Literature DB >> 20921003

Theory of hybrid dynamical systems and its applications to biological and medical systems.

Kazuyuki Aihara1, Hideyuki Suzuki.   

Abstract

In this introductory article, we survey the contents of this Theme Issue. This Theme Issue deals with a fertile region of hybrid dynamical systems that are characterized by the coexistence of continuous and discrete dynamics. It is now well known that there exist many hybrid dynamical systems with discontinuities such as impact, switching, friction and sliding. The first aim of this Issue is to discuss recent developments in understanding nonlinear dynamics of hybrid dynamical systems in the two main theoretical fields of dynamical systems theory and control systems theory. A combined study of the hybrid systems dynamics in the two theoretical fields might contribute to a more comprehensive understanding of hybrid dynamical systems. In addition, mathematical modelling by hybrid dynamical systems is particularly important for understanding the nonlinear dynamics of biological and medical systems as they have many discontinuities such as threshold-triggered firing in neurons, on-off switching of gene expression by a transcription factor, division in cells and certain types of chronotherapy for prostate cancer. Hence, the second aim is to discuss recent applications of hybrid dynamical systems in biology and medicine. Thus, this Issue is not only general to serve as a survey of recent progress in hybrid systems theory but also specific to introduce interesting and stimulating applications of hybrid systems in biology and medicine. As the introduction to the topics in this Theme Issue, we provide a brief history of nonlinear dynamics and mathematical modelling, different mathematical models of hybrid dynamical systems, the relationship between dynamical systems theory and control systems theory, examples of complex behaviour in a simple neuron model and its variants, applications of hybrid dynamical systems in biology and medicine as a road map of articles in this Theme Issue and future directions of hybrid systems modelling.

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Year:  2010        PMID: 20921003     DOI: 10.1098/rsta.2010.0237

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


  14 in total

1.  Stochastic modelling and control of antibiotic subtilin production.

Authors:  V Thalhofer; M Annunziato; A Borzì
Journal:  J Math Biol       Date:  2016-02-02       Impact factor: 2.259

Review 2.  Transcranial Electrical Stimulation: What We Know and Do Not Know About Mechanisms.

Authors:  Anna Fertonani; Carlo Miniussi
Journal:  Neuroscientist       Date:  2016-07-08       Impact factor: 7.519

3.  Towards dynamical network biomarkers in neuromodulation of episodic migraine.

Authors:  Markus A Dahlem; Sebastian Rode; Arne May; Naoya Fujiwara; Yoshito Hirata; Kazuyuki Aihara; Jürgen Kurths
Journal:  Transl Neurosci       Date:  2013-09       Impact factor: 1.757

4.  Chaotic Boltzmann machines.

Authors:  Hideyuki Suzuki; Jun-ichi Imura; Yoshihiko Horio; Kazuyuki Aihara
Journal:  Sci Rep       Date:  2013       Impact factor: 4.379

5.  Quantitative mathematical modeling of PSA dynamics of prostate cancer patients treated with intermittent androgen suppression.

Authors:  Yoshito Hirata; Koichiro Akakura; Celestia S Higano; Nicholas Bruchovsky; Kazuyuki Aihara
Journal:  J Mol Cell Biol       Date:  2012-05-04       Impact factor: 6.216

6.  Population physiology: leveraging electronic health record data to understand human endocrine dynamics.

Authors:  D J Albers; George Hripcsak; Michael Schmidt
Journal:  PLoS One       Date:  2012-12-14       Impact factor: 3.240

7.  Risk factor-dependent dynamics of atopic dermatitis: modelling multi-scale regulation of epithelium homeostasis.

Authors:  Elisa Domínguez-Hüttinger; Masahiro Ono; Mauricio Barahona; Reiko J Tanaka
Journal:  Interface Focus       Date:  2013-04-06       Impact factor: 3.906

8.  Routes to Chaos Induced by a Discontinuous Resetting Process in a Hybrid Spiking Neuron Model.

Authors:  Sou Nobukawa; Haruhiko Nishimura; Teruya Yamanishi
Journal:  Sci Rep       Date:  2018-01-10       Impact factor: 4.379

9.  Chaotic Ising-like dynamics in traffic signals.

Authors:  Hideyuki Suzuki; Jun-ichi Imura; Kazuyuki Aihara
Journal:  Sci Rep       Date:  2013-01-24       Impact factor: 4.379

10.  Nonlinear dynamics analysis of a self-organizing recurrent neural network: chaos waning.

Authors:  Jürgen Eser; Pengsheng Zheng; Jochen Triesch
Journal:  PLoS One       Date:  2014-01-23       Impact factor: 3.240

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