Region-based current-source reconstruction for the inverse EEG problem.

This paper presents a new method for the reconstruction of current sources for the electroencephalography (EEG) inverse problem, which produces reconstructed sources, which are confined to a few anatomical regions. The method is based on a partition of the gray matter into a set of regions, and in the construction of a simple linear model for the potential produced by feasible source configurations inside each one of these regions. The proposed method computes the solution in two stages: in the first one, a subset of active regions is found so that the combined potentials produced by sources inside them approximate the measured potential data. In the second stage, a detailed reconstruction of the current sources inside each active region is performed. Experimental results with synthetic data are presented, which show that the proposed scheme is fast, computationally efficient and robust to noise, producing results that are competitive with other published methods, especially when the current sources are effectively distributed in few anatomical regions. The proposed method is also validated with real data from an experiment with visual evoked potentials.