The neural basis for the effects of color and contrast on perceived speed was examined using functional magnetic resonance imaging (fMRI). Responses to S cone (blue-yellow) and L + M cone (luminance) patterns were measured in area V1 and in the motion area MT+. The MT+ responses were quantitatively similar to perceptual speed judgments of color patterns but not to color detection measures. We also measured cortical motion responses in individuals lacking L and M cone function (S cone monochromats). The S cone monochromats have clear motion-responsive regions in the conventional MT+ position, and their contrast-response functions there have twice the responsivity of S cone contrast-response functions in normal controls. But, their responsivity is far lower than the normals' responsivity to luminance contrast. Thus, the powerful magnocellular input to MT+ is either weak or silent during photopic vision in S cone monochromats.
The relationship between the neural processing of color and motion information has been a contentious issue in visual neuroscience. We examined this relationship directly by measuring neural responses to isoluminant S cone signals in extrastriate area MT of the macaque monkey. S cone stimuli produced robust, direction-selective responses at most recording sites, indicating that color signals are present in MT. While these responses were unequivocal, S cone contrast sensitivity was, on average, 1.0-1.3 log units lower than luminance contrast sensitivity. The presence of S cone responses and the relative sensitivity of MT neurons to S cone and luminance signals agree with functional magnetic resonance imaging (fMRI) measurements in human MT+. The results are consistent with the hypothesis that color signals in MT influence behavior in speed judgment tasks.
We have measured how color appearance of square-wave bars varies with stimulus strength and spatial frequency. Observers adjusted the color of a uniform patch to match the color appearance of the bars in square-wave patterns. We used low-to-moderate square-wave patterns, from 1 to 8 cycles per degree (c/deg). The matches are not photoreceptor matches but rather are established at more central neural sites. The signals at the putative central sites obey several simple regularities. The cone contrast of the uniform patch is proportional to square-wave stimulus strength (color homogeneity) and additive with respect to the superposition of equal-frequency square waves containing different colors (color superposition). We use the asymmetric matches to derive, from first principles, three pattern-color-separable appearance pathways. The matches are explained by two spectrally opponent, spatially low-pass mechanisms and one spectrally positive, spatially bandpass mechanism. The spectral mechanisms that we derive are similar to luminance and opponent mechanisms that are derived with entirely different experimental methods.
We have studied how contrast threshold sensitivity depends jointly on pattern and color. We measured sensitivity to colored Gabor patches from 0.5 to 8 c/deg. At each spatial frequency, we measured in many different color directions. We analyze the sensitivity measurements using a series of nested models. We conclude that a model consisting of three pattern-color separable mechanisms predicts detection performance nearly as well as fitting psychometric functions independently. We derive the pattern and color sensitivities of the separable mechanisms from the experimental data. Two derived mechanisms are spatially lowpass and spectrally color-opponent. The third mechanism is spatially bandpass and spectrally broadband.
We evaluate how well three different parametric shapes, ellipsoids, rectangles, and parallelograms, serve as models of three-dimensional detection contours. We describe how the procedures for deriving the best-fitting shapes constrain inferences about the theoretical visual detection mechanisms. The ellipsoidal shape, commonly assumed by vector-length theories, is related to a class of visual mechanisms that are unique only up to orthogonal transformations. The rectangle shape is related to a unique set of visual mechanisms, but since the rectangle is not invariant with respect to linear transformations the estimated visual mechanisms are dependent on the stimulus coordinate frame. The parallelogram is related to a unique set of visual mechanisms and can be derived by methods that are independent of the stimulus coordinate frame. We evaluate how well these shapes approximate detection contours, using 2-deg test fields with a long (1-sec) Gaussian time course. Two statistical tests suggest that the parallelogram model is too strong. First, we find that the ellipsoid and rectangle shapes fit the data with the same precision as the variance in repeated threshold measurements. The parallelogram model, which has more free parameters, fits the data with more precision than the variance in repeated threshold measurements. Second, although the parallelogram model provides a slightly better fit of our data than the other two shapes, it does not serve as a better guide than the ellipsoidal model for interpolating from the measurements to thresholds in novel color directions.
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