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首页> 外文期刊>Physica, A. Statistical mechanics and its applications >Computational modeling of the dependence of kindling rate on network properties
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Computational modeling of the dependence of kindling rate on network properties

机译:点燃率对网络特性的依赖性的计算模型

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The dependence of the rate of kindling on network properties, such as the number of neurons, number of stored memories, and the number of neurons used to store each memory, is studied through computer simulations of an appropriate neural network model for kindling of focal epilepsy. Simulations are performed for models of both chemical and electrical kindling. Larger and more complex networks are found to take longer time to kindle, as observed in experiments. The nature of the dependence of the kindling rate on network properties is somewhat different between the two types of kindling. A simple analysis of the process of chemical kindling is presented, which provides a semi-quantitative explanation of the behavior observed in our simulations. This analysis also shows that our main conclusions about the dependence of the kindling rate on the size and complexity of the network are independent of some of the assumptions made in our modeling. (c) 2005 Elsevier B.V. All rights reserved.
机译:通过计算机模拟局灶性癫痫发作的适当神经网络模型,研究了点燃率对网络属性(如神经元数量,存储的内存数量以及用于存储每个内存的神经元数量)的依赖性。 。对化学和电气点燃模型进行仿真。实验中发现,更大,更复杂的网络点燃时间更长。两种类型的点燃之间,点燃率对网络属性的依赖性有所不同。提出了对化学点燃过程的简单分析,它提供了对我们模拟中观察到的行为的半定量解释。该分析还表明,我们关于点燃率对网络大小和复杂性的依赖性的主要结论与我们在建模中所做的某些假设无关。 (c)2005 Elsevier B.V.保留所有权利。

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