Rank-order coding, a form of temporal coding, has emerged as a promising scheme to explain the rapid ability of the mammalian brain. Owing to its speed as well as efficiency, rank-order coding is increasingly gaining interest in diverse research areas beyond neuroscience. However, much uncertainty still exists about the performance of rank-order coding under noise. Herein we show what information rates are fundamentally possible and what trade-offs are at stake. An unexpected finding in this paper is the emergence of a special class of errors that, in a regime, increase with less noise.

翻译：排序编码作为一种时间编码形式，已成为解释哺乳动物大脑快速处理能力的一种有前景机制。因其快速性和高效性，排序编码在神经科学以外的多个研究领域日益受到关注。然而，关于排序编码在噪声条件下的性能仍存在诸多不确定性。本文揭示了在噪声环境下排序编码可达到的信息速率基本极限及其面临的权衡关系。一个意外的发现是，存在一类特殊错误，在特定条件下会随着噪声降低反而增加。