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Rank-order coding, a form of temporal coding, has emerged as a promisingscheme to explain the rapid ability of the mammalian brain. Owing to its speedas well as efficiency, rank-order coding is increasingly gaining interest indiverse research areas beyond neuroscience. However, much uncertainty stillexists about the performance of rank-order coding under noise. Herein we showwhat information rates are fundamentally possible and what trade-offs are atstake. An unexpected finding in this paper is the emergence of a special classof errors that, in a regime, increase with less noise.

An Inherent Trade-Off in Noisy Neural Communication with Rank-Order Coding