Bayesian statistics: Relevant for the brain?

Konrad Paul Kording*

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

20 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)130-133
Number of pages4
JournalCurrent opinion in neurobiology
Volume25
DOIs
StatePublished - Apr 2014

ASJC Scopus subject areas

  • Neuroscience(all)

Fingerprint Dive into the research topics of 'Bayesian statistics: Relevant for the brain?'. Together they form a unique fingerprint.

Cite this