标题： 神经网络活动的抑制反馈去相关性 显示英文标题

标题： Decorrelation of neural-network activity by inhibitory feedback

摘要： 突触发放序列集合中的相关性会严重损害其时空结构对信息的编码。 有限神经网络中相关性的不可避免的来源是成对神经元的共同突触前输入。 最近的理论和实验研究表明，循环神经网络中的尖峰相关性明显小于根据共享突触前输入量所预期的值。 通过一个线性网络模型和漏电整合-发放神经元网络的模拟，我们表明共享输入相关性被抑制反馈有效地抑制。 为了阐明反馈的影响，我们比较了完整循环网络以及反馈通道统计特性被扰动的系统的响应。 抑制反馈可以同时观察到在纯粹抑制性和兴奋性-抑制性网络中尖峰序列相关性和群体速率波动的抑制。 该效应可以通过线性理论完全理解，并且在群体平均活动的宏观层面上已经明显。 在微观层面上，共享输入相关性被尖峰序列相关性所抑制：在纯粹抑制性网络中，它们被负的尖峰序列相关性抵消。 在兴奋性-抑制性网络中，尖峰序列相关性通常是正的。 在这里，输入相关性的抑制不是由于兴奋性（E）和抑制性（I）神经元之间相关性的存在，而是由于三种可能配对（EE、EI、II）之间相关性的特定结构所致。 显示英文摘要

摘要： Correlations in spike-train ensembles can seriously impair the encoding of information by their spatio-temporal structure. An inevitable source of correlation in finite neural networks is common presynaptic input to pairs of neurons. Recent theoretical and experimental studies demonstrate that spike correlations in recurrent neural networks are considerably smaller than expected based on the amount of shared presynaptic input. By means of a linear network model and simulations of networks of leaky integrate-and-fire neurons, we show that shared-input correlations are efficiently suppressed by inhibitory feedback. To elucidate the effect of feedback, we compare the responses of the intact recurrent network and systems where the statistics of the feedback channel is perturbed. The suppression of spike-train correlations and population-rate fluctuations by inhibitory feedback can be observed both in purely inhibitory and in excitatory-inhibitory networks. The effect is fully understood by a linear theory and becomes already apparent at the macroscopic level of the population averaged activity. At the microscopic level, shared-input correlations are suppressed by spike-train correlations: In purely inhibitory networks, they are canceled by negative spike-train correlations. In excitatory-inhibitory networks, spike-train correlations are typically positive. Here, the suppression of input correlations is not a result of the mere existence of correlations between excitatory (E) and inhibitory (I) neurons, but a consequence of a particular structure of correlations among the three possible pairings (EE, EI, II).