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.

Bibliographic Details
Main Authors: Naoki Hiratani, Peter E. Latham
Format: Article
Language:English
Published: Nature Publishing Group 2020-07-01
Series:Nature Communications
Online Access:https://doi.org/10.1038/s41467-020-17490-0

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