The distribution of category and location information across object-selective regions in human visual cortex

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Abstract
Since Ungerleider and Mishkin [Underleider LG, Mishkin M (1982) Two cortical visual systems. Analysis of Visual Behavior, eds Ingle MA, Goodale MI, Masfield RJW (MIT Press, Cambridge, MA), pp 549-586] proposed separate visual pathways for processing object shape and location, steady progress has been made in characterizing the organization of the two kinds of information in extrastriate visual cortex in humans. However, to date, there has been no broad-based survey of category and location information across all major functionally defined object-selective regions. In this study, we used an fMRI region-of-interest (ROI) approach to identify eight regions characterized by their strong selectivity for particular object categories (faces, scenes, bodies, and objects). Participants viewed four types of stimuli (faces, scenes, bodies, and cars) appearing in each of three different spatial locations (above, below, or at fixation). Analyses based on the mean response and voxelwise patterns of response in each ROI reveal location information in almost all of the known object-selective regions. Furthermore, category and location information can be read out independently of one another such that most regions contain both position-invariant category information and category-invariant position information. Finally, we find substantially more location information in ROIs on the lateral than those on the ventral surface of the brain, even though these regions have equal amounts of category information. Although the presence of both location and category information in most object-selective regions argues against a strict physical separation of processing streams for object shape and location, the ability to extract position-invariant category information and category-invariant position information from the same neural population indicates that form and location information nonetheless remain functionally independent.