Litcius/Paper detail

An Empirically Driven Guide on Using Bayes Factors for M/EEG Decoding

Lina Teichmann

2022Aperture Neuro47 citationsDOIOpen Access PDF

Abstract

The purpose of Aperture is to enable a diverse approach to sharing and communicating high quality, community-based, open neuroscience while bringing transparency and interactivity to the publishing process.

Topics & Concepts

Bayes' theoremBayes factorMagnetoencephalographyFrequentist inferenceComputer scienceNaive Bayes classifierBayesian probabilityArtificial intelligenceMachine learningNeuroimagingMultivariate statisticsBayesian inferencePsychologyElectroencephalographyPsychiatrySupport vector machineNeural Networks and ApplicationsBlind Source Separation TechniquesFractal and DNA sequence analysis
An Empirically Driven Guide on Using Bayes Factors for M/EEG Decoding | Litcius