From cones to color vision: a neurobiological model that explains the unique hues.

The irreducible unique hues-red, green, blue, and yellow-remain one of the great mysteries of vision science. Attempts to create a physiologically parsimonious model that can predict the spectral locations of the unique hues all rely on at least one post hoc adjustment to produce appropriate loci for unique green and unique red, and struggle to explain the non-linearity of the Blue/Yellow system. We propose a neurobiological color vision model that overcomes these challenges by using physiological cone ratios, cone-opponent normalization to equal-energy white, and a simple adaptation mechanism to produce color-opponent mechanisms that accurately predict the spectral locations and variability of the unique hues.

Potential value of color vision aids for varying degrees of color vision deficiency.

Red-green color vision deficiency (CVD) is the most common single locus genetic disorder in humans, affecting approximately 8% of males and 0.4% of females [G. H. M. Waaler, Acta Ophthalmol.5, 309 (2009)10.1111/j.1755-3768.1927.tb01016.x]; however, only about 1/4 of CVD individuals are dichromats who rely on only two cone types for color vision. The remaining 3/4 are anomalous trichromats whose CVD is milder, being based on three cone types, and who still perform remarkably well on many color-based tasks. To illustrate this, we have developed an algorithm that computes the relative loss of color discrimination in red-green CVD individuals with varying degrees of deficiency and accurately simulates their color experience for color normal observers. The resulting simulation illustrates the large gap in color discrimination between dichromats and even the most severe anomalous trichromats, showing that, relative to dichromats, the majority of anomalous trichromats can function without aids for color vision deficiency.

How We See Black and White: The Role of Midget Ganglion Cells.

According to classical opponent color theory, hue sensations are mediated by spectrally opponent neurons that are excited by some wavelengths of light and inhibited by others, while black-and-white sensations are mediated by spectrally non-opponent neurons that respond with the same sign to all wavelengths. However, careful consideration of the morphology and physiology of spectrally opponent L vs. M midget retinal ganglion cells (RGCs) in the primate retina indicates that they are ideally suited to mediate black-and-white sensations and poorly suited to mediate color. Here we present a computational model that demonstrates how the cortex could use unsupervised learning to efficiently separate the signals from L vs. M midget RGCs into distinct signals for black and white based only correlation of activity over time. The model also reveals why it is unlikely that these same ganglion cells could simultaneously mediate our perception of red and green, and shows how, in theory, a separate small population of midget RGCs with input from S, M, and L cones would be ideally suited to mediating hue perception.