Dynamical synapses causing self-organized criticality in neural networks
Dynamical synapses causing self-organized criticality in neural networks
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DOI：
10.1038/nphys758
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发表时间：
2007-12-01
期刊：
影响因子：
19.6
通讯作者：
Geisel, T.
中科院分区：
文献类型：
--
作者：
Levina, A.;Herrmann, J. M.;Geisel, T.
自组织临界性（1）是描述自然系统复杂性出现的关键概念之一。这个概念断言，系统自组织成一个临界状态，其中系统的可观测量是根据幂律分布。自组织临界动力学的突出例子包括颗粒介质的堆积（2），板块构造（3）和粘滑运动（4）。批判性行为已被证明可以带来最佳的计算能力（5），最佳的传输（6），信息存储（7）和对感官刺激的敏感性（8-10）。在神经元系统中，临界雪崩的存在被预测（11），后来被实验观察到（6，12，13）。然而，尽管在实验中发现了一般的临界雪崩，但在参考文献11的模型中，只有当参数集被外部微调到临界过渡态时，它们才会出现。在这里，我们通过分析和数字证明，通过假设（生物学上更现实）在尖峰神经网络中的动态突触（14），如果神经递质的总资源足够大，神经元雪崩从一个例外的现象变成一个典型的和强大的自组织临界行为。
Self-organized criticality(1) is one of the key concepts to describe the emergence of complexity in natural systems. The concept asserts that a system self-organizes into a critical state where system observables are distributed according to a power law. Prominent examples of self-organized critical dynamics include piling of granular media(2), plate tectonics(3) and stick-slip motion(4). Critical behaviour has been shown to bring about optimal computational capabilities(5), optimal transmission(6), storage of information(7) and sensitivity to sensory stimuli(8-10). In neuronal systems, the existence of critical avalanches was predicted(11) and later observed experimentally(6,12,13). However, whereas in the experiments generic critical avalanches were found, in the model of ref. 11 they only show up if the set of parameters is fine-tuned externally to a critical transition state. Here, we demonstrate analytically and numerically that by assuming (biologically more realistic) dynamical synapses(14) in a spiking neural network, the neuronal avalanches turn from an exceptional phenomenon into a typical and robust self-organized critical behaviour, if the total resources of neurotransmitter are sufficiently large.