A mid-level organization of the ventral stream

ABSTRACT Human object-selective cortex shows a large-scale organization characterized by the high-level properties of both animacy and object-size. To what extent are these neural responses explained by primitive perceptual features that distinguish animals from objects and big objects from small objects? To address this question, we used a texture synthesis algorithm to create a novel class of stimuli— texforms —which preserve some mid-level texture and form information from objects while rendering them unrecognizable. We found that unrecognizable texforms were sufficient to elicit the large-scale organizations of object-selective cortex along the entire ventral pathway. Further, the structure in the neural patterns elicited by texforms was well predicted by curvature features and by intermediate layers of a deep convolutional neural network, supporting the mid-level nature of the representations. These results provide clear evidence that a substantial portion of ventral stream organization can be accounted for by coarse texture and form information, without requiring explicit recognition of intact objects. SIGNIFICANCE STATEMENT While neural responses to object categories are remarkably systematic across human visual cortex, the nature of these responses been hotly debated for the past 20 years. In this paper, a new class of stimuli (“texforms”) is used to examine how mid-level features contribute to the large-scale organization of the ventral visual stream. Despite their relatively primitive visual appearance, these unrecognizable texforms elicited the entire large-scale organizations of the ventral stream by animacy and object size. This work demonstrates that much of ventral stream organization can be explained by relatively primitive mid-level features, without requiring explicit recognition of the objects themselves.