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首页> 外文期刊>Proceedings of the National Academy of Sciences of the United States of America >Neuronal couplings between retinal ganglion cells inferred by efficient inverse statistical physics methods
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Neuronal couplings between retinal ganglion cells inferred by efficient inverse statistical physics methods

机译：通过有效的逆统计物理方法推断视网膜神经节细胞之间的神经元耦合

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摘要

Complexity of neural systems often makes impracticable explicit measurements of all interactions between their constituents. Inverse statistical physics approaches, which infer effective couplings between neurons from their spiking activity, have been so far hindered by their computational complexity. Here, we present 2 complementary, computationally efficient inverse algorithms based on the Ising and "leaky integrate-and-fire" models. We apply those algorithms to reanalyze multielectrode recordings in the salamander retina in darkness and under random visual stimulus. We find strong positive couplings between nearby ganglion cells common to both stimuli, whereas long-range couplings appear under random stimulus only. The uncertainty on the inferred couplings due to limitations in the recordings (duration, small area covered on the retina) is discussed. Our methods will allow realtime evaluation of couplings for large assemblies of neurons.
机译：神经系统的复杂性通常无法对其各组成部分之间的所有相互作用进行明确的测量。迄今为止，逆统计物理方法由于其计算复杂性而受阻，该方法从其尖峰活动中推断出神经元之间的有效耦合。在这里，我们基于Ising和“泄漏集成并发射”模型，提出2种互补的，计算效率高的逆算法。我们应用这些算法在黑暗和随机视觉刺激下重新分析the视网膜中的多电极记录。我们发现附近的神经节细胞之间的强烈刺激积极耦合，而远程耦合仅在随机刺激下出现。讨论了由于记录限制（持续时间，视网膜上覆盖的小区域）而导致的推断耦合的不确定性。我们的方法将允许实时评估大型神经元组件的耦合。

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  • 作者

    Simona Cocco; Stanislas Leibler; Remi Monasson;

  • 作者单位

    Laboratoire de Physique Statistique de I'Ecole Normale Superieure, Universite Pierre et Marie Curie, Universite Denis Diderot, Centre National de la Recherche Scientifique, 24 Rue Lhomond, 75005 Paris, France;

    Center for Studies in Physics and Biology and Laboratory of Living Matter, The Rockefeller University, 1230 York Avenue, New York, NY 10065 The Simons Center For Systems Biology and School of Natural Sciences, Institute for Advanced Study, Einstein Drive, Princeton, NJ 08540;

    Laboratoire de Physique Theorique de I'Ecole Normale Superieure, Universite Pierre et Marie Curie, Centre National de la Recherche Scientifique, 24 Rue Lhomond, 75005 Paris, France;

  • 收录信息 美国《科学引文索引》(SCI);美国《生物学医学文摘》(MEDLINE);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    inference and inverse problems; multielectrode recordings; neural couplings;

    机译：推理和反问题;多电极记录;神经耦合;

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