Application of wavelet network combined with nonlinear dimensionality reduction on the neural dipole localization

Abstract

A wavelet network (WN) method is presented in this paper, which can be used to estimate the location and moment of an equivalent current dipole source using reduced-dimension data from the original measurement electroencephalography (EEG). In order to handle the large-scale high dimension problems efficiently and provide a real-time EEG dipole source localizer, the ISOMAP algorithm is firstly used to find the low dimensional manifolds from high dimensional EEG signal. Then, a WN is employed to discover the relationship between the observation potentials on the scalp and the internal sources within the brain. In our simulation experiments, satisfactory results are obtained. © Springer-Verlag Berlin Heidelberg 2006.