Inhomogeneous Coherent States in Small-World Networks: Application to the Brain Networks
American Journal of Physics and Applications
Volume 7, Issue 3, May 2019, Pages: 68-72
Received: Apr. 20, 2019;
Accepted: Jun. 11, 2019;
Published: Jun. 25, 2019
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Bahruz Gadjiev, Institute of System Analysis and Management, Dubna State University, Dubna, Russia
Tatiana Progulova, Institute of System Analysis and Management, Dubna State University, Dubna, Russia
We study the dynamics of the processes in the small-world networks with a power-law degree distribution where every node is considered to be in one of the two available statuses. We present an algorithm for generation of such network and determine analytically a temporal dependence of the network nodes degrees and using the maximum entropy principle we define a degree distribution of the network. We discuss the results of the Ising discrete model for small-world networks and in the framework of the continuous approach using the principle of least action, we derive an equation of motion for the order parameter in these networks in the form of a fractional differential equation. The obtained equation enables the description of the problem of a spontaneous symmetry breaking in the system and determination of the spatio-temporal dependencies of the order parameter in varies stable phases of the system. In the cases of one and two component order parameters with taken into account major and secondary order parameters we obtain analytical solutions of the equation of motion for the order parameters and determine solutions for various regimes of the system functioning. We apply the obtained results to the description of the processes in the brain and discuss the problems of emergence of mind.
Inhomogeneous Coherent States in Small-World Networks: Application to the Brain Networks, American Journal of Physics and Applications.
Vol. 7, No. 3,
2019, pp. 68-72.
Copyright © 2019 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/
) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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