Vision is limited by the measurements taken by the cone photoreceptors. To provide useful perceptual representations, the brain must go beyond the measurements and make inferences about the scene being viewed. This article considers the first stages of spatiochromatic vision. We show how spatial and chromatic information become intertwined by the optics of the eye and because of the structure of the retinal cone mosaic, and we consider the consequent implications for perception. Because there is at most one cone at each retinal location, the standard treatment of human trichromacy does not apply at fine spatial scales. Rather, trichromacy results from a perceptual inference based on measurements from cones of different classes at different locations. Our treatment emphasizes linking physics, biology, and computation with the goal of providing a framework for a larger understanding of how the brain interprets photoreceptor excitations to see objects and their properties.


Article metrics loading...

Loading full text...

Full text loading...


Literature Cited

  1. Adelson EH, Bergen JR. 1991. The plenoptic function and the elements of early vision. Computational Models of Visual Processing MS Landy, JA Movshon 3–20 Cambridge, MA: MIT Press [Google Scholar]
  2. Ahumada AJJ. 1991. Learning receptor positions. Computational Models of Visual Processing JA Movshon, MS Landy 23–34 Cambridge, MA: MIT Press [Google Scholar]
  3. Atick JJ. 1992. Could information theory provide an ecological theory of sensory processing. Network 3:213–51 [Google Scholar]
  4. Atick JJ, Li ZP, Redlich AN. 1992. Understanding retinal color coding from first principles. Neural Comput. 4:559–72 [Google Scholar]
  5. Autrusseau F, Thibos L, Shevell SK. 2011. Chromatic and wavefront aberrations: L-, M- and S-cone stimulation with typical and extreme retinal image quality. Vis. Res. 51:2282–94 [Google Scholar]
  6. Balasubramanian V, Berry 2nd MJ. 2002. A test of metabolically efficient coding in the retina. Network 13:531–52 [Google Scholar]
  7. Balasubramanian V, Kimber D, Berry MJ 2nd. 2001. Metabolically efficient information processing. Neural Comput. 13:799–815 [Google Scholar]
  8. Barlow HB. 1956. Retinal noise and absolute threshold. J. Opt. Soc. Am. 46:634–39 [Google Scholar]
  9. Benson NC, Manning JR, Brainard DH. 2014. Unsupervised learning of cone spectral classes from natural images. PLOS Comput. Biol. 10:e1003652 [Google Scholar]
  10. Bowmaker JK. 1977. The visual pigments, oil droplets, and spectral sensitivity of the pigeon. Vis. Res. 17:1129–38 [Google Scholar]
  11. Bowmaker JK. 1991. The evolution of vertebrate visual pigments and photoreceptors. Evolution of the Eye and Visual System JR Cronly-Dillon, RL Gregory 63–81 Boca Raton, FL: CRC [Google Scholar]
  12. Bowmaker JK, Kunz YW. 1987. Ultraviolet receptors, tetrachromatic colour vision and retinal mosaics in the brown trout (Salmo trutta): age-dependent changes. Vis. Res. 27:2101–8 [Google Scholar]
  13. Brainard DH. 1994. Bayesian method for reconstructing color images from trichromatic samples. Proc. IS&T 47th Annu. Meet.375–79 Springfield, VA: IS&T [Google Scholar]
  14. Brainard DH. 2009. Bayesian approaches to color vision. The Cognitive Neurosciences MS Gazzaniga 395–408 Cambridge, MA: MIT Press, 4th ed.. [Google Scholar]
