21 April 2016 Analysis of the characteristics of the synchronous clusters in the adaptive Kuramoto network and neural network of the epileptic brain
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Abstract
In the paper we study the mechanisms of phase synchronization in the adaptive model network of Kuramoto oscillators and the neural network of brain by consideration of the integral characteristics of the observed networks signals. As the integral characteristics of the model network we consider the summary signal produced by the oscillators. Similar to the model situation we study the ECoG signal as the integral characteristic of neural network of the brain. We show that the establishment of the phase synchronization results in the increase of the peak, corresponding to synchronized oscillators, on the wavelet energy spectrum of the integral signals. The observed correlation between the phase relations of the elements and the integral characteristics of the whole network open the way to detect the size of synchronous clusters in the neural networks of the epileptic brain before and during seizure.
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Alexander E. Hramov, Alexander A. Kharchenko, Vladimir V. Makarov, Marina V. Khramova, Alexey A. Koronovskii, Alexey N. Pavlov, Syamal K. Dana, "Analysis of the characteristics of the synchronous clusters in the adaptive Kuramoto network and neural network of the epileptic brain", Proc. SPIE 9917, Saratov Fall Meeting 2015: Third International Symposium on Optics and Biophotonics and Seventh Finnish-Russian Photonics and Laser Symposium (PALS), 991725 (21 April 2016); doi: 10.1117/12.2229833; https://doi.org/10.1117/12.2229833
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