How the intrinsic functional connectivity patterns of the semantic network support semantic processing.

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
ACS Applied Bio Materials Pub Date : 2024-06-01 Epub Date: 2024-01-23 DOI:10.1007/s11682-024-00849-y
Chengmei Huang, Aqian Li, Yingdan Pang, Jiayi Yang, Jingxian Zhang, Xiaoyan Wu, Leilei Mei
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Abstract

Semantic processing, a core of language comprehension, involves the activation of brain regions dispersed extensively across the frontal, temporal, and parietal cortices that compose the semantic network. To comprehend the functional structure of this semantic network and how it prepares for semantic processing, we investigated its intrinsic functional connectivity (FC) and the relation between this pattern and semantic processing ability in a large sample from the Human Connectome Project (HCP) dataset. We first defined a well-studied brain network for semantic processing, and then we characterized the within-network connectivity (WNC) and the between-network connectivity (BNC) within this network using a voxel-based global brain connectivity (GBC) method based on resting-state functional magnetic resonance imaging (fMRI). The results showed that 97.73% of the voxels in the semantic network displayed considerably greater WNC than BNC, demonstrating that the semantic network is a fairly encapsulated network. Moreover, multiple connector hubs in the semantic network were identified after applying the criterion of WNC > 1 SD above the mean WNC of the semantic network. More importantly, three of these connector hubs (i.e., the left anterior temporal lobe, angular gyrus, and orbital part of the inferior frontal gyrus) were reliably associated with semantic processing ability. Our findings suggest that the three identified regions use WNC as the central mechanism for supporting semantic processing and that task-independent spontaneous connectivity in the semantic network is essential for semantic processing.

Abstract Image

语义网络的内在功能连接模式如何支持语义处理。
语义处理是语言理解的核心,需要激活广泛分布于额叶、颞叶和顶叶皮层的大脑区域,这些区域组成了语义网络。为了了解这一语义网络的功能结构及其如何为语义处理做准备,我们从人类连接组计划(HCP)数据集的一个大样本中研究了其内在功能连接性(FC)以及这种模式与语义处理能力之间的关系。我们首先定义了一个经过充分研究的语义处理脑网络,然后使用基于静息态功能磁共振成像(fMRI)的体素全局脑连通性(GBC)方法,描述了该网络中的网内连通性(WNC)和网间连通性(BNC)。结果显示,语义网络中97.73%的体素显示的WNC远大于BNC,这表明语义网络是一个相当封装的网络。此外,在应用 WNC > 高于语义网络平均 WNC 1 SD 的标准后,还发现了语义网络中的多个连接器枢纽。更重要的是,其中三个连接枢纽(即左侧颞叶前部、角回和额下回眶部)与语义处理能力有可靠的关联。我们的研究结果表明,这三个被识别的区域使用WNC作为支持语义加工的中心机制,而且语义网络中与任务无关的自发连接对语义加工至关重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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