  15. Brainard DH, Calderone J, Nugent AK, Jacobs GH. 1999. Flicker ERG responses to stimuli parametrically modulated in color space. Investig. Ophthalmol. Vis. Sci. 40:2840–47 [Google Scholar]
  16. Brainard DH, Freeman WT. 1997. Bayesian color constancy. J. Opt. Soc. Am. A 14:1393–411 [Google Scholar]
  17. Brainard DH, Roorda A, Yamauchi Y, Calderone JB, Metha A. et al. 2000. Functional consequences of the relative numbers of L and M cones. J. Opt. Soc. Am. A 17:607–14 [Google Scholar]
  18. Brainard DH, Stockman A. 2010. Colorimetry. The Optical Society of America Handbook of Optics 3 Vision and Vision Optics M Bass, C DeCusatis, J Enoch, V Lakshminarayanan, G Li 10.1–10.56 New York: McGraw-Hill, 3rd ed.. [Google Scholar]
  19. Brainard DH, Williams DR. 1992. Spatial reconstruction of signals from short-wavelength cones. Vis. Res. 33:105–16 [Google Scholar]
  20. Brainard DH, Williams DR, Hofer H. 2008. Trichromatic reconstruction from the interleaved cone mosaic: Bayesian model and the color appearance of small spots. J. Vis. 8:515 [Google Scholar]
  21. Brewster D. 1832. On the undulations excited in the retina by the action of luminous points and lines. Philos. Mag. 13169–74 [Google Scholar]
  22. Buchsbaum G, Gottschalk A. 1983. Trichromacy, opponent colours coding and optimum colour information transmission in the retina. Proc. R. Soc. Lond. B 220:89–113 [Google Scholar]
  23. Burge J, Geisler WS. 2011. Optimal defocus estimation in individual natural images. PNAS 108:16849–54 [Google Scholar]
  24. Burton GJ, Moorehead IR. 1987. Color and spatial structure in natural images. Appl. Opt. 26:157–70 [Google Scholar]
  25. Buzas P, Blessing EM, Szmajda BA, Martin PR. 2006. Specificity of M and L cone inputs to receptive fields in the parvocellular pathway: random wiring with functional bias. J. Neurosci. 26:11148–61 [Google Scholar]
  26. Calkins DJ, Schein SJ, Tsukamoto Y, Sterling P. 1994. M and L cones in macaque fovea connect to midget ganglion cells by different numbers of excitatory synapses. Nature 371:70–72 [Google Scholar]
  27. Carroll J, McMahon C, Neitz M, Neitz J. 2000. Flicker-photometric electroretinogram estimates of L:M cone photoreceptor ratio in men with photopigment spectra derived from genetics. J. Opt. Soc. Am. A 17:499–509 [Google Scholar]
  28. Carroll J, Neitz J, Neitz M. 2002. Estimates of L:M cone ratio from ERG flicker photometry and genetics. J. Vis. 2:81 [Google Scholar]
  29. Carroll J, Yoon G, Williams DR. 2009. The cone photoreceptor mosaic in normal and defective color vision. The Cognitive Neurosciences MS Gazzaniga 383–94 Cambridge, MA: MIT Press, 4th ed.. [Google Scholar]
  30. Chakrabarti A, Zickler T. 2011. Statistics of real-world hyperspectral images. Proc. IEEE Comput. Soc. Conf. Comput. Vision Pattern Recognit. 2011193–200 New York: IEEE [Google Scholar]
  31. Challa NK, McKeefry D, Parry NRA, Kremers J, Murray IJ, Panorgias A. 2010. L- and M-cone input to 12Hz and 30Hz flicker ERGs across the human retina. Ophthalmic Physiol. Opt. 30:503–10 [Google Scholar]
  32. Charman N. 2010. Optics of the eye. The Optical Society of America Handbook of Optics 3 Vision and Vision Optics M Bass, C DeCusatis, J Enoch, V Lakshminarayanan, G Li et al.1.1–1.65 New York: McGraw-Hill, 3rd ed.. [Google Scholar]
