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柱状分组在具有距离相关时滞的神经元网络中保持同步。

Columnar grouping preserves synchronization in neuronal networks with distance-dependent time delays.

机构信息

Department of Physics, Drexel University, 3141 Chestnut Street, Philadelphia, Pennsylvania 19104, United States.

出版信息

Phys Rev E. 2020 Feb;101(2-1):022408. doi: 10.1103/PhysRevE.101.022408.

Abstract

Neuronal connectivity at the cellular level in the cerebral cortex is far from random, with characteristics that point to a hierarchical design with intricately connected neuronal clusters. Here we investigate computationally the effects of varying neuronal cluster connectivity on network synchronization for two different spatial distributions of clusters: one where clusters are arranged in columns in a grid and the other where neurons from different clusters are spatially intermixed. We characterize each case by measuring the degree of neuronal spiking synchrony as a function of the number of connections per neuron and the degree of intercluster connectivity. We find that in both cases as the number of connections per neuron increases, there is an asynchronous to synchronous transition dependent only on intrinsic parameters of the biophysical model. We also observe in both cases that with very low intercluster connectivity clusters have independent firing dynamics yielding a low degree of synchrony. More importantly, we find that for a high number of connections per neuron but intermediate intercluster connectivity, the two spatial distributions of clusters differ in their response where the clusters in a grid have a higher degree of synchrony than the clusters that are intermixed.

摘要

大脑皮层细胞水平的神经元连接远非随机的,其特征表明存在具有错综复杂连接的神经元簇的层次设计。在这里,我们通过计算研究了改变神经元簇连接对两种不同簇空间分布的网络同步的影响:一种是簇在网格中排列成列,另一种是来自不同簇的神经元在空间上混合。我们通过测量神经元尖峰同步的程度来表征每种情况,该程度是作为神经元每个神经元的连接数和簇间连接程度的函数。我们发现,在这两种情况下,随着神经元每个神经元的连接数的增加,都会出现仅依赖于生物物理模型内在参数的异步到同步的转变。我们还在这两种情况下观察到,簇间连接非常低时,簇具有独立的发射动力学,导致同步程度非常低。更重要的是,我们发现对于每个神经元的连接数非常高但簇间连接中等的情况,网格中的簇具有比混合的簇更高的同步程度。

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