Guiding Synchrony through Random Networks
Guiding Synchrony through Random Networks
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DOI：
10.1103/physrevx.2.041016
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发表时间：
2012-12-13
影响因子：
12.5
通讯作者：
Memmesheimer, Raoul-Martin
中科院分区：
文献类型：
--
作者：
Jahnke, Sven;Timme, Marc;Memmesheimer, Raoul-Martin
稀疏随机网络包含可被视为稀释前馈网络的结构。皮质电路的建模表明，前馈结构，如果强烈明显的嵌入随机网络相比，使可靠的信号传输传播本地化（子网）同步。然而，这种假设的突出性在局部皮层回路中没有实验观察到。在这里，我们表明，非线性树突的相互作用，在最近的单神经元实验中发现，自然使引导同步传播已经在随机循环神经网络，表现出轻度增强，生物学上合理的子结构。DOI：10.1103/PhysRevX.2.041016
Sparse random networks contain structures that can be considered as diluted feed-forward networks. Modeling of cortical circuits has shown that feed-forward structures, if strongly pronounced compared to the embedding random network, enable reliable signal transmission by propagating localized (subnetwork) synchrony. This assumed prominence, however, is not experimentally observed in local cortical circuits. Here, we show that nonlinear dendritic interactions, as discovered in recent single-neuron experiments, naturally enable guided synchrony propagation already in random recurrent neural networks that exhibit mildly enhanced, biologically plausible substructures. DOI: 10.1103/PhysRevX.2.041016