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Syntactic Computations in the Language Network: Characterizing Dynamic Network Properties Using Representational Similarity Analysis

The core human capacity of syntactic analysis involves a left hemisphere network involving left inferior frontal gyrus (LIFG) and posterior middle temporal gyrus (LMTG) and the anatomical connections between them. Here we use magnetoencephalography (MEG) to determine the spatio-temporal properties o...

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Autores principales: Tyler, Lorraine K., Cheung, Teresa P. L., Devereux, Barry J., Clarke, Alex
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3656357/
https://www.ncbi.nlm.nih.gov/pubmed/23730293
http://dx.doi.org/10.3389/fpsyg.2013.00271
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author Tyler, Lorraine K.
Cheung, Teresa P. L.
Devereux, Barry J.
Clarke, Alex
author_facet Tyler, Lorraine K.
Cheung, Teresa P. L.
Devereux, Barry J.
Clarke, Alex
author_sort Tyler, Lorraine K.
collection PubMed
description The core human capacity of syntactic analysis involves a left hemisphere network involving left inferior frontal gyrus (LIFG) and posterior middle temporal gyrus (LMTG) and the anatomical connections between them. Here we use magnetoencephalography (MEG) to determine the spatio-temporal properties of syntactic computations in this network. Listeners heard spoken sentences containing a local syntactic ambiguity (e.g., “… landing planes …”), at the offset of which they heard a disambiguating verb and decided whether it was an acceptable/unacceptable continuation of the sentence. We charted the time-course of processing and resolving syntactic ambiguity by measuring MEG responses from the onset of each word in the ambiguous phrase and the disambiguating word. We used representational similarity analysis (RSA) to characterize syntactic information represented in the LIFG and left posterior middle temporal gyrus (LpMTG) over time and to investigate their relationship to each other. Testing a variety of lexico-syntactic and ambiguity models against the MEG data, our results suggest early lexico-syntactic responses in the LpMTG and later effects of ambiguity in the LIFG, pointing to a clear differentiation in the functional roles of these two regions. Our results suggest the LpMTG represents and transmits lexical information to the LIFG, which responds to and resolves the ambiguity.
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spelling pubmed-36563572013-05-31 Syntactic Computations in the Language Network: Characterizing Dynamic Network Properties Using Representational Similarity Analysis Tyler, Lorraine K. Cheung, Teresa P. L. Devereux, Barry J. Clarke, Alex Front Psychol Psychology The core human capacity of syntactic analysis involves a left hemisphere network involving left inferior frontal gyrus (LIFG) and posterior middle temporal gyrus (LMTG) and the anatomical connections between them. Here we use magnetoencephalography (MEG) to determine the spatio-temporal properties of syntactic computations in this network. Listeners heard spoken sentences containing a local syntactic ambiguity (e.g., “… landing planes …”), at the offset of which they heard a disambiguating verb and decided whether it was an acceptable/unacceptable continuation of the sentence. We charted the time-course of processing and resolving syntactic ambiguity by measuring MEG responses from the onset of each word in the ambiguous phrase and the disambiguating word. We used representational similarity analysis (RSA) to characterize syntactic information represented in the LIFG and left posterior middle temporal gyrus (LpMTG) over time and to investigate their relationship to each other. Testing a variety of lexico-syntactic and ambiguity models against the MEG data, our results suggest early lexico-syntactic responses in the LpMTG and later effects of ambiguity in the LIFG, pointing to a clear differentiation in the functional roles of these two regions. Our results suggest the LpMTG represents and transmits lexical information to the LIFG, which responds to and resolves the ambiguity. Frontiers Media S.A. 2013-05-17 /pmc/articles/PMC3656357/ /pubmed/23730293 http://dx.doi.org/10.3389/fpsyg.2013.00271 Text en Copyright © 2013 Tyler, Cheung, Devereux and Clarke. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in other forums, provided the original authors and source are credited and subject to any copyright notices concerning any third-party graphics etc.
spellingShingle Psychology
Tyler, Lorraine K.
Cheung, Teresa P. L.
Devereux, Barry J.
Clarke, Alex
Syntactic Computations in the Language Network: Characterizing Dynamic Network Properties Using Representational Similarity Analysis
title Syntactic Computations in the Language Network: Characterizing Dynamic Network Properties Using Representational Similarity Analysis
title_full Syntactic Computations in the Language Network: Characterizing Dynamic Network Properties Using Representational Similarity Analysis
title_fullStr Syntactic Computations in the Language Network: Characterizing Dynamic Network Properties Using Representational Similarity Analysis
title_full_unstemmed Syntactic Computations in the Language Network: Characterizing Dynamic Network Properties Using Representational Similarity Analysis
title_short Syntactic Computations in the Language Network: Characterizing Dynamic Network Properties Using Representational Similarity Analysis
title_sort syntactic computations in the language network: characterizing dynamic network properties using representational similarity analysis
topic Psychology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3656357/
https://www.ncbi.nlm.nih.gov/pubmed/23730293
http://dx.doi.org/10.3389/fpsyg.2013.00271
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