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International Conference on Brain Informatics

BI 2012: Brain Informatics pp 119–129Cite as

A Naïve Hypergraph Model of Brain Networks

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7670))

Abstract

This paper extended the concept of motif by maximum cliques defined as “hyperedges” in brain networks, as novel and flexible characteristic network building blocks. Based on the definition of hyperedge, a naïve brain hypergraph model was constructed from a graph model of large-scale brain functional networks during rest. Nine intrinsic hub hyperedges of functional connectivity were identified, which could be considered as the most important intrinsic information processing blocks (or units), and they also covered many components of the core brain intrinsic networks. Furthermore, these overlapped hub hyperedges were assembled into a compound structure as a core subsystem of the intrinsic brain organization.

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Author information

Authors and Affiliations

  1. International WIC Institute, Beijing University of Technology, China

    Zhijiang Wang, Jiming Liu, Ning Zhong, Yulin Qin, Haiyan Zhou & Jian Yang

  2. Beijing Key Laboratory of MRI and Brain Informatics, China

    Zhijiang Wang, Jiming Liu, Ning Zhong, Yulin Qin, Haiyan Zhou, Jian Yang & Kuncheng Li

  3. Dept. of Computer Science, Hong Kong Baptist University, China

    Jiming Liu

  4. Dept. of Life Science and Informatics, Maebashi Institute of Technology, Japan

    Ning Zhong

  5. Dept. of Psychology, Carnegie Mellon University, USA

    Yulin Qin

  6. Dept. of Radiology, Xuanwu Hospital, Capital Medical University, China

    Kuncheng Li

Authors
  1. Zhijiang Wang
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  2. Jiming Liu
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  3. Ning Zhong
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  4. Yulin Qin
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  5. Haiyan Zhou
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  6. Jian Yang
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  7. Kuncheng Li
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Editor information

Editors and Affiliations

  1. Department of Enterprise Engineering, University of Rome “Tor Vergata”, Viale del Politecnico, 1, 00133, Roma, Italy

    Fabio Massimo Zanzotto

  2. Department of Medical Informatics, Faculty of Medicine, Shimane University, 89-1 Enya-cho, 693-8501, Izumo-city, Shimane, Japan

    Shusaku Tsumoto

  3. Department of Artificial Intelligence, Faculty of Mathematics and Natural Sciences, University of Groningen, Nijenborgh 9, 9747 AG, Groningen, Netherlands

    Niels Taatgen

  4. Department of Computer Science, University of Regina, 3737 Wascana Parkway, S4S 0A2, Regina, SK, Canada

    Yiyu Yao

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© 2012 Springer-Verlag Berlin Heidelberg

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Wang, Z. et al. (2012). A Naïve Hypergraph Model of Brain Networks. In: Zanzotto, F.M., Tsumoto, S., Taatgen, N., Yao, Y. (eds) Brain Informatics. BI 2012. Lecture Notes in Computer Science(), vol 7670. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35139-6_12

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  • DOI: https://doi.org/10.1007/978-3-642-35139-6_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-35138-9

  • Online ISBN: 978-3-642-35139-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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