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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| 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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