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刺激依赖相关性与群体编码。

Stimulus-dependent correlations and population codes.

作者信息

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

机构信息

Department of Mathematics, University of Houston, Houston, TX 77204-3008, USA.

出版信息

Neural Comput. 2009 Oct;21(10):2774-804. doi: 10.1162/neco.2009.10-08-879.

Abstract

The magnitude of correlations between stimulus-driven responses of pairs of neurons can itself be stimulus dependent. We examine how this dependence affects the information carried by neural populations about the stimuli that drive them. Stimulus-dependent changes in correlations can both carry information directly and modulate the information separately carried by the firing rates and variances. We use Fisher information to quantify these effects and show that, although stimulus-dependent correlations often carry little information directly, their modulatory effects on the overall information can be large. In particular, if the stimulus dependence is such that correlations increase with stimulus-induced firing rates, this can significantly enhance the information of the population when the structure of correlations is determined solely by the stimulus. However, in the presence of additional strong spatial decay of correlations, such stimulus dependence may have a negative impact. Opposite relationships hold when correlations decrease with firing rates.

摘要

成对神经元的刺激驱动反应之间相关性的大小本身可能依赖于刺激。我们研究这种依赖性如何影响神经群体携带的关于驱动它们的刺激的信息。相关性中依赖于刺激的变化既能直接携带信息,又能调节由放电率和方差分别携带的信息。我们使用费希尔信息来量化这些效应,并表明,尽管依赖于刺激的相关性通常直接携带的信息很少,但其对整体信息的调节作用可能很大。特别是,如果刺激依赖性使得相关性随刺激诱导的放电率增加,那么当相关性结构仅由刺激决定时,这可以显著增强群体的信息。然而,在存在额外的强相关性空间衰减的情况下,这种刺激依赖性可能会产生负面影响。当相关性随放电率降低时,情况则相反。

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