School of Natural Sciences, Institute for Advanced Study, Princeton, NJ 08540, USA.
Network. 2011;22(1-4):4-44. doi: 10.3109/0954898X.2011.638888.
The sensory pathways of animals are well adapted to processing a special class of signals, namely stimuli from the animal's environment. An important fact about natural stimuli is that they are typically very redundant and hence the sampled representation of these signals formed by the array of sensory cells is inefficient. One could argue for some animals and pathways, as we do in this review, that efficiency of information representation in the nervous system has several evolutionary advantages. Consequently, one might expect that much of the processing in the early levels of these sensory pathways could be dedicated towards recoding incoming signals into a more efficient form. In this review, we explore the principle of efficiency of information representation as a design principle for sensory processing. We give a preliminary discussion on how this principle could be applied in general to predict neural processing and then discuss concretely some neural systems where it recently has been shown to be successful. In particular, we examine the fly's LMC coding strategy and the mammalian retinal coding in the spatial, temporal and chromatic domains.
动物的感觉通路非常适合处理一类特殊的信号，即来自动物环境的刺激。关于自然刺激的一个重要事实是，它们通常非常冗余，因此由感觉细胞阵列形成的这些信号的采样表示效率低下。人们可以为一些动物和途径争辩，就像我们在这篇综述中所做的那样，认为信息在神经系统中的表示效率具有几个进化优势。因此，人们可能期望这些感觉途径的早期水平的大部分处理都可以专门用于将传入的信号重新编码为更有效的形式。在这篇综述中，我们探讨了信息表示效率作为感觉处理设计原则的原理。我们初步讨论了如何将该原理一般应用于预测神经处理，然后具体讨论了最近已经证明成功的一些神经系统。特别是，我们研究了果蝇的 LMC 编码策略和哺乳动物在空间、时间和颜色域的视网膜编码。