  33. Chittka L, Menzel R. 1992. The evolutionary adaptation of flower colours and the insect pollinators' colour vision. J. Comp. Physiol. A 171:171–81 [Google Scholar]
  34. CIE 2006. Fundamental chromaticity diagram with physiological axes—Part 1 Tech. Rep. 170-1, Central Bur. Comm. Int. Éclair., Vienna [Google Scholar]
  35. Coletta NJ, Williams DR. 1987. Psychophysical estimate of extrafoveal cone spacing. J. Opt. Soc. Am. A 4:1503–13 [Google Scholar]
  36. Cronin TW, Marshall NJ. 1989. A retina with at least ten types of spectral photoreceptors in a mantis shrimp. Nature 339:137–40 [Google Scholar]
  37. Cummings ME. 2004. Modelling divergence in luminance and chromatic detection performance across measured divergence in surfperch (Embiotocidae) habitats. Vis. Res. 44:1127–45 [Google Scholar]
  38. Curcio CA, Allen KA, Sloan KR, Lerea CL, Hurley JB. et al. 1991. Distribution and morphology of human cone photoreceptors stained with anti-blue opsin. J. Comp. Neurol. 312:610–24 [Google Scholar]
  39. Curcio CA, Sloan KR. 1992. Packing geometry of human cone photoreceptors: variation with eccentricity and evidence for local anisotropy. Vis. Neurosci. 9:169–80 [Google Scholar]
  40. Curcio CA, Sloan KR, Kalina RE, Hendrickson AE. 1990. Human photoreceptor topography. J. Comp. Neurol. 292:497–523 [Google Scholar]
  41. Dacey DM. 2000. Parallel pathways for spectral coding in primate retina. Annu. Rev. Neurosci. 23:743–75 [Google Scholar]
  42. Dacey DM, Diller LC, Verweij J, Williams DR. 2000. Physiology of L- and M-cone inputs to H1 horizontal cells in the primate retina. J. Opt. Soc. Am. A 17:589–96 [Google Scholar]
  43. Dacey DM, Packer OS. 2003. Colour coding in the primate retina: diverse cell types and cone-specific circuitry. Curr. Opin. Neurobiol. 13:421–27 [Google Scholar]
  44. Danilova MV, Chan CH, Mollon JD. 2013. Can spatial resolution reveal individual differences in the L:M cone ratio?. Vis. Res. 78:26–38 [Google Scholar]
  45. De Vries H. 1948. The heredity of the relative numbers of red and green receptors in the human eye. Genetica 24:199–212 [Google Scholar]
  46. Dobkins KR, Thiele A, Albright TD. 2000. Comparisons of red-green equiluminance points in humans and macaques: evidence for different L:M cone ratios between species. J. Opt. Soc. Am. A 17:545–56 [Google Scholar]
  47. Dulai KS, von Dornum M, Mollon JD, Hunt DM. 1999. The evolution of trichromatic color vision by opsin duplication in New World and Old World primates. Genome Res. 9:629–38 [Google Scholar]
  48. Enoch JM, Lakshminarayanan V. 2010. The problem of correction for the Stiles-Crawford effect of the first kind in radiometry and photometry, a solution. The Optical Society of America Handbook of Optics 3 Vision and Vision Optics M Bass, C DeCusatis, J Enoch, V Lakshminarayanan, G Li, et al. , pp. 9.1–9.18. New York: McGraw-Hill, 3rd. ed. [Google Scholar]
  49. Estévez O, Spekreijse H. 1982. The “silent substitution” method in visual research. Vis. Res. 22:681–91 [Google Scholar]
  50. Farrell JE, Jiang H, Winawer J, Brainard DH, Wandell BA. 2014. Modeling visible differences: the computational observer model. Proc. 2014 Soc. Inf. Disp. (SID) Int. Symp. Campbell, CA: Soc. Inf. Disp. [Google Scholar]
