Improved EEG source localization with Bayesian uncertainty modelling of unknown skull conductivity

@article{Rimpilinen2019ImprovedES,
  title={Improved EEG source localization with Bayesian uncertainty modelling of unknown skull conductivity},
  author={Ville Rimpil{\"a}inen and Alexandra Koulouri and Felix Lucka and Jari P. Kaipio and Carsten H. Wolters},
  journal={NeuroImage},
  year={2019},
  volume={188},
  pages={252-260}
}
Electroencephalography (EEG) source imaging is an ill-posed inverse problem that requires accurate conductivity modelling of the head tissues, especially the skull. Unfortunately, the conductivity values are difficult to determine in vivo. In this paper, we show that the exact knowledge of the skull conductivity is not always necessary when the Bayesian approximation error (BAE) approach is exploited. In BAE, we first postulate a probability distribution for the skull conductivity that… CONTINUE READING
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