Distinct fronto-temporal substrates of distributional and taxonomic similarity among words: evidence from RSA of BOLD signals
A class of semantic theories defines concepts in terms of statistical distributions of lexical items, basing meaning on vectors of word co-occurrence frequencies. A different approach emphasizes abstract hierarchical taxonomic relationships among concepts. However, the functional relevance of these...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2021-01-01
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| Series: | NeuroImage |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1053811920308934 |
| _version_ | 1818727602441945088 |
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| author | Francesca Carota Hamed Nili Friedemann Pulvermüller Nikolaus Kriegeskorte |
| author_facet | Francesca Carota Hamed Nili Friedemann Pulvermüller Nikolaus Kriegeskorte |
| author_sort | Francesca Carota |
| collection | DOAJ |
| description | A class of semantic theories defines concepts in terms of statistical distributions of lexical items, basing meaning on vectors of word co-occurrence frequencies. A different approach emphasizes abstract hierarchical taxonomic relationships among concepts. However, the functional relevance of these different accounts and how they capture information-encoding of lexical meaning in the brain still remains elusive.We investigated to what extent distributional and taxonomic models explained word-elicited neural responses using cross-validated representational similarity analysis (RSA) of functional magnetic resonance imaging (fMRI) and model comparisons.Our findings show that the brain encodes both types of semantic information, but in distinct cortical regions. Posterior middle temporal regions reflected lexical-semantic similarity based on hierarchical taxonomies, in coherence with the action-relatedness of specific semantic word categories. In contrast, distributional semantics best predicted the representational patterns in left inferior frontal gyrus (LIFG, BA 47). Both representations coexisted in the angular gyrus supporting semantic binding and integration. These results reveal that neuronal networks with distinct cortical distributions across higher-order association cortex encode different representational properties of word meanings. Taxonomy may shape long-term lexical-semantic representations in memory consistently with the sensorimotor details of semantic categories, whilst distributional knowledge in the LIFG (BA 47) may enable semantic combinatorics in the context of language use.Our approach helps to elucidate the nature of semantic representations essential for understanding human language. |
| first_indexed | 2024-12-17T22:16:42Z |
| format | Article |
| id | doaj.art-422085efbddb48b090813c34054a7846 |
| institution | Directory Open Access Journal |
| issn | 1095-9572 |
| language | English |
| last_indexed | 2024-12-17T22:16:42Z |
| publishDate | 2021-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | NeuroImage |
| spelling | doaj.art-422085efbddb48b090813c34054a78462022-12-21T21:30:35ZengElsevierNeuroImage1095-95722021-01-01224117408Distinct fronto-temporal substrates of distributional and taxonomic similarity among words: evidence from RSA of BOLD signalsFrancesca Carota0Hamed Nili1Friedemann Pulvermüller2Nikolaus Kriegeskorte3Max-Planck-Institute for Psycholinguistics, Wundtlaan 1, Nijmegen, the Netherlands; Donders Centre for Cognitive NeuroImaging, Radboud University, Kapittelweg 29, 6525 EN Nijmegen, the Netherlands; MRC Cognition and Brain Sciences Unit, 15 Chaucer Road, Cambridge CB2 7EF, United Kingdom; Berlin School of Mind and Brain, Humboldt Universität zu Berlin, Berlin, Germany; Brain Language Laboratory, Department of Philosophy and Humanities, WE4, Freie Universität Berlin, Berlin, Germany; Corresponding author at: Max-Planck-Institute for Psycholinguistics, Wundtlaan 1, Nijmegen, the Netherlands & Donders Centre for Cognitive NeuroImaging, RU, Kapittelweg 29, 6525 EN Nijmegen, the Netherlands.MRC Cognition and Brain Sciences Unit, 15 Chaucer Road, Cambridge CB2 7EF, United Kingdom; Department of Experimental Psychology, University of Oxford, Tinbergen Building, 9 South Parks Road, Oxford OX1 3UD, United KingdomMRC Cognition and Brain Sciences Unit, 15 Chaucer Road, Cambridge CB2 7EF, United Kingdom; Berlin School of Mind and Brain, Humboldt Universität zu Berlin, Berlin, Germany; Brain Language Laboratory, Department of Philosophy and Humanities, WE4, Freie Universität Berlin, Berlin, GermanyMRC Cognition and Brain Sciences Unit, 15 Chaucer Road, Cambridge CB2 7EF, United Kingdom; Cognitive Imaging at the Zuckerman Mind Brain Behavior Institute, Columbia University, Jerome L. Greene Science Center, 3227 Broadway, L3-064, 9834 New York, NY 10027, United StatesA class of semantic theories defines concepts in terms of statistical distributions of lexical items, basing meaning on vectors of word co-occurrence frequencies. A different approach emphasizes abstract hierarchical taxonomic relationships among concepts. However, the functional relevance of these different accounts and how they capture information-encoding of lexical meaning in the brain still remains elusive.We investigated to what extent distributional and taxonomic models explained word-elicited neural responses using cross-validated representational similarity analysis (RSA) of functional magnetic resonance imaging (fMRI) and model comparisons.Our findings show that the brain encodes both types of semantic information, but in distinct cortical regions. Posterior middle temporal regions reflected lexical-semantic similarity based on hierarchical taxonomies, in coherence with the action-relatedness of specific semantic word categories. In contrast, distributional semantics best predicted the representational patterns in left inferior frontal gyrus (LIFG, BA 47). Both representations coexisted in the angular gyrus supporting semantic binding and integration. These results reveal that neuronal networks with distinct cortical distributions across higher-order association cortex encode different representational properties of word meanings. Taxonomy may shape long-term lexical-semantic representations in memory consistently with the sensorimotor details of semantic categories, whilst distributional knowledge in the LIFG (BA 47) may enable semantic combinatorics in the context of language use.Our approach helps to elucidate the nature of semantic representations essential for understanding human language.http://www.sciencedirect.com/science/article/pii/S1053811920308934Conceptual taxonomiesCo-occurrence statisticsfMRIRepresentational similarity searchlightsLanguage comprehension |
| spellingShingle | Francesca Carota Hamed Nili Friedemann Pulvermüller Nikolaus Kriegeskorte Distinct fronto-temporal substrates of distributional and taxonomic similarity among words: evidence from RSA of BOLD signals NeuroImage Conceptual taxonomies Co-occurrence statistics fMRI Representational similarity searchlights Language comprehension |
| title | Distinct fronto-temporal substrates of distributional and taxonomic similarity among words: evidence from RSA of BOLD signals |
| title_full | Distinct fronto-temporal substrates of distributional and taxonomic similarity among words: evidence from RSA of BOLD signals |
| title_fullStr | Distinct fronto-temporal substrates of distributional and taxonomic similarity among words: evidence from RSA of BOLD signals |
| title_full_unstemmed | Distinct fronto-temporal substrates of distributional and taxonomic similarity among words: evidence from RSA of BOLD signals |
| title_short | Distinct fronto-temporal substrates of distributional and taxonomic similarity among words: evidence from RSA of BOLD signals |
| title_sort | distinct fronto temporal substrates of distributional and taxonomic similarity among words evidence from rsa of bold signals |
| topic | Conceptual taxonomies Co-occurrence statistics fMRI Representational similarity searchlights Language comprehension |
| url | http://www.sciencedirect.com/science/article/pii/S1053811920308934 |
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