Abstract
An important goal for vision science is to develop quantitative models of the representation of visual signals at post-receptoral sites. To this end, we develop the quadratic color model (QCM) and examine its ability to account for the BOLD fMRI response in human V1 to spatially uniform, temporal chromatic modulations that systematically vary in chromatic direction and contrast. We find that the QCM explains the same, cross-validated variance as a conventional general linear model, with far fewer free parameters. The QCM generalizes to allow prediction of V1 responses to a large range of modulations. We replicate the results for each subject and find good agreement across both replications and subjects. We find that within the LM cone contrast plane, V1 is most sensitive to L-M contrast modulations and least sensitive to L+M contrast modulations. Within V1, we observe little to no change in chromatic sensitivity as a function of eccentricity.
Highlights
The initial stage of human color vision is well characterized
To evaluate the quadratic color model (QCM), three subjects underwent functional magnetic resonance imaging (fMRI) scanning while viewing stimuli consisting of spatially uniform (0 cycles per degree) chromatic temporal modulations, presented using a block design
We develop a quantitative model of the visual cortex response to chromatic stimuli in the LM contrast plane, the quadratic color model (QCM), and examine its ability to fit V1 blood oxygen level dependent (BOLD) fMRI responses to spatially uniform chromatic stimuli
Summary
The initial stage of human color vision is well characterized. The encoding of light by the three classes of cone photoreceptors (L, M, and S) is described quantitatively by a set of spectral sensitivity functions, one for each class. Knowledge of the spectral sensitivities allows for the calculation of cone excitations from the spectral radiance of the light entering the eye (Brainard and Stockman, 2010). This quantitative characterization supports the analysis of the information available to subsequent processing stages (Geisler, 1989; Cottaris et al, 2019), supports the precise specification of visual stimuli (Brainard, 1996; Brainard et al, 2002), and enables color reproduction technologies (Wandell and Silverstein, 2003; Hunt, 2004). The second stage of color vision combines the signals from the cones to create three post-receptoral mechanisms. While the outlines of this second stage seem well established, the precise links between retinal physiology and visual perception remain qualitative and subject to debate (Stockman and Brainard, 2010; Shevell and Martin, 2017)
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