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A Naïve Hypergraph Model of Brain Networks

  • Zhijiang Wang
  • Jiming Liu
  • Ning Zhong
  • Yulin Qin
  • Haiyan Zhou
  • Jian Yang
  • Kuncheng Li
Part of the Lecture Notes in Computer Science book series (LNCS, 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.

Keywords

Functional Connectivity Default Mode Network Brain Network Maximum Clique Eigenvector Centrality 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Zhijiang Wang
    • 1
    • 2
  • Jiming Liu
    • 1
    • 2
    • 3
  • Ning Zhong
    • 1
    • 2
    • 4
  • Yulin Qin
    • 1
    • 2
    • 5
  • Haiyan Zhou
    • 1
    • 2
  • Jian Yang
    • 1
    • 2
  • Kuncheng Li
    • 6
    • 2
  1. 1.International WIC InstituteBeijing University of TechnologyChina
  2. 2.Beijing Key Laboratory of MRI and Brain InformaticsChina
  3. 3.Dept. of Computer ScienceHong Kong Baptist UniversityChina
  4. 4.Dept. of Life Science and InformaticsMaebashi Institute of TechnologyJapan
  5. 5.Dept. of PsychologyCarnegie Mellon UniversityUSA
  6. 6.Dept. of Radiology, Xuanwu HospitalCapital Medical UniversityChina

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