Rapid Bayesian learning in the mammalian olfactory system

How can rodents make sense of the olfactory environment without supervision? Here, the authors formulate olfactory learning as an integrated Bayesian inference problem, then derive a set of synaptic plasticity rules and neural dynamics that enables near-optimal learning of odor identification.

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Autores principales: Naoki Hiratani, Peter E. Latham
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2020
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Acceso en línea:https://doaj.org/article/f6df5da2e76146c792e6313cc3b56b26
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