Department of Mathematics and Computing, Indian Institute of Technology (Indian School of Mines), Dhanbad 826004, India.
School of Engineering, Amrita Vishwa Vidyapeetham, Amritapuri, Kollam 690525, India.
Chaos. 2021 Oct;31(10):103122. doi: 10.1063/5.0055389.
In this paper, we study an excitable, biophysical system that supports wave propagation of nerve impulses. We consider a slow-fast, FitzHugh-Rinzel neuron model where only the membrane voltage interacts diffusively, giving rise to the formation of spatiotemporal patterns. We focus on local, nonlinear excitations and diverse neural responses in an excitable one- and two-dimensional configuration of diffusively coupled FitzHugh-Rinzel neurons. The study of the emerging spatiotemporal patterns is essential in understanding the working mechanism in different brain areas. We derive analytically the coefficients of the amplitude equations in the vicinity of Hopf bifurcations and characterize various patterns, including spirals exhibiting complex geometric substructures. Furthermore, we derive analytically the condition for the development of antispirals in the neighborhood of the bifurcation point. The emergence of broken target waves can be observed to form spiral-like profiles. The spatial dynamics of the excitable system exhibits two- and multi-arm spirals for small diffusive couplings. Our results reveal a multitude of neural excitabilities and possible conditions for the emergence of spiral-wave formation. Finally, we show that the coupled excitable systems with different firing characteristics participate in a collective behavior that may contribute significantly to irregular neural dynamics.
在本文中,我们研究了一个兴奋的生物物理系统,该系统支持神经冲动的波传播。我们考虑了一个慢-快的 FitzHugh-Rinzel 神经元模型,其中只有膜电压弥散相互作用,导致时空模式的形成。我们关注局部非线性激发和扩散耦合 FitzHugh-Rinzel 神经元的一维和二维兴奋结构中的不同神经反应。对新兴时空模式的研究对于理解不同脑区的工作机制至关重要。我们在 Hopf 分岔附近解析地推导出振幅方程的系数,并表征各种模式,包括表现出复杂几何亚结构的螺旋。此外,我们还解析地推导出在分岔点附近出现反螺旋的条件。可以观察到破碎的目标波的出现,形成螺旋状的轮廓。兴奋系统的空间动力学在小扩散耦合下表现出双臂和多臂螺旋。我们的结果揭示了多种神经兴奋性和可能的螺旋波形成条件。最后,我们表明具有不同发射特性的耦合兴奋系统参与集体行为,这可能对不规则的神经动力学有重大贡献。