论文标题

在分析电磁通量影响下的Chialvo神经元的变化噪声调节的异质耦合网络中

On the analysis of a time varying noise-modulated heterogeneous coupled network of Chialvo neurons under the influence of electromagnetic flux

论文作者

Ghosh, Indranil, Muni, Sishu Shankar, Fatoyinbo, Hammed Olawale

论文摘要

我们对电磁通量在以环形拓扑拓扑为代表的Chialvo神经元网络上应用的数值研究进行了数值研究。通过对拓扑中的中央 - 外围 - 外交耦合链路引入加性噪声调制,可以实现异质性,这些噪声不仅在空间上,而且及时及时变化。时间的变化是通过两个耦合概率来理解的,一个耦合概率分别用于外围 - 外围连接,另一个用于外围 - 外围连接,这可以在每次迭代时更新网络拓扑。我们进一步报道了在整个网络动力学中出现的富裕时空模式,例如两个群集状态,嵌合体状态,旅行波,连贯和异步状态。我们还研究了一种称为“孤立节点”的特殊异步行为的出现,该行为具有与现实世界神经系统有关的广泛应用。为了表征在这些异质性影响下节点的行为,我们研究了两个称为“互相关系数”和“同步误差”的不同指标。此外,为了捕获网络的统计特性,例如,系统的行为如何复杂,我们还研究了一种称为“样本熵”的度量。在研究中介绍了各种二维色编码图,以展示这些指标/措施如何以参数的变化来表现。最后,通过主动力学变量的最后一个实例的一维分叉图(即,与膜电位相关的状态变量与不同的网络参数相关的状态变量)显示,节点如何同步或异步。

We perform a numerical study on the application of electromagnetic flux on a heterogeneous network of Chialvo neurons represented by a ring-star topology. Heterogeneities are realized by introducing additive noise modulations on both the central-peripheral and the peripheral-peripheral coupling links in the topology that not only vary in space but also in time. The variation in time is understood by two coupling probabilities, one for the central-peripheral connections and the other for the peripheral-peripheral connections respectively, that updates the network topology with each iteration in time. We have further reported the rich spatiotemporal patterns like two-cluster states, chimera states, traveling waves, coherent, and asynchronized states that arise throughout the network dynamics. We have also investigated the appearance of a special kind of asynchronization behavior called "solitary nodes" that have wide range of applications pertaining to real-world nervous systems. In order to characterize the behavior of the nodes under the influence of these heterogeneities, we have studied two different metrics called the "cross-correlation coefficient" and the "synchronization error". Additionally, to capture the statistical property of the network, for example, how complex the system behaves, we have also studied a measure called "sample entropy". Various two-dimensional color-coded plots are presented in the study to exhibit how these metrics/measures behave with the variation of parameters. Finally, how the nodes synchronize or asynchronize is shown via one-dimensional bifurcation diagrams of the last instance of the main dynamical variable, i.e., the state variable associated with the membrane potential, against different network parameters.

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