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

doi:10.1088/1674-1056/20/3/038701

中国物理B ›› 2011, Vol. 20 ›› Issue (3): 38701-038701.doi: 10.1088/1674-1056/20/3/038701

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

李凌¹, 金贞兰¹, 李斌²

(1)Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China; (2)School of Physical Electronics, University of Electronic Science and Technology of China, Chengdu 610054, China

收稿日期:2010-08-09 修回日期:2010-10-22 出版日期:2011-03-15 发布日期:2011-03-15
基金资助:
Project supported by the Young Scientists Fund of the National Natural Science Foundation of China (Grant No. 30800242).

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

Li Ling(李凌)^a),Jin Zhen-Lan(金贞兰)^a),and Li Bin(李斌)^b)^†

^a Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China; ^b School of Physical Electronics, University of Electronic Science and Technology of China, Chengdu 610054, China

Received:2010-08-09 Revised:2010-10-22 Online:2011-03-15 Published:2011-03-15
Supported by:
Project supported by the Young Scientists Fund of the National Natural Science Foundation of China (Grant No. 30800242).

摘要/Abstract

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 coefficient 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.

关键词: electroencephalogram, phase synchronization, rhythm, functional brain network

Abstract: 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 coefficient 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.

Key words: electroencephalogram, phase synchronization, rhythm, functional brain network

中图分类号: (EEG and MEG)

87.19.le

64.60.aq (Networks) 89.75.Fb (Structures and organization in complex systems)

李凌, 金贞兰, 李斌. Analysis of a phase synchronized functional network based on the rhythm of brain activities[J]. 中国物理B, 2011, 20(3): 38701-038701.

Li Ling(李凌), Jin Zhen-Lan(金贞兰), and Li Bin(李斌) . Analysis of a phase synchronized functional network based on the rhythm of brain activities[J]. Chin. Phys. B, 2011, 20(3): 38701-038701.

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

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

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