Abstract
Visual patterns have widely varying contrasts and elicit local signals of varying reliability, ranging from noisy to relatively noise-free. One way to deal efficiently with the variable visual input is to employ flexible neural mechanisms that adapt to changing conditions. We investigated whether the spatial properties of motion mechanisms change with stimulus contrast and found that the optimal size for perceiving motion decreases with increasing contrast. These data were well-described by a model in which spatial summation increases with decreasing contrast.