Global optimization approaches to MEG source localization

Abstract

The authors compare the performance of three typical and widely used optimization techniques for a specific MEG source localization problem. Firstly, they introduce a hybrid algorithm by combining genetic and local search strategies to overcome disadvantages of conventional genetic algorithms. Secondly, they apply the tabu search: a widely used optimization methods in combinational optimization and discrete mathematics, to source localization. To the best of the authors' knowledge, this is the first attempt in the literature to apply tabu search to MEG/EEG source localization. Thirdly, in order to further comparison of the performance of above algorithms, simulated annealing is also applied to MEG source localization problem. The computer simulation results show that the authors' local genetic algorithm is the most effective approach to dipole location.