How Do Efficient Coding Strategies Depend on Origins of Noise in Neural Circuits?
How Do Efficient Coding Strategies Depend on Origins of Noise in Neural Circuits?
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DOI：
10.1371/journal.pcbi.1005150
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发表时间：
2016-10-01
影响因子：
4.3
通讯作者：
Shea-Brown, Eric
中科院分区：
文献类型：
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作者：
Brinkman, Braden A. W.;Weber, Alison I.;Shea-Brown, Eric
尽管在处理的多个阶段存在噪声，神经回路仍能可靠地编码和传输信号。高效编码假说是计算神经科学的一个指导原则，它认为一个神经元或神经元群尽可能有效地分配其有限的响应范围，以便在减轻噪声影响的同时对输入进行最佳编码。先前关于这个问题的工作依赖于噪声进入电路的特定假设，限制了所得结论的通用性。本文系统地研究了在神经处理的不同阶段引入的噪声对最优编码策略的影响。通过模拟和灵活的分析方法，我们展示了这些策略如何依赖于每个噪声源的强度，揭示了在什么条件下不同的噪声源具有竞争或互补的影响。我们得出了两个主要结论：(1)感觉系统D之间编码策略的差异，甚至在给定系统D内编码特性的适应性变化可能是由神经噪声的结构或位置的变化产生的；(2)电路非线性和噪声的表征对于评估电路是否有效运行是必要的。
Neural circuits reliably encode and transmit signals despite the presence of noise at multiple stages of processing. The efficient coding hypothesis, a guiding principle in computational neuroscience, suggests that a neuron or population of neurons allocates its limited range of responses as efficiently as possible to best encode inputs while mitigating the effects of noise. Previous work on this question relies on specific assumptions about where noise enters a circuit, limiting the generality of the resulting conclusions. Here we systematically investigate how noise introduced at different stages of neural processing impacts optimal coding strategies. Using simulations and a flexible analytical approach, we show how these strategies depend on the strength of each noise source, revealing under what conditions the different noise sources have competing or complementary effects. We draw two primary conclusions: (1) differences in encoding strategies between sensory systems D or even adaptational changes in encoding properties within a given system D may be produced by changes in the structure or location of neural noise, and (2) characterization of both circuit nonlinearities as well as noise are necessary to evaluate whether a circuit is performing efficiently.