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  Distributed representations of behaviorally relevant object dimensions in the human visual system

Contier, O., Baker, C. I., & Hebart, M. N. (2023). Distributed representations of behaviorally relevant object dimensions in the human visual system. bioRxiv. doi:10.1101/2023.08.23.553812.

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Contier, Oliver1, Author           
Baker, C. I., Author
Hebart, Martin N.1, Author                 
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1Max Planck Research Group Vision and Computational Cognition, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_3158378              

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 Abstract: Object vision is commonly thought to involve a hierarchy of brain regions processing increasingly complex image features, with high-level visual cortex supporting object recognition and categorization. However, object vision supports diverse behavioral goals, suggesting basic limitations of this category-centric framework. To address these limitations, here we map a series of behaviorally-relevant dimensions derived from a large-scale analysis of human similarity judgments directly onto the brain. Our results reveal broadly-distributed representations of behaviorally-relevant information, demonstrating selectivity to a wide variety of novel dimensions while capturing known selectivities for visual features and categories. Behaviorally-relevant dimensions were superior to categories at predicting brain responses, yielding mixed selectivity in much of visual cortex and sparse selectivity in category-selective clusters. This framework reconciles seemingly disparate findings regarding regional specialization, explaining category selectivity as a special case of sparse response profiles among representational dimensions, and suggesting a behavior-centric view on visual processing in the human brain.

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Language(s): eng - English
 Dates: 2023-08-24
 Publication Status: Published online
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 Identifiers: DOI: 10.1101/2023.08.23.553812
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Title: bioRxiv
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