Delay-Induced Multistability and Loop Formation in Neuronal Networks with Spike-Timing-Dependent Plasticity
Delay-Induced Multistability and Loop Formation in Neuronal Networks with Spike-Timing-Dependent Plasticity
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DOI：
10.1038/s41598-018-30565-9
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发表时间：
2018-08-13
影响因子：
4.6
通讯作者：
Tass, Peter A.
中科院分区：
文献类型：
--
作者：
Asl, Mojtaba Madadi;Valizadeh, Alireza;Tass, Peter A.
棘波时序依赖可塑性(STDP)根据突触前和突触后棘波对的精确时序调节突触强度。理论和计算研究表明，STDP可能有助于在可塑性神经元群体中出现各种结构和动力学状态。在这篇手稿中，我们表明，通过在振荡神经元的递归网络中加入树突和轴突传播延迟，渐近连通性表现出多重稳定性，其中不同的结构出现取决于突触强度的初始分布。特别是，我们发现，突触权重初始分布的标准差除了其平均值外，还决定了突触结构连通性的主要性质，如平均最终突触权重、两个神经元环的数量和最终结构的对称性。我们还表明，神经元的放电速率影响网络的演化，并且在较高的放电速率下出现更对称的突触配置。我们证明了基于双神经元框架的网络结果的合理性，并展示了结果如何转化为大型递归网络
Spike-timing-dependent plasticity (STDP) adjusts synaptic strengths according to the precise timing of pre- and postsynaptic spike pairs. Theoretical and computational studies have revealed that STDP may contribute to the emergence of a variety of structural and dynamical states in plastic neuronal populations. In this manuscript, we show that by incorporating dendritic and axonal propagation delays in recurrent networks of oscillatory neurons, the asymptotic connectivity displays multistability, where different structures emerge depending on the initial distribution of the synaptic strengths. In particular, we show that the standard deviation of the initial distribution of synaptic weights, besides its mean, determines the main properties of the emergent structural connectivity such as the mean final synaptic weight, the number of two-neuron loops and the symmetry of the final structure. We also show that the firing rates of the neurons affect the evolution of the network, and a more symmetric configuration of the synapses emerges at higher firing rates. We justify the network results based on a two-neuron framework and show how the results translate to large recurrent networks