Hierarchical Bayesian inference for the EEG inverse problem using realistic FE head models: Depth localization and source separation for focal primary currents

► We consider hierarchical Bayesian modeling for EEG current density reconstruction. ► Scenarios of few focal sources are examined using fully-Bayesian inference. ► Superior results to established methods in depth localization and source separation. ► A realistic, high resolution finite element head model is used. ► Wasserstein distances as performance measures for inverse methods are introduced.