Literature DB >> 33169698

Both activation and deactivation of functional networks support increased sentence processing costs.

Yanyu Xiong1, Sharlene Newman2.   

Abstract

The research on the neural correlates underlying the language system has gradually moved away from the traditional Broca-Wernicke framework to a network perspective in the past 15 years. Language processing is found to be supported by the co-activation of both core and peripheral brain regions. However, the dynamic co-activation patterns of these brain regions serving different language functions remain to be fully revealed. The present functional magnetic resonance imaging (fMRI) study focused on sentence processing at different syntactic complexity levels to examine how the co-activation of different brain networks will be modulated by increased processing costs. Chinese relative clauses were used to probe the two dimensions of syntactic complexity: embeddedness (left-branching vs. center-embedded) and gap-filler dependency (subject-gap vs. object-gap) using the general linear model (GLM) approach, independent component analysis (ICA) and graph theoretical analysis. In contrast to localized activation revealed by the GLM approach, ICA identified more extensive networks both positively and negatively correlated with the task. We found that the posterior default mode network was anti-correlated to the gap-filler integration costs with increased deactivation for the left-branching object relative clauses compared to subject relative clauses, suggesting the involvement of this network in leveraging the cognitive resources based on the complexity level of the language task. Concurrent activation and deactivation of networks were found to be associated with the higher costs induced by center-embedding and its interaction with gap-filler integration. The graph theoretical analysis further unveiled that center-embeddedness imposed more attentional demand on the subject relative clause, as characterized by its higher degree and strength in the ventral attention network, and higher processing costs of syntactic reanalysis on the object relative clause, as characterized by increased intermodular connections of the language network with other networks. The results suggest that network activation and deactivation profiles are modulated by different dimensions of syntactic complexity to serve the higher demand of creating a coherent semantic representation.
Copyright © 2020 The Author(s). Published by Elsevier Inc. All rights reserved.

Keywords:  Center-embedding; Chinese relative clause; Deactivation; Functional network; Gap-filler integration

Year:  2020        PMID: 33169698     DOI: 10.1016/j.neuroimage.2020.117475

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  2 in total

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Authors:  Ingo Hertrich; Susanne Dietrich; Corinna Blum; Hermann Ackermann
Journal:  Front Hum Neurosci       Date:  2021-05-17       Impact factor: 3.169

2.  NetDI: Methodology Elucidating the Role of Power and Dynamical Brain Network Features That Underpin Word Production.

Authors:  Sudha Yellapantula; Kiefer Forseth; Nitin Tandon; Behnaam Aazhang
Journal:  eNeuro       Date:  2021-02-09
  2 in total

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