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In defense of abstract conceptual representations

Overview of attention for article published in Psychonomic Bulletin & Review, June 2016
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Title
In defense of abstract conceptual representations
Published in
Psychonomic Bulletin & Review, June 2016
DOI 10.3758/s13423-015-0909-1
Pubmed ID
Authors

Jeffrey R. Binder

Abstract

An extensive program of research in the past 2 decades has focused on the role of modal sensory, motor, and affective brain systems in storing and retrieving concept knowledge. This focus has led in some circles to an underestimation of the need for more abstract, supramodal conceptual representations in semantic cognition. Evidence for supramodal processing comes from neuroimaging work documenting a large, well-defined cortical network that responds to meaningful stimuli regardless of modal content. The nodes in this network correspond to high-level "convergence zones" that receive broadly crossmodal input and presumably process crossmodal conjunctions. It is proposed that highly conjunctive representations are needed for several critical functions, including capturing conceptual similarity structure, enabling thematic associative relationships independent of conceptual similarity, and providing efficient "chunking" of concept representations for a range of higher order tasks that require concepts to be configured as situations. These hypothesized functions account for a wide range of neuroimaging results showing modulation of the supramodal convergence zone network by associative strength, lexicality, familiarity, imageability, frequency, and semantic compositionality. The evidence supports a hierarchical model of knowledge representation in which modal systems provide a mechanism for concept acquisition and serve to ground individual concepts in external reality, whereas broadly conjunctive, supramodal representations play an equally important role in concept association and situation knowledge.

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Geographical breakdown

Country Count As %
United Kingdom 1 <1%
Netherlands 1 <1%
United States 1 <1%
Unknown 195 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 45 23%
Researcher 32 16%
Student > Master 24 12%
Student > Doctoral Student 12 6%
Student > Bachelor 9 5%
Other 34 17%
Unknown 42 21%
Readers by discipline Count As %
Psychology 59 30%
Neuroscience 29 15%
Linguistics 17 9%
Computer Science 10 5%
Social Sciences 7 4%
Other 19 10%
Unknown 57 29%