摘要翻译：
我们表明，如果突触效应遵循现实动力学，一个尖峰神经元网络表现出强大的自组织临界性。推导了平均耦合强度和尖峰间间隔的解析表达式，证明了具有动态突触的网络在较宽的相互作用参数范围内表现出临界雪崩动力学。我们证明了在热力学极限下，对于所有足够大的耦合参数，网络变得至关重要。因此，我们解释了皮层神经元表现出雪崩活动的实验观察，放电事件的总强度呈幂律分布。
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英文标题：
《Dynamical synapses causing self-organized criticality in neural networks》
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作者：
Anna Levina, J. Michael Herrmann, Theo Geisel
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最新提交年份：
2007
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分类信息：

一级分类：Physics        物理学
二级分类：Statistical Mechanics        统计力学
分类描述：Phase transitions, thermodynamics, field theory, non-equilibrium phenomena, renormalization group and scaling, integrable models, turbulence
相变，热力学，场论，非平衡现象，重整化群和标度，可积模型，湍流
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一级分类：Physics        物理学
二级分类：Disordered Systems and Neural Networks        无序系统与神经网络
分类描述：Glasses and spin glasses; properties of random, aperiodic and quasiperiodic systems; transport in disordered media; localization; phenomena mediated by defects and disorder; neural networks
眼镜和旋转眼镜；随机、非周期和准周期系统的性质；无序介质中的传输；本地化；由缺陷和无序介导的现象；神经网络
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一级分类：Quantitative Biology        数量生物学
二级分类：Neurons and Cognition        神经元与认知
分类描述：Synapse, cortex, neuronal dynamics, neural network, sensorimotor control, behavior, attention
突触，皮层，神经元动力学，神经网络，感觉运动控制，行为，注意
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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.
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PDF链接：
https://arxiv.org/pdf/712.1003