Current density reconstruction with multi-scale grid approach

The computational cost of solving an electroencephalographic (EEG) or magnetoencephalographic (MEG) inverse problem is extremely high due to the inversion of a matrix configured with a priori information. The matrix size is proportional to the number of points in source grid. We present a multi-scale grid approach to solve the inverse problem using FOCUSS algorithms which is one of the current density reconstruction (CDR) methods and tested the algorithm with simulated EEG data. The multi-scale grid approach dramatically reduces grid points without loss of the resolution.