  51. Field DJ. 1987. Relations between the statistics of natural images and the response properties of cortical cells. J. Opt. Soc. Am. A 4:2379–94 [Google Scholar]
  52. Field GD, Gauthier JL, Sher A, Greschner M, Machado TA. et al. 2010. Functional connectivity in the retina at the resolution of photoreceptors. Nature 467:673–77 [Google Scholar]
  53. Foley JD, van Dam A, Feiner SK, Hughes JF. 1990. Computer Graphics: Principles and Practice Reading, MA: Addison-Wesley [Google Scholar]
  54. Garrigan P, Ratliff CP, Klein JM, Sterling P, Brainard DH, Balasubramanian V. 2010. Design of a trichromatic cone array. PLOS Comput. Biol. 6:e1000677 [Google Scholar]
  55. Geisler WS. 1989. Sequential ideal-observer analysis of visual discriminations. Psychol. Rev. 96:267–314 [Google Scholar]
  56. Geisler WS. 2011. Contributions of ideal observer theory to vision research. Vis. Res. 51:771–81 [Google Scholar]
  57. Hagstrom SA, Neitz J, Neitz M. 1998. Variations in cone populations for red-green color vision examined by analysis of mRNA. NeuroReport 9:1963–67 [Google Scholar]
  58. Hansen T, Pracejus L, Gegenfurtner KR. 2009. Color perception in the intermediate periphery of the visual field. J. Vis. 9:426 [Google Scholar]
  59. Harmening WM, Tuten WS, Bruce KS, Holz FG, Roorda A, Sincich LC. 2013. Visual function testing at the single cone level with a multi-wavelength adaptive optics SLO. Ophthalmologica 230:13–14 [Google Scholar]
  60. Harmening WM, Tuten WS, Roorda A, Sincich LC. 2014. Mapping the perceptual grain of the human retina. J. Neurosci. 34:5667–77 [Google Scholar]
  61. Hart NS. 2001. Variations in cone photoreceptor abundance and the visual ecology of birds. J. Comp. Physiol. A 187:685–97 [Google Scholar]
  62. Hofer H, Singer B, Williams DR. 2005a. Different sensations from cones with the same photopigment. J. Vis. 5:55 [Google Scholar]
  63. Hofer HJ, Carroll J, Neitz J, Neitz M, Williams DR. 2005b. Organization of the human trichromatic cone mosaic. J. Neurosci. 25:9669–79 [Google Scholar]
  64. Hofer HJ, Williams DR. 2014. Color vision and the retinal mosaic. The New Visual Neurosciences LM Chalupa, JS Werner 469–83 Cambridge, MA: MIT Press [Google Scholar]
  65. IEC 1999. sRGB Standard, International Electrotechnical Commission Standard 61966-2-1.
  66. Jacobs GH. 2009. Evolution of colour vision in mammals. Philos. Trans. R. Soc. Lond. B 364:2957–67 [Google Scholar]
  67. Jacobs GH, Deegan JF II. 1999. Uniformity of colour vision in Old World monkeys. Proc. R. Soc. Lond. B 266:2023–28 [Google Scholar]
  68. Jacobs GH, Deegan JF II, Neitz J, Corgnale MA, Neitz M. 1993. Photopigments and color vision in the nocturnal monkey, Aotus. Vis. Res. 33:1773–83 [Google Scholar]
  69. Jacobs GH, Nathans J. 2009. The evolution of primate color vision. Sci. Am. 300:56–63 [Google Scholar]
  70. Jacobs GH, Neitz J. 1985. Spectral positioning of mammalian cone pigments. J. Opt. Soc. Am. A 2:23 [Google Scholar]
  71. Jacobs GH, Neitz J. 1993. Electrophysiological estimates of individual variation in L/M cone ratio. Colour Vision Deficiencies XI B Drum 107–12 Dordrecht: Kluwer [Google Scholar]
  72. Jacobs GH, Neitz M, Deegan JF, Neitz J. 1996. Trichromatic colour vision in New World monkeys. Nature 382:156–58 [Google Scholar]
