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Spatial Complex Brain Network

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EEG Signal Processing and Feature Extraction

Abstract

This chapter introduces the research status of spatial complex brain networks from the perspective of graph theory and complex networks. Firstly, we review the theoretical concepts of graph theory and complex networks, and combined them with spatial complex brain networks. We focused on a variety of important network topological properties, and then introduced them based on structural connections, functional connections, and cost-effective connections. Three different types of brain networks were established, and further studies on the relationship between structural brain networks and functional brain networks, as well as brain network research based on computational models. Finally, we discussed the future research directions of spatial complex brain networks.

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Authors and Affiliations

  1. School of Information Science and Engineering, Yanshan University, Qinhuangdao, Hebei, China

    Dong Wen, Zhenhao Wei & Yanbo Sun

  2. School of Mathematics and Information Science and Technology, Hebei Normal University of Science and Technology, Qinhuangdao, Hebei, China

    Yanhong Zhou

  3. Yanshan University Library, Yanshan University, Qinhuangdao, Hebei, China

    Fengnian Li

  4. Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, China

    Jiewei Li

Authors
  1. Dong Wen
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  2. Zhenhao Wei
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  3. Yanhong Zhou
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  4. Yanbo Sun
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  5. Fengnian Li
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  6. Jiewei Li
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Corresponding author

Correspondence to Dong Wen .

Editor information

Editors and Affiliations

  1. CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China

    Li Hu

  2. School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, Guangdong, China

    Zhiguo Zhang

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Wen, D., Wei, Z., Zhou, Y., Sun, Y., Li, F., Li, J. (2019). Spatial Complex Brain Network. In: Hu, L., Zhang, Z. (eds) EEG Signal Processing and Feature Extraction. Springer, Singapore. https://doi.org/10.1007/978-981-13-9113-2_13

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