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The associative-semantic network for words and pictures: Effective connectivity and graph analysis

机译:文字和图片的关联语义网络:有效的连通性和图形分析

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摘要

Explicit associative-semantic processing of words and pictures activates a distributed set of brain areas that has been replicated across a wide range of studies. We applied graph analysis to examine the structure of this network. We determined how the left ventral occipitotemporal transition zone (vOT) was connected to word-specific areas. A modularity analysis discerned four communities: one corresponded to the classical perisylvian language system, including superior temporal sulcus (STS), middle temporal gyrus (GTm) and pars triangularis of the inferior frontal gyrus (GFi), among other nodes. A second subsystem consisted of vOT and anterior fusiform gyrus along with hippocampus and intraparietal sulcus. The two subsystems were linked through a unique connection between vOT and GTm, which were hubs with a high betweenness centrality compared to STS and GFi which had a high local clustering coefficient. Graph analysis reveals novel insights into the structure of the network for associative-semantic processing.
机译:单词和图片的显式联想语义处理激活了一组分布在广泛研究中的大脑区域。我们应用图分析来检查该网络的结构。我们确定了左腹枕颞过渡区(vOT)如何连接到特定单词的区域。模块化分析可识别四个社区:一个社区对应于经典的沿岸生物语言系统,包括上颞沟(STS),中颞回(GTm)和额额下回(GFi)的三角形三角肌,以及其他节点。第二个子系统由vOT和前梭形回以及海马和顶壁沟组成。这两个子系统通过vOT和GTm之间的独特连接而链接在一起,而vOT和GTm是具有较高中间聚类性的集线器,而STS和GFi具有较高的局部聚类系数。图分析揭示了对用于关联语义处理的网络结构的新颖见解。

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