EEG source localization for two dipoles in the brain using a combined method

Estimating the correct location of electric current source with the brain from electroencephalographic (EEG) recordings is a challenging analytic and computational problem. Specifically, there is no unique solution and solutions do not depend continuously on the data. This is an inverse problem from EEG to dipole source. In this paper we consider a method combining backpropagation neural network (BPNN) with nonlinear least square (NLS) method for source localization. For inverse problem, the BP neural network and the NLS method has its own advantage and disadvantage, so we use the BPNN to supply the initial value to the NLS method and then get the final result, here we select the Powell algorithm to do the NLS calculating. All these work are for the fast and accurate dipole source localization. The main purpose of using this combined method is to localize two dipole sources when they are locating at the same region of the brain. The following investigations are presented to show that this combined method used in this paper is an advanced approach for two dipole sources localization with high accuracy and fast calculating.