An Evaluation of EEG Scannerís Dependence on the Imaging Technique, Forward Model Computation Method, and Array Dimensionality

Carsten Stahlhut, Hagai Thomas Attias, Arkadiusz Stopczynski, Michael Kai Petersen, Jakob Eg Larsen, Lars Kai Hansen

AbstractEEG source reconstruction involves solving an inverse problem that is highly ill-posed and dependent on a generally fixed forward propagation model. In this contribution we compare a low and high density EEG setupís dependence on correct forward modeling. Specifically, we examine how different forward models affect the source estimates obtained using four inverse solvers Minimum-Norm, LORETA, Minimum-Variance Adaptive Beamformer, and Sparse Bayesian Learning.
TypeConference paper [With referee]
Conference34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), San Diego, CA
BibTeX data [bibtex]
IMM Group(s)Intelligent Signal Processing

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