Three-dimensional filtering approach to brain potential mapping

The spatial distribution of electroencephalogram (EEG) features on the scalp surface, both in time or frequency, is of great importance in clinical applications and medical research. Traditionally, mathematical methods based on interpolation algorithms have been widely applied to obtain the EEG mappings. This paper presents an innovative approach to reconstructing the brain potential mappings from multichannel EEGs. The three-dimensional (3-D) filtering approach, differing from the numerical interpolating methods, considers the spatial distribution of brain potentials as a 3-D signal, which is processed and interpolated according to its spatial frequency characteristics. The performance of the 3-D filtering method evaluated on simulated brain potentials is shown to be comparable to the four-nearest-neighbors method. Moreover, the 3-D filtering method is superior to the spherical splines method in efficiency. Two main advantages of this method are: the prospect of developing realtime, animated EEG mappings utilizing powerful digital signal processors and its capability of processing and interpolating the brain potentials on the realistic irregular scalp surface.