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The Redemption of Noise:Inference with Neural Populations
Title / Series / Name
Trends in Neurosciences
Publication Volume
41
Publication Issue
11
Pages
Authors
Editors
Keywords
Bayesian inference
cortex
neural network
neural variability
perception
uncertainty
General Neuroscience
cortex
neural network
neural variability
perception
uncertainty
General Neuroscience
URI
https://hdl.handle.net/20.500.14018/28548
Abstract
In 2006, Ma et al. (Nat. Neurosci. 1006;9:1432–1438) presented an elegant theory for how populations of neurons might represent uncertainty to perform Bayesian inference. Critically, according to this theory, neural variability is no longer a nuisance, but rather a vital part of how the brain encodes probability distributions and performs computations with them.
Topic
Publisher
Place of Publication
Type
Journal article
Date
2018-11
Language
ISBN
Identifiers
10.1016/j.tins.2018.09.003