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Improvement of source localization by dynamical systems based modeling (DSBM).

C Uhl·A Hutt·F Kruggel
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Abstract

Recently, we have proposed a new concept for analyzing EEG/MEG data (Uhl et al. 1998), which leads to a dynamical systems based modeling (DSBM) of neurophysiological data. We report the application of this approach to four different classes of simulated noisy data sets, to investigate the impact of DSBM-filtering on source localization. An improvement is demonstrated of up to above 50% of the distance between simulated and estimated dipole positions compared to principal component filtered and unfiltered data. On a noise level on which two underlying dipoles cannot be resolved from the unfiltered data, DSBM allows for an extraction of the two sources.

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AlgorithmsComputer SimulationElectroencephalographyHumansMagnetoencephalographyModels, NeurologicalJournal Article

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BibTeXRIS

C Uhl, A Hutt, F Kruggel. 2001. Improvement of source localization by dynamical systems based modeling (DSBM).. https://doi.org/10.1023/a%3A1007859220001

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