  73. Jacobs GH, Rowe MP. 2004. Evolution of vertebrate color vision. Clin. Exp. Optom. 87:206–16 [Google Scholar]
  74. Jacobs GH, Williams GA, Cahill H, Nathans J. 2007. Emergence of novel color vision in mice engineered to express a human cone photopigment. Science 315:1723–25 [Google Scholar]
  75. Jagle H, de Luca E, Serey L, Bach M, Sharpe LT. 2006. Visual acuity and X-linked color blindness. Graefe's Arch. Clin. Exp. Ophthalmol. 244:447–53 [Google Scholar]
  76. Jusuf PR, Martin PR, Grunert U. 2006. Random wiring in the midget pathway of primate retina. J. Neurosci. 26:3908–17 [Google Scholar]
  77. Kaiser PK, Boynton RM. 1996. Human Color Vision Washington, DC: Opt. Soc. Am. 2nd ed. [Google Scholar]
  78. Knill DC, Richards W. 1996. Perception as Bayesian Inference Cambridge, UK: Cambridge Univ. Press [Google Scholar]
  79. Knoblauch K, Neitz J, Neitz M. 2006. An urn model of the development of L/M cone ratios in human and macaque retinas. Vis. Neurosci. 23:387–94 [Google Scholar]
  80. Koch K, McLean J, Berry M, Sterling P, Balasubramanian V, Freed MA. 2004. Efficiency of information transmission by retinal ganglion cells. Curr. Biol. 14:1523–30 [Google Scholar]
  81. Koenderink J. 2010. Color for the Sciences Cambridge, MA: MIT Press [Google Scholar]
  82. Kolb H, Dekorver L. 1991. Midget ganglion cells of the parafovea of the human retina: a study by electron microscopy and serial reconstructions. J. Comp. Neurol. 303:617–36 [Google Scholar]
  83. Kram YA, Mantey S, Corbo JC. 2010. Avian cone photoreceptors tile the retina as five independent, self-organizing mosaics. PLOS ONE 5:e8992 [Google Scholar]
  84. Kremers J, Scholl HPN, Knau H, Berendschot TTJM, Sharpe LT. 2000. L/M cone ratios in human trichromats assessed by psychophysics, electroretinography and retinal densitometry. J. Opt. Soc. Am. A 17:517–26 [Google Scholar]
  85. Kuchenbecker JA, Sahay M, Tait DM, Neitz M, Neitz J. 2008. Topography of the long- to middle-wavelength sensitive cone ratio in the human retina assessed with a wide-field color mutlifocal electroretinogram. Vis. Neurosci. 25:301–06 [Google Scholar]
  86. Land M, Osorio D. 2003. Colour vision: colouring the dark. Curr. Biol. 13:R83–R85 [Google Scholar]
  87. Larson GW, Shakespeare R. 1998. Rendering with Radiance: The Art and Science of Lighting Visualization San Francisco: Morgan Kaufman [Google Scholar]
  88. Laughlin SB. 2001. Energy as a constraint on the coding and processing of sensory information. Curr. Opin. Neurobiol. 11:475–80 [Google Scholar]
  89. Laughlin SB, Sejnowski TJ. 2003. Communication in neuronal networks. Science 301:1870–74 [Google Scholar]
  90. Lee BB, Kremers J, Yeh T. 1998. Receptive fields of primate retinal ganglion cells studied with a novel technique. Vis. Neurosci. 15:161–75 [Google Scholar]
  91. Lennie P, Haake PW, Williams DR. 1991. The design of chromatically opponent receptive fields. Computational Models of Visual Processing MS Landy, JA Movshon 71–82 Cambridge, MA: MIT Press [Google Scholar]
  92. Levin A, Durand F, Freeman WT. 2008. Understanding Camera Trade-Offs through a Bayesian Analysis of Light Field Projections Cambridge, MA: MIT Press [Google Scholar]
  93. Lewis A, Zhaoping L. 2006. Are cone sensitivities determined by natural color statistics?. J. Vis. 6:38 [Google Scholar]
