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Processing Multiple Visual Objects Is Limited by Overlap in Neural Channels

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2014-06-02

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Proceedings of the National Academy of Sciences
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Michael A. Cohen, Talia Konkle, Juliana Y. Rhee, Ken Nakayama, and George A. Alvarez. "Processing Multiple Visual Objects Is Limited by Overlap in Neural Channels." Proceedings of the National Academy of Sciences 111, no. 24 (2014): 8955-8960.

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Abstract

High-level visual categories (e.g., faces, bodies, scenes, and objects) have separable neural representations across the visual cortex. Here, we show that this division of neural resources affects the ability to simultaneously process multiple items. In a behavioral task, we found that performance was superior when items were drawn from different categories (e.g., two faces/two scenes) compared to when items were drawn from one category (e.g., four faces). The magnitude of this mixed-category benefit depended on which stimulus categories were paired together (e.g., faces and scenes showed a greater behavioral benefit than objects and scenes). Using functional neuroimaging (i.e., functional MRI), we showed that the size of the mixed-category benefit was predicted by the amount of separation between neural response patterns, particularly within occipitotemporal cortex. These results suggest that the ability to process multiple items at once is limited by the extent to which those items are represented by separate neural populations.

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working memory, capacity limitations, representational similarity, competition, visual cognition

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