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Language and simulation in conceptual processing

Barsalou, Lawrence W, Santos, Ava, Simmons, W Kyle, Wilson, Christine D·2008·Symbols and EmbodimentDebates on meaning and cognition

Abstract

This chapter explains that multiple systems represent knowledge. It focuses on two resources of knowledge, believed to have strong empirical support — linguistic forms in the brain's language systems, and situated simulations in the brain's modal systems. Although this chapter focuses on two sources of knowledge, it does not exclude the possibility that other types are important as well. It argues that statistical representations play central roles throughout the brain, and that they underlie linguistic forms and situated simulations. It examines linguistic and modal approaches to the representation of knowledge. It proposes the language and situated simulation (LASS) theory as a preliminary framework for integrating these approaches. It then explores the evidence for the LASS theory, including evidence for dual code theory, Glaser's (1922) revision of dual code theory or the lexical hypothesis, evidence from the laboratories.

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Crossref · 10.1093/acprof:oso/9780199217274.003.0013

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Metadata

Authors
Barsalou, L. W., Santos, A., Simmons, W. K., & Wilson, C. D.
Venue
Symbols and EmbodimentDebates on meaning and cognition
Published
2008-10-09
Pages
245-284
OpenAlex
W47780887
Cited by
696
References
76
FWCI
46.22
Type
book chapter
Language
en
Open access
closed

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CoChat. (2026). Citation check: Language and simulation in conceptual processing. https://app.cochat.ai/papers/10.1093/acprof:oso/9780199217274.003.0013
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Barsalou, L. W., Santos, A., Simmons, W. K., & Wilson, C. D. (2008). Language and simulation in conceptual processing. Symbols and EmbodimentDebates on meaning and cognition. https://doi.org/10.1093/acprof%3Aoso/9780199217274.003.0013

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.