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神经群体可靠信息传输的关键规模。

Critical size of neural population for reliable information transmission.

机构信息

Institute of Physiology of the Czech Academy of Sciences, Videnska 1083, 14220 Prague 4, Czech Republic.

Principles of Informatics Research Division, National Institute of Informatics, 2-1-2 Hitotsubashi, Chiyoda-ku, Tokyo, Japan.

出版信息

Phys Rev E. 2019 Nov;100(5-1):050401. doi: 10.1103/PhysRevE.100.050401.

Abstract

It is known that the probability of decoding error has a phase transition at information rate equal to the channel capacity. The corresponding thermodynamic limit requires infinite coding dimension, hence making the actual decoding practically impossible. In this Rapid Communication we analyze finite-size effects that occur in limited neural populations. We report that the achievable rate approaches the asymptote in a remarkably nonlinear manner with the population size. Qualitatively, our findings do not seem to depend on the details of the model.

摘要

已知在信息率等于信道容量时,解码错误的概率会发生相变。相应的热力学极限需要无限的编码维度,因此实际解码几乎是不可能的。在这篇快报中,我们分析了有限大小的神经群体中发生的有限尺寸效应。我们报告说,在群体大小的显著非线性方式下,可实现的速率接近渐近线。从定性上看,我们的发现似乎不依赖于模型的细节。

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