Functional divisions of the left anterior and posterior temporoparietal junction for phonological and semantic processing in Chinese character reading

IF 4.7 2区 医学 Q1 NEUROIMAGING
Aqian Li , Chuansheng Chen , Yuan Feng , Rui Hu , Xiaoxue Feng , Jingyu Yang , Xingying Lin , Leilei Mei
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引用次数: 0

Abstract

Previous studies have shown that the left temporoparietal junction (TPJ) plays a critical role in word reading. Nevertheless, there is still controversy surrounding the phonological and semantic functions of the left TPJ. The parietal unified connectivity-biased computation (PUCC) model posits that the function of the left TPJ depends on both the neurocomputation of this local area and its long-range connectivity. To clarify the specific roles of different TPJ subregions in phonological and semantic processing of Chinese characters, the present study used connectivity-based clustering to identify seven subdivisions within the left TPJ, and conducted comprehensive analyses including functional and structural connectivity, univariate and multivariate analyses (i.e., representational similarity analysis, RSA) on multimodal imaging data (task-state fMRI, resting-state fMRI, and diffusion-weighted imaging [DWI]). Functional and structural connectivity analyses revealed that the left anterior TPJ had stronger connections with the phonological network, while the left posterior TPJ had stronger connections with the semantic network. RSA revealed that the left anterior and posterior TPJ represented phonological and semantic information of Chinese characters, respectively. More importantly, the phonological and semantic representations of the left TPJ were respectively correlated with its functional connectivity to the phonological and semantic networks. Altogether, our results provide a more elaborate perspective on the functional dissociation of the left anterior and posterior TPJ in phonological and semantic processing of Chinese characters, and support the PUCC model.

Abstract Image

汉字阅读中左前、后颞顶叶连接对语音和语义加工的功能划分
以往的研究表明,左侧颞顶叶交界处(TPJ)在单词阅读中起着至关重要的作用。然而,关于左侧 TPJ 的语音和语义功能仍存在争议。顶叶统一连接-偏向计算(PUCC)模型认为,左侧 TPJ 的功能取决于该局部区域的神经计算及其长程连接。为了明确不同TPJ亚区在汉字语音和语义加工中的具体作用,本研究采用基于连接性的聚类方法确定了左侧TPJ的七个亚区,并对多模态成像数据(任务态fMRI、静息态fMRI和弥散加权成像[DWI])进行了包括功能和结构连接性、单变量和多变量分析(即表征相似性分析,RSA)在内的综合分析。功能和结构连接分析表明,左前TPJ与语音网络的连接更强,而左后TPJ与语义网络的连接更强。RSA显示,左前TPJ和左后TPJ分别代表汉字的语音和语义信息。更重要的是,左侧TPJ的语音和语义表征分别与其与语音和语义网络的功能连接相关。总之,我们的研究结果为左侧TPJ前部和后部在汉字语音和语义加工中的功能分离提供了一个更详细的视角,并支持了PUCC模型。
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来源期刊
NeuroImage
NeuroImage 医学-核医学
CiteScore
11.30
自引率
10.50%
发文量
809
审稿时长
63 days
期刊介绍: NeuroImage, a Journal of Brain Function provides a vehicle for communicating important advances in acquiring, analyzing, and modelling neuroimaging data and in applying these techniques to the study of structure-function and brain-behavior relationships. Though the emphasis is on the macroscopic level of human brain organization, meso-and microscopic neuroimaging across all species will be considered if informative for understanding the aforementioned relationships.
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