Ashikaga Hiroshi, James Ryan G
Cardiac Arrhythmia Service, Johns Hopkins University School of Medicine, 600N Wolfe Street, Carnegie 568, Baltimore, Maryland 21287, USA.
Complexity Sciences Center, Department of Physics, University of California, Davis, One Shields Avenue, Davis, California 95616-8572, USA.
Chaos. 2017 Jan;27(1):013106. doi: 10.1063/1.4973542.
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.
螺旋波是可兴奋介质的一种宏观动力学现象，在包括贝洛索夫 - 扎博廷斯基反应、大脑癫痫发作以及心脏致命性心律失常等多个不同系统中发挥着重要作用。由于螺旋波动力学能够展现出广泛的行为谱，其精确量化具有挑战性。在此，我们提出一种几何与信息论相结合的混合方法来量化螺旋波动力学。我们通过将其应用于具有不同数量和空间模式螺旋波的二维可兴奋介质的数值模拟，来证明我们方法的有效性。我们表明，通过定义可兴奋介质上的信息流，会出现隐藏的相干结构，这些结构有效地量化了螺旋波动力学背后的信息传输。最重要的是，我们发现一些相干结构在更长的观测期内会变得更加清晰。这些发现为我们通过关注信息传输来定量表征螺旋波动力学的方法提供了有效性验证。我们的方法计算效率高，适用于不同物理、化学和生物系统中许多感兴趣的可兴奋介质。我们的方法最终可能通过识别介入治疗的潜在靶点，为癫痫和心律失常等临床病症的改进治疗做出贡献。
