Learning to represent continuous variables in heterogeneous neural networks
Summary: Animals must monitor continuous variables such as position or head direction. Manifold attractor networks—which enable a continuum of persistent neuronal states—provide a key framework to explain this monitoring ability. Neural networks with symmetric synaptic connectivity dominate this fra...
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| Autori principali: | , |
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| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Elsevier
2022-04-01
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| Serie: | Cell Reports |
| Soggetti: | |
| Accesso online: | http://www.sciencedirect.com/science/article/pii/S2211124722003606 |
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