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Robustness and regularity of oscillations in neuronal populations

机译:神经元群体振荡的鲁棒性和规律性

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We study a biologically plausible but computationally simplified integrate-and-fire neuronal model. Oscillatory activity is analyzed in the networks with and without self-connections. We perform a detailed scan of four major parameters that represent the properties of neurons and synapses: connection ratio, connection strengths, post-synaptic potential decay rate and soma’s potential decay rate. It is observed that networks with different properties exhibit different periods and different patterns of synchrony. We find that generally these oscillations are robust against changes of parameters, meanwhile we also locate the parametric boundaries where oscillations break down.
机译:我们研究了生物学上可行的但计算简化的集成并发射神经元模型。在有或没有自连接的网络中分析振荡活动。我们对代表神经元和突触特性的四个主要参数进行了详细的扫描:连接比率,连接强度,突触后电位衰减率和躯体电位衰减率。可以看出,具有不同属性的网络表现出不同的周期和不同的同步模式。我们发现,通常这些振荡对参数的变化具有鲁棒性,与此同时,我们还确定了发生振荡的参数边界。

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