Identifying important nodes in weighted functional brain networks: A comparison of different centrality approaches
Identifying important nodes in weighted functional brain networks: A comparison of different centrality approaches
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DOI：
10.1063/1.4729185
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发表时间：
2012-06-01
期刊：
影响因子：
2.9
通讯作者：
Lehnertz, Klaus
中科院分区：
文献类型：
--
作者：
Kuhnert, Marie-Therese;Geier, Christian;Lehnertz, Klaus
我们比较了旨在识别复杂网络中重要节点的不同中心性度量。我们研究了从 23 名健康受试者在静息状态下睁眼或闭眼条件下记录的多通道脑电图得出的加权功能性大脑网络。尽管我们观察到指标强度、紧密度和介数中心性彼此相关，但它们捕获了这些网络中与行为变化相关的重要节点的不同空间和时间方面。因此，这些节点的识别和表征受益于多个中心性度量的应用。 (C) 2012 年美国物理研究所。 [http://dx.doi.org/10.1063/1.4729185]
We compare different centrality metrics which aim at an identification of important nodes in complex networks. We investigate weighted functional brain networks derived from multichannel electroencephalograms recorded from 23 healthy subject under resting-state eyes-open or eyes-closed conditions. Although we observe the metrics strength, closeness, and betweenness centrality to be related to each other, they capture different spatial and temporal aspects of important nodes in these networks associated with behavioral changes. Identifying and characterizing of these nodes thus benefits from the application of several centrality metrics. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4729185]