Friedrich Johannes, Kinzel Wolfgang
Institute of Theoretical Physics and Astrophysics, University of Würzburg, Am Hubland, 97074 Würzburg, Germany.
J Comput Neurosci. 2009 Aug;27(1):65-80. doi: 10.1007/s10827-008-0127-1. Epub 2008 Dec 10.
The influence of unreliable synapses on the dynamic properties of a neural network is investigated for a homogeneous integrate-and-fire network with delayed inhibitory synapses. Numerical and analytical calculations show that the network relaxes to a state with dynamic clusters of identical size which permanently exchange neurons. We present analytical results for the number of clusters and their distribution of firing times which are determined by the synaptic properties. The number of possible configurations increases exponentially with network size. In addition to states with a maximal number of clusters, metastable ones with a smaller number of clusters survive for an exponentially large time scale. An externally excited cluster survives for some time, too, thus clusters may encode information.
针对具有延迟抑制性突触的均匀积分发放网络，研究了不可靠突触对神经网络动态特性的影响。数值计算和解析计算表明，该网络会弛豫到一种状态，其中具有相同大小的动态簇会不断交换神经元。我们给出了簇的数量及其发放时间分布的解析结果，这些结果由突触特性决定。可能配置的数量随网络规模呈指数增长。除了具有最大簇数量的状态外，具有较少簇数量的亚稳态会在指数级大的时间尺度上持续存在。一个外部激发的簇也会持续一段时间，因此簇可能编码信息。
