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arXiv 0712.1003cond-mat.stat-mechcond-mat.dis-nnq-bio.NC
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神经网络中引起自组织临界性的动态突触

Dynamical synapses causing self-organized criticality in neural networks

Anna Levina, J. Michael Herrmann, Theo Geisel

摘要:

我们表明,网络的尖峰神经元表现出强大的自组织临界性,如果突触的功效遵循现实的动态。推导出平均耦合强度和峰间间隔的解析表达式,我们证明了动态突触的网络具有广泛的相互作用参数的临界雪崩动力学。我们证明,在临界极限的网络成为关键的所有足够大的耦合参数。因此,我们解释了实验观察中,皮层神经元显示雪崩活动的发射事件的总强度分布为幂律。

英文摘要:

We show that a network of spiking neurons exhibits robust self-organized criticality if the synaptic efficacies follow realistic dynamics. Deriving analytical expressions for the average coupling strengths and inter-spike intervals, we demonstrate that networks with dynamical synapses exhibit critical avalanche dynamics for a wide range of interaction parameters. We prove that in the thermodynamical limit the network becomes critical for all large enough coupling parameters. We thereby explain experimental observations in which cortical neurons show avalanche activity with the total intensity of firing events being distributed as a power-law.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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