Clustering Coefficients for Correlation Networks

@article{Masuda2018ClusteringCF,
  title={Clustering Coefficients for Correlation Networks},
  author={N. Masuda and Michiko Sakaki and T. Ezaki and T. Watanabe},
  journal={Frontiers in Neuroinformatics},
  year={2018},
  volume={12}
}
  • N. Masuda, Michiko Sakaki, +1 author T. Watanabe
  • Published 2018
  • Computer Science, Physics, Biology, Medicine
  • Frontiers in Neuroinformatics
  • Graph theory is a useful tool for deciphering structural and functional networks of the brain on various spatial and temporal scales. The clustering coefficient quantifies the abundance of connected triangles in a network and is a major descriptive statistics of networks. For example, it finds an application in the assessment of small-worldness of brain networks, which is affected by attentional and cognitive conditions, age, psychiatric disorders and so forth. However, it remains unclear how… CONTINUE READING

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