SEEG dipole source localization based on an empirical Bayesian approach taking into account forward model uncertainties.Electromagnetic brain source localization consists in the inversion of a forward model based on a limited number of potential measurements.  In this work we propose an empirical Bayesian approach to take into account the uncertainties of the forward model by allowing constrained variations around a prior physical model, in the particular context of SEEG measurements. 
SEEG
SEEG dipole source localization based on an empirical Bayesian approach taking into account forward model uncertainties.Electromagnetic brain source localization consists in the inversion of a forward model based on a limited number of potential measurements.  Bayesian approaches have the ability to provide sparse solutions under adequate parametrization, and bring a convenient framework for the introduction of priors in the form of probabilistic density functions.  In this work we propose an empirical Bayesian approach to take into account the uncertainties of the forward model by allowing constrained variations around a prior physical model, in the particular context of SEEG measurements. 
Bayesian approach
SEEG dipole source localization based on an empirical Bayesian approach taking into account forward model uncertainties.Electromagnetic brain source localization consists in the inversion of a forward model based on a limited number of potential measurements. 
forward model uncertainties