Accuracy of Single Dipole Source Localization by BP Neural Networks from 18-Channel EEGs

A problem of estimating biopotential sources in the brain based on EEG signals observed on the scalp is known as an important inverse problem of electrophysiology. Usually there is no closed-form solution for this problem and it requires iterative techniques such as the Levenberg-Marquardt algorithm. Considering the nonlinear properties of inverse problem, and signal to noise ratio inherent in EEG signals, a back propagation neural network has been recently proposed as a solution. In this paper, we investigated the properties of neural networks and its localization accuracy for single dipole source localization. Based on the results of extensive studies, we concluded the neural networks are highly feasible in single-source localization with a small number of electrodes (18 electrodes), also examined the usefulness of this method for clinical application with a case of epilepsy.