Coding mechanisms & contextual interactions in color vision
نویسنده
چکیده
The perceived color of an object depends not only on the spectral composition of the light reflected from its surface, but also on the visual context such as illumination and surrounding colors. Such contextual modulations are thought to underlie perceptual phenomena such as color constancy. A possible neuronal basis may be lateral interactions that alter the activity of color selective neurons in the early visual cortex. Here, we present a model of cortical color processing that predicts color shifts induced by chromatic surrounds. The model assumes that stimulus hue is encoded by a population of neurons with Gaussian tuning curves and color preferences distributed in color space. This is based on empirical findings of distributed color preferences in primary visual cortex. The influence of the surround hue on the stimulus was implemented via inhibition of the units’ activation in the population code. The strength of this inhibition depended on the distance between the stimulus and the surround hue in colorspace. This contextual modulation by the surround hue introduced a bias in the population response that, when decoded, revealed systematic shifts in the encoded stimulus hue. The strength and shape of the resulting simulated induction curve strongly depended on the modulation parameters, such as width and amplitude. The results indicate that important computations in color vision that lead to perceptual hue shifts can be realized using simple neural mechanisms when color is represented by a distributed code.
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