Amsel, Ben D.

Cree, George S.

eScholarship - University of California

UC MercedProceedings of the Annual Meeting of the Cognitive Science SocietyTitleA Dynamic Approach to Semantic Computation: Evidence from Event-Related Potentials and Connectionist Attractor NetworksPermalinkhttps://escholarship.org/uc/item/8n65g4hxJournalProceedings of the Annual Meeting of the Cognitive Science Society, 31(31)ISSN1069-7977AuthorsAmsel, Ben D.Cree, George S.Publication Date2009 Peer reviewedeScholarship.org Powered by the California Digital LibraryUniversity of CaliforniaA Dynamic Approach to Semantic Computation: Evidence fromEvent-Related Potentials and Connectionist Attractor NetworksBen D. AmselUniversity of Toronto ScarboroughGeorge S. CreeUniversity of Toronto ScarboroughAbstract: What factors determine speed of word meaning computation, and what is the time course of eachfactors influence? Implicated factors include correlations among, and distinctiveness of, semantic features, semanticrichness, and the structural organization of features into cortical regions (by modality and/or object domain). Event-related potentials and connectionist attractor networks are well suited for this problem because they provide near-continuous measurement during word meaning computation. We explored the dynamics of a recurrent attractornetwork trained with verbal feature-based representations of concepts and show how feature-based statistical structure(e.g., correlations among features) affects concept settling dynamically through time. We also analyzed ERPs during amental image-generation task using the identical items, incorporating measures of feature-based statistical structure,semantic richness (e.g., imageability), and modality-specific knowledge types (e.g., number of visual features). Usingpolynomial mixed-effects models, we demonstrate overlapping dynamic spatiotemporal effects of these measures, anddiscuss implications for theories of knowledge representation.2034

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A Dynamic Approach to Semantic Computation: Evidence from Event-Related Potentials and Connectionist Attractor Networks

https://escholarship.org/uc/item/8n65g4hx

A Dynamic Approach to Semantic Computation: Evidence from Event-Related Potentials and Connectionist Attractor Networks

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