Feature Statistics Modulate the Activation of Meaning During Spoken Word Processing. (4th June 2015)

• Record Type: Journal Article
• Authors: Devereux, Barry J.; Taylor, Kirsten I.; Randall, Billi; Geertzen, Jeroen; Tyler, Lorraine K.
• Is Part Of: Cognitive science. Volume 40:Number 2(2016:Mar.)
• Page Start: 325
• Page End: 350
• Publication Date: 2015-06-04
• Subjects: Concepts -- Semantic features -- Spoken word processing -- Lexical decision -- Connectionist modeling -- Attractor networks -- Lexical semantics -- Conceptual structure; Cognition -- Periodicals; Psycholinguistics -- Periodicals; Artificial intelligence -- Periodicals; 153.05
• DOI: 10.1111/cogs.12234
• Languages: English
• ISSNs: 0364-0213

Abstract

Abstract: Understanding spoken words involves a rapid mapping from speech to conceptual representations. One distributed feature‐based conceptual account assumes that the statistical characteristics of concepts' features—the number of concepts they occur in ( distinctiveness / sharedness ) and likelihood of co‐occurrence ( correlational strength )—determine conceptual activation. To test these claims, we investigated the role of distinctiveness/sharedness and correlational strength in speech‐to‐meaning mapping, using a lexical decision task and computational simulations. Responses were faster for concepts with higher sharedness, suggesting that shared features are facilitatory in tasks like lexical decision that require access to them. Correlational strength facilitated responses for slower participants, suggesting a time‐sensitive co‐occurrence‐driven settling mechanism. The computational simulation showed similar effects, with early effects of shared features and later effects of correlational strength. These results support a general‐to‐specific account of conceptual processing, whereby early activation of shared features is followed by the gradual emergence of a specific target representation.