Literature DB >> 24463330

Bayesian statistics: relevant for the brain?

Konrad Paul Kording1.   

Abstract

Analyzing data from experiments involves variables that we neuroscientists are uncertain about. Efficiently calculating with such variables usually requires Bayesian statistics. As it is crucial when analyzing complex data, it seems natural that the brain would "use" such statistics to analyze data from the world. And indeed, recent studies in the areas of perception, action, and cognition suggest that Bayesian behavior is widespread, in many modalities and species. Consequently, many models have suggested that the brain is built on simple Bayesian principles. While the brain's code is probably not actually simple, I believe that Bayesian principles will facilitate the construction of faithful models of the brain.
Copyright © 2014 Elsevier Ltd. All rights reserved.

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Year:  2014        PMID: 24463330      PMCID: PMC3981868          DOI: 10.1016/j.conb.2014.01.003

Source DB:  PubMed          Journal:  Curr Opin Neurobiol        ISSN: 0959-4388            Impact factor:   6.627


  27 in total

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4.  Bayesian inference with probabilistic population codes.

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10.  Brain systems for probabilistic and dynamic prediction: computational specificity and integration.

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  13 in total

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3.  Control of the strength of visual-motor transmission as the mechanism of rapid adaptation of priors for Bayesian inference in smooth pursuit eye movements.

Authors:  Timothy R Darlington; Stefanie Tokiyama; Stephen G Lisberger
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5.  Will understanding vision require a wholly empirical paradigm?

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Journal:  Front Psychol       Date:  2015-07-30

6.  The Cluster Variation Method: A Primer for Neuroscientists.

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7.  Mentalizing regions represent distributed, continuous, and abstract dimensions of others' beliefs.

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9.  Perception and Reality: Why a Wholly Empirical Paradigm is Needed to Understand Vision.

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10.  Feasibility Theory Reconciles and Informs Alternative Approaches to Neuromuscular Control.

Authors:  Brian A Cohn; May Szedlák; Bernd Gärtner; Francisco J Valero-Cuevas
Journal:  Front Comput Neurosci       Date:  2018-09-11       Impact factor: 2.380

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