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  • Letter
  • Open Access

Inherent trade-off in noisy neural communication with rank-order coding

Ibrahim Alsolami* and Tomoki Fukai

  • Neural Coding and Brain Computing Unit, Okinawa Institute of Science and Technology (OIST) Graduate University, Onna, Okinawa 904-0495, Japan

  • *ibrahim.alsolami@oist.jp
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Phys. Rev. Research 6, L012009 – Published 16 January, 2024

DOI: https://doi.org/10.1103/PhysRevResearch.6.L012009

Abstract

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 Letter is the emergence of a special class of errors that, in a regime, increase with less noise.

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Phys. Rev. Research 6, L012009– Published 16 January, 2024
  • Received 13 August 2023
  • Accepted 14 December 2023
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Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.

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