From space to time: Spatial inhomogeneities lead to the emergence of spatio-temporal activity sequences in spiking neuronal networks
From space to time: Spatial inhomogeneities lead to the emergence of spatio-temporal activity sequences in spiking neuronal networks
复制标题
从空间到时间：空间不均匀性导致尖峰神经元网络中时空活动序列的出现
DOI：
10.1101/428649
复制
发表时间：
2018
期刊：
影响因子：
--
通讯作者：
Arvind Kumar
中科院分区：
文献类型：
--
作者：
Sebastian Spreizer;A. Aertsen;Arvind Kumar
神经元活动的时空序列在各种任务中的许多大脑区域被观察到，并被认为构成了任何有意义的行为的基础。神经网络可以产生时空活动序列的机制仍然不清楚。现有的模型在生物学上是站不住脚的，因为它们需要在随机网络中手动嵌入前馈网络，或者需要有监督的学习来训练网络的连通性以生成序列。在这里，我们提出了一个生物学上看似合理的生成规则，以在具有距离相关连接性的尖峰神经元网络模型中创建时空活动序列。我们证明了时空活动序列的出现需要：(1)单个神经元优先将其一小部分轴突投射到特定方向，(2)相邻神经元的优先投射方向相似。因此，神经元组的各向异性但相关的连接性足以在其他随机的神经网络模型中产生时空活动序列。
Spatio-temporal sequences of neuronal activity are observed in many brain regions in a variety of tasks and are thought to form the basis of any meaningful behavior. Mechanisms by which a neuronal network can generate spatio-temporal activity sequences have remained obscure. Existing models are biologically untenable because they require manual embedding of a feedforward network within a random network or supervised learning to train the connectivity of a network to generate sequences. Here, we propose a biologically plausible, generative rule to create spatio-temporal activity sequences in a network model of spiking neurons with distance dependent connectivity. We show that the emergence of spatio-temporal activity sequences requires: (1) individual neurons preferentially project a small fraction of their axons in a specific direction, and (2) the preferential projection direction of neighboring neurons is similar. Thus, an anisotropic but correlated connectivity of neuron groups suffices to generate spatio-temporal activity sequences in an otherwise random neuronal network model.
DOI：
10.1126/science.aat4422
发表时间：
2018-06-29
期刊：
Science (New York, N.Y.)
影响因子：
--
作者：
Patriarchi T;Cho JR;Merten K;Howe MW;Marley A;Xiong WH;Folk RW;Broussard GJ;Liang R;Jang MJ;Zhong H;Dombeck D;von Zastrow M;Nimmerjahn A;Gradinaru V;Williams JT;Tian L
通讯作者：
Tian L