—detection thresholds for cone-isolating stimuli at different temporal frequencies, heterochromatic flicker photometry, and cone contrast ratios at minimal flicker perception—as well as flicker electroretinography and retinal densitometry. The psychophysical tasks involving high temporal frequencies, specifically designed to tap into the luminance channel, provide average L/M cone ratios that significantly differfrom unity with large interindividual variation. In contrast, the psychophysical tasks involving low temporal frequencies, chosen to tap into the red-green chromatic channel, provide L/M cone ratios that are always close to unity. L/M cone ratios determined from electroretino graphic recordings or from retinal densitometry correlate with those determined fromthe high-temporal-frequency tasks. These findings suggest that thesensitivity of the luminance channel is directly related to the relative densities of the L and the M cones and that the red-green chromatic channel introduces a gain adjustment to compensate for differences in L and M cone signal strength.

Original languageEnglish (US)
Pages (from-to)517-526
Number of pages10
JournalJournal of the Optical Society of America A: Optics and Image Science, and Vision
Issue number3
StatePublished - Mar 2000
Externally publishedYes

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Atomic and Molecular Physics, and Optics
  • Computer Vision and Pattern Recognition


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