Literature DB >> 31656141

A practical method for estimating coupling functions in complex dynamical systems.

Isao T Tokuda1, Zoran Levnajic2, Kazuyoshi Ishimura1.   

Abstract

A foremost challenge in modern network science is the inverse problem of reconstruction (inference) of coupling equations and network topology from the measurements of the network dynamics. Of particular interest are the methods that can operate on real (empirical) data without interfering with the system. One such earlier attempt (Tokuda et al. 2007 Phys. Rev. Lett. 99, 064101. (doi:10.1103/PhysRevLett.99.064101)) was a method suited for general limit-cycle oscillators, yielding both oscillators' natural frequencies and coupling functions between them (phase equations) from empirically measured time series. The present paper reviews the above method in a way comprehensive to domain-scientists other than physics. It also presents applications of the method to (i) detection of the network connectivity, (ii) inference of the phase sensitivity function, (iii) approximation of the interaction among phase-coherent chaotic oscillators, and (iv) experimental data from a forced Van der Pol electric circuit. This reaffirms the range of applicability of the method for reconstructing coupling functions and makes it accessible to a much wider scientific community. This article is part of the theme issue 'Coupling functions: dynamical interaction mechanisms in the physical, biological and social sciences'.

Keywords:  coupling function; parameter estimation; phase dynamics

Year:  2019        PMID: 31656141      PMCID: PMC6833996          DOI: 10.1098/rsta.2019.0015

Source DB:  PubMed          Journal:  Philos Trans A Math Phys Eng Sci        ISSN: 1364-503X            Impact factor:   4.226


  51 in total

1.  Synchronization of cellular clocks in the suprachiasmatic nucleus.

Authors:  Shun Yamaguchi; Hiromi Isejima; Takuya Matsuo; Ryusuke Okura; Kazuhiro Yagita; Masaki Kobayashi; Hitoshi Okamura
Journal:  Science       Date:  2003-11-21       Impact factor: 47.728

2.  Determination of a coupling function in multicoupled oscillators.

Authors:  Jun Miyazaki; Shuichi Kinoshita
Journal:  Phys Rev Lett       Date:  2006-05-17       Impact factor: 9.161

3.  Revealing network connectivity from response dynamics.

Authors:  Marc Timme
Journal:  Phys Rev Lett       Date:  2007-05-30       Impact factor: 9.161

4.  Detecting triplet locking by triplet synchronization indices.

Authors:  Björn Kralemann; Arkady Pikovsky; Michael Rosenblum
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2013-05-09

5.  Spectral reconstruction of phase response curves reveals the synchronization properties of mouse globus pallidus neurons.

Authors:  Joshua A Goldberg; Jeremy F Atherton; D James Surmeier
Journal:  J Neurophysiol       Date:  2013-08-21       Impact factor: 2.714

6.  Discovering governing equations from data by sparse identification of nonlinear dynamical systems.

Authors:  Steven L Brunton; Joshua L Proctor; J Nathan Kutz
Journal:  Proc Natl Acad Sci U S A       Date:  2016-03-28       Impact factor: 11.205

7.  Quantifying interactions between real oscillators with information theory and phase models: application to cardiorespiratory coupling.

Authors:  Yenan Zhu; Yee-Hsee Hsieh; Rishi R Dhingra; Thomas E Dick; Frank J Jacono; Roberto F Galán
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2013-02-13

8.  Bayesian Estimation of Phase Dynamics Based on Partially Sampled Spikes Generated by Realistic Model Neurons.

Authors:  Kento Suzuki; Toshio Aoyagi; Katsunori Kitano
Journal:  Front Comput Neurosci       Date:  2018-01-08       Impact factor: 2.380

9.  Modeling Dynamic Systems with Efficient Ensembles of Process-Based Models.

Authors:  Nikola Simidjievski; Ljupčo Todorovski; Sašo Džeroski
Journal:  PLoS One       Date:  2016-04-14       Impact factor: 3.240

10.  Alterations in the coupling functions between cortical and cardio-respiratory oscillations due to anaesthesia with propofol and sevoflurane.

Authors:  Tomislav Stankovski; Spase Petkoski; Johan Raeder; Andrew F Smith; Peter V E McClintock; Aneta Stefanovska
Journal:  Philos Trans A Math Phys Eng Sci       Date:  2016-05-13       Impact factor: 4.226

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  2 in total

1.  Network structure from a characterization of interactions in complex systems.

Authors:  Thorsten Rings; Timo Bröhl; Klaus Lehnertz
Journal:  Sci Rep       Date:  2022-07-11       Impact factor: 4.996

2.  Coupling functions: dynamical interaction mechanisms in the physical, biological and social sciences.

Authors:  Tomislav Stankovski; Tiago Pereira; Peter V E McClintock; Aneta Stefanovska
Journal:  Philos Trans A Math Phys Eng Sci       Date:  2019-10-28       Impact factor: 4.226

  2 in total

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