Variability v.s. synchronicity of neuronal activity in local cortical network models with different wiring topologies
Variability v.s. synchronicity of neuronal activity in local cortical network models with different wiring topologies
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DOI：
10.1007/s10827-007-0030-1
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发表时间：
2007-10-01
影响因子：
1.2
通讯作者：
Fukai, Tomoki
中科院分区：
文献类型：
--
作者：
Kitano, Katsunori;Fukai, Tomoki
生物神经元网络的动力学行为在很大程度上取决于神经元之间突触连接的空间模式。虽然神经元网络动力学已经被广泛研究了简单的布线模式，如所有对所有或随机突触连接，但对具有更复杂布线拓扑结构的网络的活动知之甚少。在这里，我们研究了不同的布线拓扑结构可能会影响神经元网络的响应特性，注意不规则的尖峰放电，这是已知的在体内皮层神经元的特性，和尖峰同步性。我们构建了一个真实神经元的递归网络模型，并系统地重新连接递归突触以改变网络拓扑，从局部规则和“小世界”网络拓扑到分布式随机网络拓扑。规则和小世界布线模式大大增加了不规则性或输出尖峰序列的变异系数（Cv），而这种增加是小的随机连接模式。对于给定的强度的复发性突触，放电不规则性表现出单调的减少，从规则的随机网络拓扑结构。相比之下，任意神经元对之间的尖峰相干性表现出对拓扑布线模式的非单调依赖性。更准确地说，最大化尖峰相干性的布线模式随着复发性突触的强度而变化。在一定的突触强度范围内，小世界网络拓扑结构中的锋电位一致性最大，并且这种连接中引入的长程连接适度地改变了锋电位同步性对突触强度的依赖性。然而，这种网络拓扑结构的影响在网络活动的其他属性上并不特别。
Dynamical behavior of a biological neuronal network depends significantly on the spatial pattern of synaptic connections among neurons. While neuronal network dynamics has extensively been studied with simple wiring patterns, such as all-to-all or random synaptic connections, not much is known about the activity of networks with more complicated wiring topologies. Here, we examined how different wiring topologies may influence the response properties of neuronal networks, paying attention to irregular spike firing, which is known as a characteristic of in vivo cortical neurons, and spike synchronicity. We constructed a recurrent network model of realistic neurons and systematically rewired the recurrent synapses to change the network topology, from a localized regular and a "small-world" network topology to a distributed random network topology. Regular and small-world wiring patterns greatly increased the irregularity or the coefficient of variation (Cv) of output spike trains, whereas such an increase was small in random connectivity patterns. For given strength of recurrent synapses, the firing irregularity exhibited monotonous decreases from the regular to the random network topology. By contrast, the spike coherence between an arbitrary neuron pair exhibited a non-monotonous dependence on the topological wiring pattern. More precisely, the wiring pattern to maximize the spike coherence varied with the strength of recurrent synapses. In a certain range of the synaptic strength, the spike coherence was maximal in the small-world network topology, and the long-range connections introduced in this wiring changed the dependence of spike synchrony on the synaptic strength moderately. However, the effects of this network topology were not really special in other properties of network activity.