Color and form information can be decoded in every region of the human ventral visual hierarchy, and at every layer of many convolutional neural networks (CNNs) trained to recognize objects, but how does the coding strength of these features vary over processing? Here, we characterize for these features both their absolute coding strength—how strongly each feature is represented independent of the other feature—and their relative coding strength—how strongly each feature is encoded relative to the other, which could constrain how well a feature can be read out by downstream regions across variation in the other feature. To quantify relative coding strength, we define a measure called the form dominance index that compares the relative influence of color and form on the representational geometry at each processing stage. We analyze brain and CNN responses to stimuli varying based on color and either a simple form feature, orientation, or a more complex form feature, curvature. We find that while the brain and CNNs largely differ in how the absolute coding strength of color and form vary over processing, comparing them in terms of their relative emphasis of these features reveals a striking similarity: For both the brain and for CNNs trained for object recognition (but not for untrained CNNs), orientation information is increasingly de-emphasized, and curvature information is increasingly emphasized, relative to color information over processing, with corresponding processing stages showing largely similar values of the form dominance index.

Primate ventral and dorsal visual pathways both contain visual object representations. Dorsal regions receive more input from magnocellular system while ventral regions receive inputs from both magnocellular and parvocellular systems. Due to potential differences in the spatial sensitivites of manocellular and parvocellular systems, object representations in ventral and dorsal regions may differ in how they represent visual input from different spatial scales. To test this prediction, we asked observers to view blocks of images from six object categories, shown in full spectrum, high spatial frequency (SF), or low SF. We found robust object category decoding in all SF conditions as well as SF decoding in nearly all the early visual, ventral, and dorsal regions examined. Cross-SF decoding further revealed that object category representations in all regions exhibited substantial tolerance across the SF components. No difference between ventral and dorsal regions was found in their preference for the different SF components. Further comparisons revealed that, whereas differences in the SF component separated object category representations in early visual areas, such a separation was much smaller in downstream ventral and dorsal regions. In those regions, variations among the object categories played a more significant role in shaping the visual representational structures. Our findings show that ventral and dorsal regions are similar in how they represent visual input from different spatial scales and argue against a dissociation of these regions based on differential sensitivity to different SFs.