标题： 神经系统中共振的出现：阈值适应与短期突触可塑性的相互作用 显示英文标题

标题： Emergence of resonances in neural systems: the interplay between threshold adaptation and short-term synaptic plasticity

摘要： 在本工作中，我们研究了在存在一定水平的噪声背景神经活动的情况下，脉冲神经元对弱刺激的检测。 我们的研究集中在现实的假设上，即网络中的突触表现出依赖于活动的过程，如短期突触抑制和增强。 采用平均场技术以及数值模拟，我们发现存在两个可能的噪声水平可以优化信号传输。 这一新发现与经典的随机共振理论相矛盾，该理论只能预测一个最优的噪声水平。 我们发现，神经元阈值的非线性动力学与依赖于活动的突触机制之间的复杂相互作用是这种新现象的原因。 我们的结果通过采用更现实的FitzHugh-Nagumo神经元模型得到了验证，该模型表现出阈值变化，同时通过考虑更现实的突触模型也得到了验证。 我们用最近的人类触觉眨眼反射中的随机共振实验数据支持我们的发现。 显示英文摘要

摘要： In this work we study the detection of weak stimuli by spiking neurons in the presence of certain level of noisy background neural activity. Our study has focused in the realistic assumption that the synapses in the network present activity-dependent processes, such as short-term synaptic depression and facilitation. Employing mean-field techniques as well as numerical simulations, we found that there are two possible noise levels which optimize signal transmission. This new finding is in contrast with the classical theory of stochastic resonance which is able to predict only one optimal level of noise. We found that the complex interplay between the nonlinear dynamics of the neuron threshold and the activity-dependent synaptic mechanisms is responsible for this new phenomenology. Our results are confirmed by employing a more realistic FitzHugh-Nagumo neuron model, which displays threshold variability, as well as by considering more realistic synaptic models. We support our findings with recent experimental data of stochastic resonance in the human tactile blink reflex.