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date: 04 July 2020

Abstract and Keywords

Semantic memory is composed of one’s accumulated world knowledge. This includes one’s stored factual information about the real-world objects and animals, which enables one to recognize and interact with the things in one’s environment. How is this semantic information organized, and where is it stored in the brain? Newly developed functional neuroimaging (fMRI) methods have provided exciting and innovative approaches to studying these questions. In particular, several recent fMRI investigations have examined the neural bases of semantic knowledge using similarity-based approaches. In similarity models, data from direct (i.e., neural) and indirect (i.e., subjective, psychological) measurements are interpreted as proximity data that provide information about the relationships among object concepts in an abstract, high-dimensional space. Concepts are encoded as points in this conceptual space, such that the semantic relatedness between two concepts is determined by their distance from one another. Using this approach, neuroimaging studies have offered compelling insights to several open-ended questions about how object concepts are represented in the brain. This chapter briefly describes how similarity spaces are computed from both behavioral data and spatially distributed fMRI activity patterns. Then, it reviews empirical reports that relate observed neural similarity spaces to various models of semantic similarity. The chapter examines how these methods have both shaped and informed our current understanding of the neural representation of conceptual information about real-world objects.

Keywords: semantic memory, fMRI, MVPA, concept, abstract representation, neuroimaging, representational similarity

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