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    Simulating Dynamics of Circulation in the Awake State and Different Stages of Sleep Using Non-autonomous Mathematical Model With Time Delay
    (Lausanne : Frontiers Research Foundation, 2021) Karavaev, Anatoly S.; Ishbulatov, Yurii M.; Prokhorov, Mikhail D.; Ponomarenko, Vladimir I.; Kiselev, Anton R.; Runnova, Anastasiia E.; Hramkov, Alexey N.; Semyachkina-Glushkovskaya, Oxana V.; Kurths, Jürgen; Penzel, Thomas
    We propose a mathematical model of the human cardiovascular system. The model allows one to simulate the main heart rate, its variability under the influence of the autonomic nervous system, breathing process, and oscillations of blood pressure. For the first time, the model takes into account the activity of the cerebral cortex structures that modulate the autonomic control loops of blood circulation in the awake state and in various stages of sleep. The adequacy of the model is demonstrated by comparing its time series with experimental records of healthy subjects in the SIESTA database. The proposed model can become a useful tool for studying the characteristics of the cardiovascular system dynamics during sleep.
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    Basins of attraction of chimera states on networks
    (Lausanne : Frontiers Research Foundation, 2022) Li, Qiang; Larosz, Kelly C.; Han, Dingding; Ji, Peng; Kurths, Jürgen
    Networks of identical coupled oscillators display a remarkable spatiotemporal pattern, the chimera state, where coherent oscillations coexist with incoherent ones. In this paper we show quantitatively in terms of basin stability that stable and breathing chimera states in the original two coupled networks typically have very small basins of attraction. In fact, the original system is dominated by periodic and quasi-periodic chimera states, in strong contrast to the model after reduction, which can not be uncovered by the Ott-Antonsen ansatz. Moreover, we demonstrate that the curve of the basin stability behaves bimodally after the system being subjected to even large perturbations. Finally, we investigate the emergence of chimera states in brain network, through inducing perturbations by stimulating brain regions. The emerged chimera states are quantified by Kuramoto order parameter and chimera index, and results show a weak and negative correlation between these two metrics.