@ARTICLE\{IMM2010-05987,
    author       = "C. Stahlhut and M. M{\o}rup and O. Winther and L. K. Hansen",
    title        = "Simultaneous {EEG} Source and Forward Model Reconstruction (SOFOMORE) using a Hierarchical Bayesian Approach",
    year         = "2010",
    keywords     = "{EEG} - Inverse problem - Source localization - Distributed models - Variational Bayes - Forward model reconstruction",
    journal      = "Journal of Signal Processing Systems",
    volume       = "",
    editor       = "",
    number       = "",
    publisher    = "Springer New York",
    url          = "http://dx.doi.org/10.1007/s11265-010-0527-0",
    abstract     = "We present an approach to handle forward model uncertainty for {EEG} source reconstruction. A stochastic forward model representation is motivated by the many random contributions to the path from sources to measurements including the tissue conductivity distribution, the geometry of the cortical surface, and electrode positions. We first present a hierarchical Bayesian framework for {EEG} source localization that jointly performs source and forward model reconstruction (SOFOMORE). Secondly, we evaluate the {SOFOMORE} approach by comparison with source reconstruction methods that use fixed forward models. Analysis of simulated and real {EEG} data provide evidence that reconstruction of the forward model leads to improved source estimates."
}