  94. Lindbloom-Brown Z, Tait LJ, Horwitz GD. 2014. Spectral sensitivity differences between rhesus monkeys and humans: implications for neurophysiology. J. Neurophysiol. 112:3164–72 [Google Scholar]
  95. Makous W. 2007. Comment on “Emergence of novel color vision in mice engineered to express a human cone photopigment. Science 318:196 [Google Scholar]
  96. Maloney LT, Ahumada AJJ. 1989. Learning by assertion: two methods for calibrating a linear visual system. Neural Comput. 1:392–401 [Google Scholar]
  97. Mancuso K, Hauswirth WW, Li QH, Connor TB, Kuchenbecker JA. et al. 2009. Gene therapy for red-green colour blindness in adult primates. Nature 461:784–87 [Google Scholar]
  98. Manning JR, Brainard DH. 2009. Optimal design of photoreceptor mosaics: why we do not see color at night. Vis. Neurosci. 26:5–19 [Google Scholar]
  99. Marc RE, Sperling HG. 1976. Chromatic organization of primate cones. Science 196:454–56 [Google Scholar]
  100. Marimont DH, Wandell BA. 1994. Matching color images: the effects of axial chromatic aberration. J. Opt. Soc. Am. A 11:3113–22 [Google Scholar]
  101. Marshall J, Oberwinkler J. 1999. The colorful world of the mantis shrimp. Nature 401:873–74 [Google Scholar]
  102. Miyahara E, Pokorny J, Smith VC, Baron R, Baron E. 1998. Color vision in two observers with highly biased LWS/MWS cone ratios. Vis. Res. 38:601–12 [Google Scholar]
  103. Mollon JD, Bowmaker JK. 1992. The spatial arrangement of cones in the primate fovea. Nature 360:677–79 [Google Scholar]
  104. Morgan MJ, Adam A, Mollon JD. 1992. Dichromats detect colour-camouflaged objects that are not detected by trichromats. Proc. R. Soc. Lond. B 248:291–95 [Google Scholar]
  105. Mullen KT. 1985. The contrast sensitivity of human colour vision to red-green and blue-yellow gratings. J. Physiol. 359:381–400 [Google Scholar]
  106. Mullen KT, Kingdom FAA. 2002. Differential distributions of red-green and blue-yellow cone opponency across the visual field. Vis. Neurosci. 19:109–18 [Google Scholar]
  107. Mullen KT, Sakurai M, Chu W. 2005. Does L/M cone opponency disappear in human periphery?. Perception 34:951–59 [Google Scholar]
  108. Nathans J. 1999. The evolution and physiology of human color vision: insights from molecular genetic studies of visual pigments. Neuron 24:299–312 [Google Scholar]
  109. Neitz J, Carroll J, Yamauchi Y, Neitz M, Williams DR. 2002. Color perception is mediated by a plastic neural mechanism that is adjustable in adults. Neuron 35:783–92 [Google Scholar]
  110. Neitz J, Neitz M. 2011. The genetics of normal and defective color vision. Vis. Res. 51:633–51 [Google Scholar]
  111. Osorio D, Ruderman DL, Cronin TW. 1998. Estimation of errors in luminance signals encoded by primate retina resulting from sampling of natural images with red and green cones. J. Opt. Soc. Am. A 15:16–22 [Google Scholar]
  112. Osorio D, Vorobyev M. 1996. Colour vision as an adaptation to frugivory in primates. Proc. R. Soc. Lond. B 263:593–99 [Google Scholar]
  113. Østerberg GA. 1935. Topography of the layer of rods and cones in the human retina. Acta Ophthalmol. 6:1–102 [Google Scholar]
  114. Pharr M, Humphreys G. 2010. Physically Based Rendering: From Theory to Implementation San Francisco: Morgan Kaufmann [Google Scholar]
