Analysis of a phase synchronized functional network based on the rhythm of brain activities

作     者：李凌 金贞兰 李斌 

作者机构：Key Laboratory for NeuroInformation of Ministry of EducationSchool of Life Science and Technology University of Electronic Science and Technology of China School of Physical ElectronicsUniversity of Electronic Science and Technology of China 

出 版 物：《Chinese Physics B》 (中国物理B（英文版）)

年 卷 期：2011年第20卷第3期

页      面：512-518页

核心收录：

学科分类：0710[理学-生物学] 07[理学] 071006[理学-神经生物学] 0805[工学-材料科学与工程（可授工学、理学学位）] 0704[理学-天文学] 

基　　金：supported by the Young Scientists Fund of the National Natural Science Foundation of China (Grant No. 30800242) 

主　　题：electroencephalogram phase synchronization rhythm functional brain network 

摘      要：Rhythm of brain activities represents oscillations of postsynaptic potentials in neocortex, therefore it can serve as an indicator of the brain activity state. In order to check the connectivity of brain rhythm, this paper develops a new method of constructing functional network based on phase synchronization. Electroencephalogram （EEG） data were collected while subjects looking at a green cross in two states, performing an attention task and relaxing with eyes-open. The EEG from these two states was filtered by three band-pass filters to obtain signals of theta （4-7 Hz）, alpha （8-13 Hz） and beta （14-30 Hz） bands. Mean resultant length was used to estimate strength of phase synchronization in three bands to construct networks of both states, and mean degree K and cluster coefficient C of networks were calculated as a function of threshold. The result shows higher cluster coetticient in the attention state than in the eyes-open state in all three bands, suggesting that cluster coefficient reflects brain state. In addition, an obvious fronto-parietal network is found in the attention state, which is a well-known attention network. These results indicate that attention modulates the fronto-parietal connectivity in different modes as compared with the eyes-open state. Taken together this method is an objective and important tool to study the properties of neural networks of brain rhythm,