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Interplay between Graph Topology and Correlations of Third Order in Spiking Neuronal Networks

机译:尖峰神经网络中图拓扑与三阶相关性之间的相互作用

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Author Summary Many biological phenomena can be viewed as dynamical processes on a graph. Understanding coordinated activity of nodes in such a network is of some importance, as it helps to characterize the behavior of the complex system. Of course, the topology of a network plays a pivotal role in determining the level of coordination among its different vertices. In particular, correlations between triplets of events (here: action potentials generated by neurons) have recently garnered some interest in the theoretical neuroscience community. In this paper, we present a decomposition of an average measure of third-order coordinated activity of neurons in a spiking neuronal network in terms of the relevant topological motifs present in the underlying graph. We study different network topologies and show, in particular, that the presence of certain tree motifs in the synaptic connectivity graph greatly affects the strength of third-order correlations between spike trains of different neurons.
机译:作者摘要许多生物现象都可以看作是图形上的动力学过程。了解这样的网络中节点的协调活动非常重要,因为它有助于表征复杂系统的行为。当然,网络的拓扑在确定其不同顶点之间的协调级别方面起着关键作用。特别是,事件三胞胎之间的相关性(在这里:神经元产生的动作电位)最近在理论神经科学界引起了一些兴趣。在本文中,我们根据底层图形中存在的相关拓扑图案,对尖峰神经元网络中神经元的三阶协调活动的平均度量进行了分解。我们研究了不同的网络拓扑,并特别表明,突触连接图中某些树形图案的存在极大地影响了不同神经元的尖峰序列之间的三阶相关强度。

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