Connecting concepts in the brain by mapping cortical representations of semantic relations

Yizhen Zhang, Kuan Han, Robert Worth and Zhongming Liu ()
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Yizhen Zhang: University of Michigan
Kuan Han: University of Michigan
Robert Worth: Indiana University–Purdue University
Zhongming Liu: University of Michigan

Nature Communications, 2020, vol. 11, issue 1, 1-13

Abstract: Abstract In the brain, the semantic system is thought to store concepts. However, little is known about how it connects different concepts and infers semantic relations. To address this question, we collected hours of functional magnetic resonance imaging data from human subjects listening to natural stories. We developed a predictive model of the voxel-wise response and further applied it to thousands of new words. Our results suggest that both semantic categories and relations are represented by spatially overlapping cortical patterns, instead of anatomically segregated regions. Semantic relations that reflect conceptual progression from concreteness to abstractness are represented by cortical patterns of activation in the default mode network and deactivation in the frontoparietal attention network. We conclude that the human brain uses distributed networks to encode not only concepts but also relationships between concepts. In particular, the default mode network plays a central role in semantic processing for abstraction of concepts.

Date: 2020
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DOI: 10.1038/s41467-020-15804-w

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