A Biologically Plausible Learning Rule for Perceptual Systems of organisms that Maximize Mutual Information

2021/09/07 by Tao Liu, Liu, Tao
Computer Science · Engineering · Neuroscience · #Advanced Memory and Neural Computing #Artificial Intelligence (cs.AI) #FOS: Biological sciences #FOS: Computer and information sciences #Neural Networks and Applications #Neural and Evolutionary Computing (cs.NE) #Neural dynamics and brain function #Neurons and Cognition (q-bio.NC) #Visual perception and processing mechanisms

paper · pdf · doi:10.48550/arxiv.2109.13102

openalex publication_date 2021/09/07 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

It is widely believed that the perceptual system of an organism is optimized for the properties of the environment to which it is exposed. A specific instance of this principle known as the Infomax principle holds that the purpose of early perceptual processing is to maximize the mutual information between the neural coding and the incoming sensory signal. In this article, we present a method to implement this principle accurately with a local, spike-based, and continuous-time learning rule.

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