Taming the chaos gently: a predictive alignment learning rule in recurrent neural networks

Abstract Recurrent neural circuits often face inherent complexities in learning and generating their desired outputs, especially when they initially exhibit chaotic spontaneous activity. While the celebrated FORCE learning rule can train chaotic recurrent networks to produce coherent patterns by sup...

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Bibliographic Details
Main Authors: Toshitake Asabuki, Claudia Clopath
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Nature Communications
Online Access:https://doi.org/10.1038/s41467-025-61309-9
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