  115. Pokorny J, Smith VC, Wesner MF. 1991. Variability in cone populations and implications. From Pigments to Perception A Valberg, BB Lee 23–34 New York: Plenum [Google Scholar]
  116. Pratt WK. 1978. Digital Image Processing New York: Wiley [Google Scholar]
  117. Regan BC, Julliot C, Simmen B, Vienot F, Charles-Dominique P, Mollon JD. 2001. Fruits, foliage and the evolution of primate color vision. Philos. Trans. R. Soc. Lond. B 356:229–83 [Google Scholar]
  118. Roorda A, Williams DR. 1999. The arrangement of the three cone classes in the living human eye. Nature 397:520–22 [Google Scholar]
  119. Ruderman DL, Cronin TW, Chiao CC. 1998. Statistics of cone responses to natural images: implications for visual coding. J. Opt. Soc. Am. A 15:2036–45 [Google Scholar]
  120. Rushton WAH, Baker HD. 1964. Red/green sensitivity in normal vision. Vis. Res. 4:75–85 [Google Scholar]
  121. Sabesan R, Schmidt B, Tuten WS, Boehm A, Roorda A. 2015. Functional organization of color in the trichromatic cone mosaic Presented at ARVO Annu. Meet., Denver, CO [Google Scholar]
  122. Schmidt BP, Neitz M, Neitz J. 2014. Neurobiological hypothesis of color appearance and hue perception. J. Opt. Soc. Am. A 31:A195–207 [Google Scholar]
  123. Scholes JH. 1975. Colour receptors and their synaptic connexions in the retina of a Cyprinid fish. Philos. Trans. R. Soc. Lond. B 270:61–118 [Google Scholar]
  124. Sekiguchi N, Williams DR, Brainard DH. 1993. Aberration-free measurements of the visibility of isoluminant gratings. J. Opt. Soc. Am. A 10:2105–17 [Google Scholar]
  125. Sharpe LT, de Luca E, Hansen T, Jagle H, Gegenfurtner KR. 2006. Advantages and disadvantages of human dichromacy. J. Vis. 6:3213–23 [Google Scholar]
  126. Simoncelli EP. 2005. Statistical modeling of photographic images. Handbook of Image and Video Processing A Bovik 431–41 New York: Academic [Google Scholar]
  127. Smallwood PM, Wang Y, Nathhans J. 2002. Role of a locus control region in the mutually exculsive expression of human red and green cone pigment genes. PNAS 99:1006–11 [Google Scholar]
  128. Solomon SG, Lee BB, White AJ, Rüttiger L, Martin PR. 2005. Chromatic organization of ganglion cell receptive fields in the peripheral retina. J. Neurosci. 25:4527–39 [Google Scholar]
  129. Spitschan M, Aguirre GK, Brainard DH. 2015. Selective stimulation of penumbral cones reveals perception in the shadow of retinal blood vessels. PLOS ONE 10:e0124328 [Google Scholar]
  130. Stiles WS, Crawford BH. 1933. The luminous efficiency of rays entering the eye pupil at different points. Proc. R. Soc. Lond. B 112:428–50 [Google Scholar]
  131. Stockman A, Sharpe LT. 2000. Spectral sensitivities of the middle- and long-wavelength sensitive cones derived from measurements in observers of known genotype. Vis. Res. 40:1711–37 [Google Scholar]
  132. Sumner P, Mollon JD. 2000a. Catarrhine photopigments are optimized for detecting targets against a foliage background. J. Exp. Biol. 203:1963–86 [Google Scholar]
  133. Sumner P, Mollon JD. 2000b. Chromaticity as a signal of ripeness in fruits taken by primates. J. Exp. Biol. 203:1987–2000 [Google Scholar]
  134. Thibos LN. 1987. Calculation of the influence of lateral chromatic aberration on image quality across the visual field. J. Opt. Soc. Am. A 4:1673–80 [Google Scholar]
