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An evaluation of EEG scanner's dependence on the imaging technique, forward model computation method, and array dimensionality

EEG 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 setup's dependence on correct forward modeling. Specifically, we examine how different...

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Published in:2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2012-01, Vol.2012, p.1538-1541
Main Authors: Stahlhut, C., Attias, H. T., Stopczynski, A., Petersen, M. K., Larsen, J. E., Hansen, L. K.
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container_title 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society
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creator Stahlhut, C.
Attias, H. T.
Stopczynski, A.
Petersen, M. K.
Larsen, J. E.
Hansen, L. K.
description EEG 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 setup's 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.
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source IEEE Electronic Library (IEL) Conference Proceedings
subjects Biological system modeling
Brain modeling
Computational modeling
Electroencephalography
Image reconstruction
Imaging
Sensors
title An evaluation of EEG scanner's dependence on the imaging technique, forward model computation method, and array dimensionality
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