An ant colony biological inspired way for statistical shortest paths in complex brain networks

  • Authors:

  • Gao Fei;Fei Feng-xia;Ilangko Balasingham

  • Affiliations:

  • Wuhan University of Technology, Wuhan, Hubei, China and Norwegian University of Science and Technology, Trondheim, Norway;Wuhan University of Technology Wuhan, Hubei, China;Norwegian University of Science and Technology, Trondheim, Norway and University of Oslo, Norway

  • Venue:
  • Proceedings of the 7th International Conference on Body Area Networks
  • Year:
  • 2012

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Abstract

What is the mechanism of information transferring, when some of the brain nerves' links do not work? Brain is the most complex, ingenious processing system in world. The complex brain networks is an inter-discipline of complex networks and neuroscience. In this paper, an ant colony optimizations are introduced to solve the crux, shortest path for information transferring mechanism. Some reviews are presented on progress of complex brain networks and computational neuroscience firstly. The deep research on brain complex networks will have a profound effects on artificial intelligence methods which models the mechanisms. Then simulations are done to finding shortest path in probabilities for theoretical nerve networks through ant colony optimization methods. The results show the proposed way is a successful method in detecting the statistical shortest path in brain networks when nerves' link broken, with the advantages of fast convergence and robustness.