Abstract
Achromatic color perception exhibits a well-known asymmetry in which luminance increments and decrements have different subjective magnitudes. This asymmetry influences the perception of simple laboratory stimuli, real-world stimuli, and visual illusions, and it has important implications for color models in neuroscience and technology. Here, the magnitudes and spatial properties of this asymmetry are modeled by a neural theory of lightness computation in which ON- and OFF-center neurons are activated in the course of fixational eye movements (FEM). The ON and OFF cell activations encode local luminance ratios, raised to a power that differs for ON and OFF cells, consistent with physiological data from macaque LGN, and with the Naka-Rushton neural response function under non-saturating conditions. OFF cells respond linearly, while ON cells exhibit a compressive (power law) response. Both ON and OFF cells are assumed to possess gaussian spatial center and surround mechanisms that differ in size, as in the classical difference-of-gaussians (DOG) receptive field model, except that, here, the inhibitory mechanism is divisive rather than subtractive. Corollary discharge signals that encode the direction of fixational eye movements are combined with transient ON and OFF cell responses to produce local contrast signals that are sensitive to FEM direction. These local, directionally-sensitive, ON and OFF signals are log-transformed, then spatially integrated in the direction of the FEM by long-range cortical ON and OFF networks, whose outputs are combined to produce a unitary achromatic color signal. The achromatic color signal is normalized to achieve highest lightness anchoring, resulting in a 2D map of perceived reflectance that models the achromatic color percept. The model is demonstrated through computer simulations to account for psychophysical data on dynamic range compression in the Staircase Gelb Illusion, lightness/darkness asymmetries in simultaneous contrast, edge integration in lightness, perceptual filling-in, the Chevreul illusion, and perceptual fading of stabilized images.