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Chaotic itinerancy as a mechanism of irregular changes between synchronization and desynchronization in a neural network

机译:混沌迭代是神经网络中同步和失步之间不规则变化的一种机制

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摘要

We investigate the dynamic character of a network of electrotonically coupled cells consisting of class I point neurons, in terms of a finite dimensional dynamical system. We classify a subclass of class I point neurons, called class I* point neurons. Based on this classification, we use a reduced Hindmarsh-Rose (H-R) model, which consists of two dynamical variables, to construct a network model consisting of electrotonically coupled H-R neurons. Although biologically simple, the system is sufficient to extract the essence of the complex dynamics, which the system may yield under certain physiological conditions. The network model produces a transitory behavior as well as a periodic motion and spatio-temporal chaos. The transitory dynamics that the network model exhibits is shown numerically to be chaotic itinerancy. The transitions appear between various metachronal waves and all-synchronization states. The network model shows that this transitory dynamics can be viewed as a chaotic switch between synchronized and desynchronized states. Despite the use of spatially discrete point neurons as basic elements of the network, the overall dynamics exhibits scale-free activity including various scales of spatio-temporal patterns.
机译:我们研究了有限元动力学系统中由I类点神经元组成的电声耦合细胞网络的动态特性。我们将I类点神经元的一个子类分类为I *类点神经元。基于此分类,我们使用简化的Hindmarsh-Rose(H-R)模型(包含两个动态变量)来构建由电声耦合的H-R神经元组成的网络模型。尽管生物学上简单,但是该系统足以提取复杂动力学的本质,而该复杂动力学可以在某些生理条件下产生。网络模型会产生短暂的行为,以及周期性运动和时空混乱。网络模型展现的瞬态动力学数值显示为混沌迭代。过渡出现在各种超同步波和全同步状态之间。网络模型表明,这种瞬态动力学可以看作是同步状态和非同步状态之间的混沌切换。尽管使用了空间离散的点神经元作为网络的基本元素,但总体动力学仍显示出无标度的活动,包括各种时空模式的标度。

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