-
Advances in Neural Networks - ISNN 2007, 4th International Symposium on Neural Networks, ISNN 2007, Nanjing, China, June 3-7, 2007, Proceedings, Part II; 01/2007
-
Advances in Neural Networks - ISNN 2006, Third International Symposium on Neural Networks, Chengdu, China, May 28 - June 1, 2006, Proceedings, Part III; 01/2006
-
[show abstract]
[hide abstract]
ABSTRACT: How to locate the neural activation sources effectively and precisely from the magnetoencephalographic (MEG) recording is
a critical issue for the clinical neurology and brain functions research. Multiple signal classification (MUSIC) algorithm
and recursive MUSIC algorithm are widely used to locate multiple dipolar sources from the MEG data. The drawback of these
algorithms is that they run very slowly when scanning a three-dimensional head volume globally. In order to solve this problem,
a novel MEG sources localization scheme based on genetic algorithm (GA) is proposed. First, this scheme uses the property
of global optimum of GA to estimate the rough source location. Then, combined with grids in small area, the accurate dipolar
source localization is performed. Furthermore, we introduce the adaptive crossover and mutation probability, two-point crossover
operator, periodical substitution and niche strategies to overcome the disadvantage of GA which falls into local optimum occasionally.
Experimental results show that the proposed scheme can improve the speed of source localization greatly and its accuracy is
satisfactory.
01/1970: pages 1133-1139;
