Literature DB >> 28147497

Hidden structures of information transport underlying spiral wave dynamics.

Hiroshi Ashikaga1, Ryan G James2.   

Abstract

A spiral wave is a macroscopic dynamics of excitable media that plays an important role in several distinct systems, including the Belousov-Zhabotinsky reaction, seizures in the brain, and lethal arrhythmia in the heart. Because the spiral wave dynamics can exhibit a wide spectrum of behaviors, its precise quantification can be challenging. Here we present a hybrid geometric and information-theoretic approach to quantifying the spiral wave dynamics. We demonstrate the effectiveness of our approach by applying it to numerical simulations of a two-dimensional excitable medium with different numbers and spatial patterns of spiral waves. We show that, by defining the information flow over the excitable medium, hidden coherent structures emerge that effectively quantify the information transport underlying the spiral wave dynamics. Most importantly, we find that some coherent structures become more clearly defined over a longer observation period. These findings provide validity with our approach to quantitatively characterize the spiral wave dynamics by focusing on information transport. Our approach is computationally efficient and is applicable to many excitable media of interest in distinct physical, chemical, and biological systems. Our approach could ultimately contribute to an improved therapy of clinical conditions such as seizures and cardiac arrhythmia by identifying potential targets of interventional therapies.

Entities:  

Mesh:

Year:  2017        PMID: 28147497     DOI: 10.1063/1.4973542

Source DB:  PubMed          Journal:  Chaos        ISSN: 1054-1500            Impact factor:   3.642


  4 in total

1.  Scale-invariant structures of spiral waves.

Authors:  Daniel Sohn; Konstantinos Aronis; Hiroshi Ashikaga
Journal:  Comput Biol Med       Date:  2018-11-14       Impact factor: 4.589

2.  Impact of number of co-existing rotors and inter-electrode distance on accuracy of rotor localization.

Authors:  Konstantinos N Aronis; Hiroshi Ashikaga
Journal:  J Electrocardiol       Date:  2017-09-01       Impact factor: 1.438

3.  Atrial fibrillation driver identification through regional mutual information networks: a modeling perspective.

Authors:  Qun Sha; Luizetta Elliott; Xiangming Zhang; Tzachi Levy; Tushar Sharma; Ahmed Abdelaal
Journal:  J Interv Card Electrophysiol       Date:  2022-01-04       Impact factor: 1.759

4.  Locating Order-Disorder Phase Transition in a Cardiac System.

Authors:  Hiroshi Ashikaga; Ameneh Asgari-Targhi
Journal:  Sci Rep       Date:  2018-01-31       Impact factor: 4.379

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.