Paper
14 April 2017 Study of pattern formation in multilayer adaptive network of phase oscillators in application to brain dynamics analysis
Daniil V. Kirsanov, Vladimir O. Nedaivozov, Vladimir V. Makarov, Mikhail V. Goremyko, Alexander E. Hramov
Author Affiliations +
Proceedings Volume 10337, Saratov Fall Meeting 2016: Laser Physics and Photonics XVII; and Computational Biophysics and Analysis of Biomedical Data III; 103370Z (2017) https://doi.org/10.1117/12.2267651
Event: Saratov Fall Meeting 2016: Fourth International Symposium on Optics and Biophotonics, 2016, Saratov, Russian Federation
Abstract
In the report we study the mechanisms of phase synchronization in the model of adaptive network of Kuramoto phase oscillators and discuss the possibility of the further application of the obtained results for the analysis of the neural network of brain. In our theoretical study the model network represents itself as the multilayer structure, in which the links between the elements belonging to the different layers are arranged according to the competitive rule. In order to analyze the dynamical states of the multilayer network we calculate and compare the values of local and global order parameter, which describe the degree of coherence between the neighboring nodes and the elements over whole network, respectively. We find that the global synchronous dynamics takes place for the large values of the coupling strength and are characterized by the identical topology of the interacting layers and a homogeneous distribution of the link strength within each layer. We also show that the partial (or cluster) synchronization, occurs for the small values of the coupling strength, lead to the emergence of the scale-free topology, within the layers.
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Daniil V. Kirsanov, Vladimir O. Nedaivozov, Vladimir V. Makarov, Mikhail V. Goremyko, and Alexander E. Hramov "Study of pattern formation in multilayer adaptive network of phase oscillators in application to brain dynamics analysis", Proc. SPIE 10337, Saratov Fall Meeting 2016: Laser Physics and Photonics XVII; and Computational Biophysics and Analysis of Biomedical Data III, 103370Z (14 April 2017); https://doi.org/10.1117/12.2267651
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KEYWORDS
Oscillators

Brain

Neural networks

Mathematical modeling

Multilayers

Biological research

Data modeling

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