  135. Thibos LN, Ye M, Zhang X, Bradley A. 1992. The chromatic eye: a new reduced-eye model of ocular chromatic aberration in humans. Appl. Opt. 31:3594–600 [Google Scholar]
  136. Tkačik G, Garrigan P, Ratliff C, Milcinski G, Klein JM. et al. 2011. Natural images from the birthplace of the human eye. PLOS ONE 6:e20409 [Google Scholar]
  137. Tuten WS, Tiruveedhula P, Roorda A. 2012. Adaptive optics scanning laser ophthalmoscope-based microperimetry. Optom. Vis. Sci. 89:563–74 [Google Scholar]
  138. Vakrou C, Whitaker D, McGraw PV, McKeefry D. 2005. Functional evidence for cone-specific connectivity in the human retina. J. Physiol. 566:93–102 [Google Scholar]
  139. van Hateren JH. 1993. Spatial, temporal and spectral pre-processing for colour vision. Proc. Biol. Sci. 251:61–68 [Google Scholar]
  140. Vienot F, Brettel H. 2014. The Verriest lecture: visual properties of metameric blacks beyond cone vision. J. Opt. Soc. Am. A 31:A38–46 [Google Scholar]
  141. von Helmholtz H. 1896. Handbuch der Physiologischen Optik Hamburg: Leopold Voss [Google Scholar]
  142. Wachtler T, Doi E, Lee T-W, Sejnowski TJ. 2007. Cone selectivity derived from the responses of the retinal cone mosaic to natural scenes. J. Vis. 7:86 [Google Scholar]
  143. Wandell BA. 1995. Foundations of Vision Sunderland, MA: Sinauer [Google Scholar]
  144. Williams DR. 1985. Aliasing in human foveal vision. Vis. Res. 25:195–205 [Google Scholar]
  145. Williams DR, Collier RJ. 1983. Consequences of spatial sampling by a human photoreceptor mosaic. Science 221:385–87 [Google Scholar]
  146. Williams DR, Collier RJ, Thompson BJ. 1983. Spatial resolution of the short-wavelength mechanism. Colour Vision JD Mollon, LT Sharpe 487–503 London: Academic [Google Scholar]
  147. Williams DR, MacLeod DIA, Hayhoe MM. 1981a. Foveal tritanopia. Vis. Res. 19:1341–56 [Google Scholar]
  148. Williams DR, MacLeod DIA, Hayhoe MM. 1981b. Punctate sensitivity of the blue-sensitive mechanism. Vis. Res. 19:1357–75 [Google Scholar]
  149. Williams DR, Sekiguchi N, Brainard DH. 1993. Color, contrast sensitivity, and the cone mosaic. PNAS 90:9770–77 [Google Scholar]
  150. Williams DR, Sekiguchi N, Haake W, Brainard DH, Packer O. 1991. The cost of trichromacy for spatial vision. From Pigments to Perception, ed. A Valberg, BB Lee 11–22 New York: Plenum [Google Scholar]
  151. Wyszecki G, Stiles WS. 1982. Color Science: Concepts and Methods, Quantitative Data and Formulae New York: Wiley [Google Scholar]
  152. Yamauchi Y, Williams DR, Brainard DH, Roorda A, Carroll J. et al. 2002. What determines unique yellow, L/M cone ratio or visual experience?. Proc. SPIE 4421:275 [Google Scholar]
  153. Yellott JI Jr. 1982. Spectral analysis of spatial sampling by photoreceptors: Topological disorder prevents aliasing. Vis. Res. 22:1205–10 [Google Scholar]
  154. Yellott JI Jr. 1983. Spectral consequences of photoreceptor sampling in the rhesus retina. Science 221:382–85 [Google Scholar]
  155. Yellott JI Jr, Wandell BA, Cornsweet TN. 1984. The beginnings of visual perception: the retinal image and its initial encoding. Handbook of Physiology: The Nervous System I Darien-Smith 257–316 New York: Easton [Google Scholar]

Data & Media loading...

  • Article Type: Review Article
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error