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

Authors:
Qing Wu;Lukui Shi;Tao Lin;Ping He
Affiliations:
School of Computer Science and Software, Hebei University of Technology, Tianjin, China;School of Computer Science and Software, Hebei University of Technology, Tianjin, China;School of Computer Science and Software, Hebei University of Technology, Tianjin, China;School of Computer Science and Software, Hebei University of Technology, Tianjin, China
Venue:
ICIC'06 Proceedings of the 2006 international conference on Intelligent Computing - Volume Part I
Year:
2006

Citing 3
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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.