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解析语言连接组的功能属性:关键子网、灵活性和可变性。

Unraveling the functional attributes of the language connectome: crucial subnetworks, flexibility and variability.

机构信息

CNRS, LPNC, Université Grenoble Alpes, BSHM, Université Savoie Mont Blanc, UMR 5105, Cedex, Grenoble 38000, France.

CNRS, LPNC, Université Grenoble Alpes, BSHM, Université Savoie Mont Blanc, UMR 5105, Cedex, Grenoble 38000, France.

出版信息

Neuroimage. 2022 Nov;263:119672. doi: 10.1016/j.neuroimage.2022.119672. Epub 2022 Oct 6.

Abstract

Language processing is a highly integrative function, intertwining linguistic operations (processing the language code intentionally used for communication) and extra-linguistic processes (e.g., attention monitoring, predictive inference, long-term memory). This synergetic cognitive architecture requires a distributed and specialized neural substrate. Brain systems have mainly been examined at rest. However, task-related functional connectivity provides additional and valuable information about how information is processed when various cognitive states are involved. We gathered thirteen language fMRI tasks in a unique database of one hundred and fifty neurotypical adults (InLang [Interactive networks of Language] database), providing the opportunity to assess language features across a wide range of linguistic processes. Using this database, we applied network theory as a computational tool to model the task-related functional connectome of language (LANG atlas). The organization of this data-driven neurocognitive atlas of language was examined at multiple levels, uncovering its major components (or crucial subnetworks), and its anatomical and functional correlates. In addition, we estimated its reconfiguration as a function of linguistic demand (flexibility) or several factors such as age or gender (variability). We observed that several discrete networks could be specifically shaped to promote key functional features of language: coding-decoding (Net1), control-executive (Net2), abstract-knowledge (Net3), and sensorimotor (Net4) functions. The architecture of these systems and the functional connectivity of the pivotal brain regions varied according to the nature of the linguistic process, gender, or age. By accounting for the multifaceted nature of language and modulating factors, this study can contribute to enriching and refining existing neurocognitive models of language. The LANG atlas can also be considered a reference for comparative or clinical studies involving various patients and conditions.

摘要

语言处理是一项高度综合的功能,交织了语言操作(处理为了交流而有意使用的语言代码)和语言外过程(例如,注意力监测、预测推理、长期记忆)。这种协同认知架构需要分布式和专门的神经基质。大脑系统主要在静息状态下进行检查。然而,任务相关的功能连接提供了额外的、有价值的信息,说明当涉及到各种认知状态时,信息是如何被处理的。我们在一个独特的一百五十名神经典型成年人的数据库中收集了十三个语言 fMRI 任务(InLang [互动语言网络]数据库),提供了评估广泛语言过程中语言特征的机会。使用这个数据库,我们应用网络理论作为一种计算工具来模拟语言的任务相关功能连接组(LANG 图谱)。在多个层次上检查了这个数据驱动的语言神经认知图谱的组织,揭示了其主要组成部分(或关键子网)及其解剖和功能相关性。此外,我们还估计了它作为语言需求(灵活性)或年龄或性别等几个因素的函数的重新配置(可变性)。我们观察到,几个离散的网络可以专门形成,以促进语言的关键功能特征:编码-解码(Net1)、控制-执行(Net2)、抽象知识(Net3)和感觉运动(Net4)功能。这些系统的结构和关键大脑区域的功能连接根据语言过程的性质、性别或年龄而有所不同。通过考虑语言的多面性质和调节因素,这项研究有助于丰富和完善现有的语言神经认知模型。LANG 图谱也可以被视为涉及各种患者和情况的比较或临床研究的参考。

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