Reconstruction of phase dynamics from macroscopic observations based on linear and nonlinear response theories

被引:0
|
作者
Yamaguchi, Yoshiyuki Y. [1 ]
Terada, Yu [2 ,3 ,4 ]
机构
[1] Kyoto Univ, Grad Sch Informat, Kyoto 6068501, Japan
[2] Univ Calif San Diego, Dept Neurobiol, La Jolla, CA 92093 USA
[3] Univ Tokyo, Inst Phys Intelligence, Grad Sch Sci, Dept Phys, 7-3-1 Hongo,Bunkyo Ku, Tokyo 1130033, Japan
[4] RIKEN Ctr Brain Sci, Lab Neural Computat & Adaptat, 2-1 Hirosawa, Wako, Saitama 3510198, Japan
基金
日本学术振兴会;
关键词
MEAN-FIELD ANALYSIS; KURAMOTO MODEL; TIME-DELAY; LIMIT; OSCILLATORS; TRANSITIONS; SYNCHRONY; REDUCTION; NETWORKS; SYSTEMS;
D O I
10.1103/PhysRevE.109.024217
中图分类号
O35 [流体力学]; O53 [等离子体物理学];
学科分类号
070204 ; 080103 ; 080704 ;
摘要
We propose a method to reconstruct the phase dynamics in rhythmical interacting systems from macroscopic responses to weak inputs by developing linear and nonlinear response theories, which predict the responses in a given system. By solving an inverse problem, the method infers an unknown system: the natural frequency distribution, the coupling function, and the time delay which is inevitable in real systems. In contrast to previous methods, our method requires neither strong invasiveness nor microscopic observations. We demonstrate that the method reconstructs two phase systems from observed responses accurately. The qualitative methodological advantages demonstrated by our quantitative numerical examinations suggest its broad applicability in various fields, including brain systems, which are often observed through macroscopic signals such as electroencephalograms and functional magnetic response imaging.
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页数:10
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