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神经脉冲序列之间的相关性随放电率增加。

Correlation between neural spike trains increases with firing rate.

作者信息

de la Rocha Jaime, Doiron Brent, Shea-Brown Eric, Josić Kresimir, Reyes Alex

机构信息

Center for Neural Science, New York University, New York 10003, USA.

出版信息

Nature. 2007 Aug 16;448(7155):802-6. doi: 10.1038/nature06028.

Abstract

Populations of neurons in the retina, olfactory system, visual and somatosensory thalamus, and several cortical regions show temporal correlation between the discharge times of their action potentials (spike trains). Correlated firing has been linked to stimulus encoding, attention, stimulus discrimination, and motor behaviour. Nevertheless, the mechanisms underlying correlated spiking are poorly understood, and its coding implications are still debated. It is not clear, for instance, whether correlations between the discharges of two neurons are determined solely by the correlation between their afferent currents, or whether they also depend on the mean and variance of the input. We addressed this question by computing the spike train correlation coefficient of unconnected pairs of in vitro cortical neurons receiving correlated inputs. Notably, even when the input correlation remained fixed, the spike train output correlation increased with the firing rate, but was largely independent of spike train variability. With a combination of analytical techniques and numerical simulations using 'integrate-and-fire' neuron models we show that this relationship between output correlation and firing rate is robust to input heterogeneities. Finally, this overlooked relationship is replicated by a standard threshold-linear model, demonstrating the universality of the result. This connection between the rate and correlation of spiking activity links two fundamental features of the neural code.

摘要

视网膜、嗅觉系统、视觉和躯体感觉丘脑以及几个皮质区域中的神经元群体,其动作电位(尖峰序列)的发放时间之间呈现出时间相关性。相关发放与刺激编码、注意力、刺激辨别和运动行为有关。然而,相关尖峰活动背后的机制仍知之甚少,其编码意义也仍存在争议。例如,尚不清楚两个神经元发放之间的相关性是仅由它们传入电流之间的相关性决定,还是也取决于输入的均值和方差。我们通过计算接受相关输入的体外皮质神经元非连接对的尖峰序列相关系数来解决这个问题。值得注意的是,即使输入相关性保持不变,尖峰序列输出相关性也会随着发放率增加,但在很大程度上与尖峰序列变异性无关。通过结合分析技术和使用“积分发放”神经元模型的数值模拟,我们表明输出相关性与发放率之间的这种关系对输入异质性具有鲁棒性。最后,一个标准的阈值线性模型复制了这种被忽视的关系,证明了结果的普遍性。尖峰活动的发放率与相关性之间的这种联系将神经编码的两个基本特征联系了起来。

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