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

N/ACitations
Citations of this article
7Readers
Mendeley users who have this article in their library.

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.

Cite

CITATION STYLE

APA

Gao, F., Fei, F. X., & Balasingham, I. (2012). An ant colony biological inspired way for statistical shortest paths in complex brain networks. In BODYNETS 2012 - 7th International Conference on Body Area Networks. ICST. https://doi.org/10.4108/icst.bodynets.2012.249961

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free