Masuda Naoki, Aihara Kazuyuki
Faculty of Engineering, Yokohama National University, Yokohama, Japan.
Biol Cybern. 2004 Apr;90(4):302-9. doi: 10.1007/s00422-004-0471-9. Epub 2004 Apr 8.
Synchronous firing of neurons is thought to play important functional roles such as feature binding and switching of cognitive states. Although synchronization has mainly been investigated so far using model neurons with simple connection topology, real neural networks have more complex structures. Here we examine the behavior of pulse-coupled leaky integrate-and-fire neurons with various network structures. We first show that the dispersion of the number of connections for neurons influences dynamical behavior even if other major topological statistics are kept fixed. The rewiring probability parameter representing the randomness of networks bridges two spatially opposite frameworks: precise local synchrony and rough global synchrony. Finally, cooperation of the global connections and the local clustering property, which is prominent in small-world networks, forces synchrony of distant neuronal groups receiving coherent inputs.
神经元的同步放电被认为在诸如特征绑定和认知状态切换等重要功能中发挥作用。尽管到目前为止，同步主要是使用具有简单连接拓扑的模型神经元进行研究的，但真实的神经网络具有更复杂的结构。在这里，我们研究了具有各种网络结构的脉冲耦合漏电积分发放神经元的行为。我们首先表明，即使其他主要拓扑统计量保持不变，神经元连接数量的分散也会影响动力学行为。表示网络随机性的重新布线概率参数连接了两个空间上相反的框架：精确的局部同步和粗糙的全局同步。最后，全局连接和局部聚类特性（在小世界网络中很突出）的协同作用促使接收相干输入的远距离神经元群体同步。
