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A reduction for spiking integrate-and-fire network dynamics ranging from homogeneity to synchrony

机译:从均匀性到同步性的尖峰集成和解雇网络动态的减少

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In this paper we provide a general methodology for systematically reducing the dynamics of a class of integrate-and-fire networks down to an augmented 4-dimensional system of ordinary-differential-equations. The class of integrate-and-fire networks we focus on are homogeneously-structured, strongly coupled, and fluctuation-driven. Our reduction succeeds where most current firing-rate and population-dynamics models fail because we account for the emergence of 'multiple-firing-events' involving the semi-synchronous firing of many neurons. These multiple-firing-events are largely responsible for the fluctuations generated by the network and, as a result, our reduction faithfully describes many dynamic regimes ranging from homogeneous to synchronous. Our reduction is based on first principles, and provides an ana-lyzable link between the integrate-and-fire network parameters and the relatively low-dimensional dynamics underlying the 4-dimensional augmented ODE.
机译:在本文中,我们提供了一种通用方法,可以系统地将一类集成射击网络的动力学降低为一个常微分方程的增强4维系统。我们关注的集成和解雇网络类别是同构结构,强耦合和波动驱动的。在大多数当前激发速率和种群动力学模型失败的情况下,我们的降低成功了,因为我们考虑了涉及多个神经元半同步激发的“多次激发事件”的出现。这些多次触发事件主要是由网络产生的波动所致,因此,我们的还原真实地描述了从同构到同步的许多动态状态。我们的减少基于第一原理,并提供了集成和发射网络参数与4维增强ODE底层的相对低维动力学之间的可分析链接。

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