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Comparison of the small-world topology between anatomical and functional connectivity in the human brain

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  • Park, Chang-hyun
  • Kim, Soo Yong
  • Kim, Yun-Hee
  • Kim, Kyungsik

Abstract

We applied graph analysis to both anatomical and functional connectivity in the human brain. Anatomical connectivity was acquired from diffusion tensor imaging data by probabilistic fiber tracking, and functional connectivity was extracted from resting-state functional magnetic resonance imaging data by calculating correlation maps of time series. For the same subject, anatomical networks seemed to be disassortative, while functional networks were significantly assortative. Anatomical networks showed higher efficiency and smaller diameters than functional networks. It can be proposed that anatomical connectivity, as a major constraint of functional connectivity, has a relatively stable and efficient structure to support functional connectivity that is more changeable and flexible.

Suggested Citation

  • Park, Chang-hyun & Kim, Soo Yong & Kim, Yun-Hee & Kim, Kyungsik, 2008. "Comparison of the small-world topology between anatomical and functional connectivity in the human brain," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(23), pages 5958-5962.
    • Handle: RePEc:eee:phsmap:v:387:y:2008:i:23:p:5958-5962
    DOI: 10.1016/j.physa.2008.06.048
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    References listed on IDEAS

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    1. Latora, Vito & Marchiori, Massimo, 2002. "Is the Boston subway a small-world network?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 314(1), pages 109-113.
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    Cited by:

    1. Mite Mijalkov & Joana B Pereira & Giovanni Volpe, 2020. "Delayed correlations improve the reconstruction of the brain connectome," PLOS ONE, Public Library of Science, vol. 15(2), pages 1-22, February.
    2. Gafarov, F.M., 2016. "Emergence of the small-world architecture in neural networks by activity dependent growth," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 409-418.

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