Multi-dipole EEG source localization using particle swarm optimization

Y. Shirvany, F. Edelvik, M. Persson, IEEE Engineering in Medicine and Biology Society, July 2013, 6357-6360.


The multi-dipole EEG source localization problem is (usually) highly nonlinear with a non-convex cost function. Moreover, the gray matter tissue is located in several disjunct regions in the head which leads to a non-continuous solution space. For solving this problem an efficient algorithm which can handle multi-source activities is needed. In this paper, a modified particle swarm optimization (MPSO) method is proposed to solve the multi-dipole EEG source localization. The method is tested on synthetic EEG signals generated from two strong active sources and a noisy background source. The results show that using the new method is a reliable choice when we deal with a strong multi-active source scenario, in which a single dipole source localization may fail.


Authors and Affiliations

  • Y. Shirvany, Departure of Signals & Systems, Chalmers University of Technology
  • F. Edelvik, Fraunhofer-Chalmers Centre
  • M. Persson, Fraunhofer-Chalmers Centre


Photo credits: Nic McPhee