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首页> 外文期刊>Neural Networks and Learning Systems, IEEE Transactions on >Long-Tailed Characteristic of Spiking Pattern Alternation Induced by Log-Normal Excitatory Synaptic Distribution
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Long-Tailed Characteristic of Spiking Pattern Alternation Induced by Log-Normal Excitatory Synaptic Distribution

机译：对数正常兴奋突触分布引起的尖刺模式交替的长尾特征

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Studies of structural connectivity at the synaptic level show that in synaptic connections of the cerebral cortex, the excitatory postsynaptic potential (EPSP) in most synapses exhibits sub-mV values, while a small number of synapses exhibit large EPSPs (greater than or similar to 1.0 [mV]). This means that the distribution of EPSP fits a log-normal distribution. While not restricting structural connectivity, skewed and long-tailed distributions have been widely observed in neural activities, such as the occurrences of spiking rates and the size of a synchronously spiking population. Many studies have been modeled this long-tailed EPSP neural activity distribution; however, its causal factors remain controversial. This study focused on the long-tailed EPSP distributions and interlateral synaptic connections primarily observed in the cortical network structures, thereby having constructed a spiking neural network consistent with these features. Especially, we constructed two coupled modules of spiking neural networks with excitatory and inhibitory neural populations with a log-normal EPSP distribution. We evaluated the spiking activities for different input frequencies and with/without strong synaptic connections. These coupled modules exhibited intermittent intermodule-alternative behavior, given moderate input frequency and the existence of strong synaptic and intermodule connections. Moreover, the power analysis, multiscale entropy analysis, and surrogate data analysis revealed that the long-tailed EPSP distribution and intermodule connections enhanced the complexity of spiking activity at large temporal scales and induced nonlinear dynamics and neural activity that followed the long-tailed distribution.
机译：在突触水平的结构连接中的研究表明，在大多数突触的脑皮层的突触联系中，大多数突触中的兴奋性突触潜力（EPSP）呈现亚MV值，而少数突触表现出大型EPSPS（大于或类似于1.0 [mv]）。这意味着EPSP的分布适合对数正态分布。虽然没有限制结构连通性，在神经活动中广泛观察到偏斜和长尾的分布，例如尖峰率的发生和同步尖峰人口的尺寸。许多研究已被建模这种长尾EPSP神经活动分布;然而，其因果因素仍然存在争议。该研究专注于在皮质网络结构中主要观察到的长尾EPSP分布和跨隔音突触连接，从而构建了与这些特征一致的尖峰神经网络。特别是，我们构建了具有兴奋性和抑制性神经群的尖刺神经网络的两个耦合模块，具有逻辑正常的EPSP分布。我们评估了不同输入频率的尖峰活动，并与/没有强大的突触连接。这些耦合模块表现出间间的间显示替代行为，给定中等输入频率和强突触和同组电连接的存在。此外，功率分析，多尺度熵分析和代理数据分析显示，长尾EPSP分布和细胞间连接增强了大型时间尺度下尖峰活动的复杂性，并且诱导了长尾分布的非线性动力学和神经活动。

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