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语言网络功能连接模式揭示语义和语音处理的神经关联。

Neural correlates of semantic and phonological processing revealed by functional connectivity patterns in the language network.

机构信息

Beijing Key Laboratory of Applied Experimental Psychology & National Demonstration Center for Experimental Psychology Education (Beijing Normal University), Faculty of Psychology, Beijing Normal University, Beijing 100875, China.

State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China.

出版信息

Neuropsychologia. 2018 Dec;121:47-57. doi: 10.1016/j.neuropsychologia.2018.10.027. Epub 2018 Nov 1.

Abstract

Semantics and phonology are fundamental components of language. Neuroimaging studies have identified a language network (LN) that is distributed through multiple regions and exhibits preferential responses to semantic and phonological information. However, it is unclear how these regions work collaboratively to support the processing of these components. In the present study, we first defined the LN as voxels that responded more to sentences than to strings of Chinese pseudo-characters. We subsequently used a voxel-based global brain connectivity method based on resting-state functional connectivity (FC) to characterize the neural correlates of semantic and phonological processing. We specifically correlated the within-network connectivity (WNC) of each voxel in the LN with the participants' scores on the semantic and phonological components extracted from a battery of reading tests via principal component analysis. We found that individuals with stronger WNC in the left posterior superior temporal gyrus (lpSTG) and anterior superior temporal gyrus (laSTG) were better at semantic and phonological processing, respectively. Furthermore, the FC of the lpSTG with the laSTG and bilateral fusiform gyrus mainly contributed to semantic processing, whereas the FC of the laSTG with the left posterior middle temporal gyrus and inferior frontal gyrus largely contributed to phonological processing. Importantly, the semantic and phonological subnetworks overlapped in the laSTG, the WNC of which correlated with the participants' performances during semantic-phonological interactions. Our study revealed the hub and subnetwork for semantic and phonological processing, respectively, and highlighted the role of the laSTG in semantic-phonological interactions.

摘要

语义学和音系学是语言的基本组成部分。神经影像学研究已经确定了一个语言网络(LN),它分布在多个区域,并对语义和音系信息表现出优先反应。然而,目前尚不清楚这些区域如何协同工作,以支持这些成分的处理。在本研究中,我们首先将 LN 定义为对句子的反应比对中文伪字串反应更强烈的体素。随后,我们使用基于静息态功能连接(FC)的基于体素的全局脑连接方法来描述语义和音系处理的神经相关性。我们特别将 LN 中每个体素的网络内连接(WNC)与通过主成分分析从阅读测试电池中提取的语义和音系成分的参与者得分相关联。我们发现,左侧后上颞回(lpSTG)和前上颞回(laSTG)中 WNC 较强的个体在语义和音系处理方面分别表现更好。此外,lpSTG 与 laSTG 和双侧梭状回之间的 FC 主要有助于语义处理,而 laSTG 与左侧后颞中回和下额回之间的 FC 主要有助于音系处理。重要的是,语义和音系子网在 laSTG 中重叠,其 WNC 与参与者在语义-音系相互作用期间的表现相关。我们的研究分别揭示了语义和音系处理的枢纽和子网,并强调了 laSTG 在语义-音系相互作用中的作用。

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