Improvement of Source Localization by Dynamical Systems Based Modeling (DSBM)

Author: Uhl C.   Hutt A.   Kruggel F.  

Publisher: Springer Publishing Company

ISSN: 0896-0267

Source: Brain Topography, Vol.13, Iss.3, 2001-01, pp. : 219-226

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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.