Work

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

Year: 2023

Type: preprint

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

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.2308.07034

Authors: Alsolami, Ibrahim, Fukai, Tomoki

Institution: Okinawa Institute of Science and Technology Graduate University

Language: English

Topic: Neural dynamics and brain function

Subfield: Cognitive Neuroscience

Field: Neuroscience

Domain: Life Sciences

Open Access status: green

Funders: Okinawa Institute of Science and Technology Graduate University, Japan Society for the Promotion of Science

Awards: G5355285265, Mechanisms underlying Information processing in idling brain

OpenAlex ID: W4385849138

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