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去极化阻滞对兴奋性和抑制性神经元网络中癫痫样活动的影响。

The influence of depolarization block on seizure-like activity in networks of excitatory and inhibitory neurons.

作者信息

Kim Christopher M, Nykamp Duane Q

机构信息

School of Mathematics, University of Minnesota, Minneapolis, MN, USA.

Laboratory of Biological Modeling, NIDDK, National Institute of Health, Bethesda, MD, USA.

出版信息

J Comput Neurosci. 2017 Aug;43(1):65-79. doi: 10.1007/s10827-017-0647-7. Epub 2017 May 20.

Abstract

The inhibitory restraint necessary to suppress aberrant activity can fail when inhibitory neurons cease to generate action potentials as they enter depolarization block. We investigate possible bifurcation structures that arise at the onset of seizure-like activity resulting from depolarization block in inhibitory neurons. Networks of conductance-based excitatory and inhibitory neurons are simulated to characterize different types of transitions to the seizure state, and a mean field model is developed to verify the generality of the observed phenomena of excitatory-inhibitory dynamics. Specifically, the inhibitory population's activation function in the Wilson-Cowan model is modified to be non-monotonic to reflect that inhibitory neurons enter depolarization block given strong input. We find that a physiological state and a seizure state can coexist, where the seizure state is characterized by high excitatory and low inhibitory firing rate. Bifurcation analysis of the mean field model reveals that a transition to the seizure state may occur via a saddle-node bifurcation or a homoclinic bifurcation. We explain the hysteresis observed in network simulations using these two bifurcation types. We also demonstrate that extracellular potassium concentration affects the depolarization block threshold; the consequent changes in bifurcation structure enable the network to produce the tonic to clonic phase transition observed in biological epileptic networks.

摘要

当抑制性神经元进入去极化阻滞状态而停止产生动作电位时,抑制异常活动所需的抑制性约束可能会失效。我们研究了抑制性神经元去极化阻滞导致癫痫样活动开始时可能出现的分岔结构。基于电导的兴奋性和抑制性神经元网络被模拟以表征向癫痫状态的不同类型转变,并且开发了一个平均场模型来验证所观察到的兴奋 - 抑制动力学现象的普遍性。具体而言,威尔逊 - 考恩模型中抑制性群体的激活函数被修改为非单调的,以反映抑制性神经元在强输入下进入去极化阻滞状态。我们发现生理状态和癫痫状态可以共存,其中癫痫状态的特征是高兴奋性和低抑制性放电率。平均场模型的分岔分析表明,向癫痫状态的转变可能通过鞍结分岔或同宿分岔发生。我们使用这两种分岔类型解释了在网络模拟中观察到的滞后现象。我们还证明细胞外钾浓度会影响去极化阻滞阈值;由此导致的分岔结构变化使网络能够产生在生物癫痫网络中观察到的强直 - 阵挛相转变。

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