Bistability within a small neural circuit can arise through an appropriate strength of excitatory recurrent feedback. The stability of a state of neural activity, measured by the mean dwelling time before a noise-induced transition to another state, depends on the neural firing-rate curves, the net strength of excitatory feedback, the statistics of spike times, and increases exponentially with the number of equivalent neurons in the circuit. Here, we show that such stability is greatly enhanced by synaptic facilitation and reduced by synaptic depression. We take into account the alteration in times of synaptic vesicle release, by calculating distributions of inter-release intervals of a synapse, which differ from the distribution of its incoming interspike intervals when the synapse is dynamic. In particular, release intervals produced by a Poisson spike train have a coefficient of variation greater than one when synapses are probabilistic and facilitating, whereas the coefficient of variation is less than one when synapses are depressing. However, in spite of the increased variability in postsynaptic input produced by facilitating synapses, their dominant effect is reduced synaptic efficacy at low input rates compared to high rates, which increases the curvature of neural input-output functions, leading to wider regions of bistability in parameter space and enhanced lifetimes of memory states. Our results are based on analytic methods with approximate formulae and bolstered by simulations of both Poisson processes and of circuits of noisy spiking model neurons.

中文翻译：

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通过随机促进突触稳定记忆状态。

小神经回路内的双稳态可以通过适当强度的兴奋性循环反馈产生。神经活动状态的稳定性，由噪声引起的过渡到另一种状态之前的平均停留时间来衡量，取决于神经放电率曲线、兴奋性反馈的净强度、尖峰时间的统计数据，并呈指数增长与电路中等效神经元的数量。在这里，我们表明这种稳定性通过突触促进大大增强，并通过突触抑制降低。我们通过计算突触间释放间隔的分布来考虑突触小泡释放时间的变化，当突触是动态的时，该间隔与传入的突触间隔分布不同。特别是，当突触是概率性和促进性时，泊松脉冲序列产生的释放间隔的变异系数大于 1，而当突触是抑制性的时，变异系数小于 1。然而，尽管促进突触产生的突触后输入的变异性增加，但与高速率相比，它们的主要影响是低输入速率下的突触功效降低，这增加了神经输入-输出函数的曲率，导致更宽的双稳态区域参数空间和内存状态的增强生命周期。我们的结果基于具有近似公式的分析方法，并通过泊松过程和噪声尖峰模型神经元电路的模拟得到支持。