A hallmark of high-level visual cortex is its functional organization of neighboring areas that are selective for single categories, such as faces, bodies, and objects. However, visual scenes are typically composed of multiple categories. How does a category- selective cortex represent such complex stimuli? Previous studies have shown that the representation of multiple stimuli can be explained by a normalization mechanism. Here we propose that a normalization mechanism that operates in a cortical region composed of neighboring category-selective areas would generate a representation of multi-category stimuli that varies continuously across a category-selective cortex as a function of the magnitude of category selectivity for its components. By using fMRI, we can examine this correspondence between category selectivity and the representation of multi-category stimuli along a large, continuous region of cortex. To test these predictions, we used a linear model to fit the fMRI response of human participants (both sexes) to a multi-category stimulus (e.g., a whole person) based on the response to its component stimuli presented in isolation (e.g., a face or a body). Consistent with our predictions, the response of cortical areas in high-level visual cortex to multi-category stimuli varies in a continuous manner along a weighted mean line, as a function of the magnitude of its category selectivity. This was the case for both related (face 1 body) and unrelated (face1wardrobe) multi-category pairs. We conclude that the functional organization of neighboring category-selective areas may enable a dynamic and flexible representation of complex visual scenes that can be modulated by higher-level cognitive systems according to task demands.
- Category-selective visual cortex
- High-level vision
- Normalization model
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