Global Optimization in the Localization of Brain Activity

摘要

The locations of active brain areas can be estimated from the magnetic fieldproduced by the neural current sources. In many cases, the actual current dipoles with time-varying amplitudes. This work studies global optimization methods that find the minimum of the least-squares error function of the current dipole estimation problem without initial guesses. Three different global optimization methods were investigated: clustering method, simulated annealing, and genetic algorithms. In simulation studies the genetic algorithm was the most effective method. A nonlinear methd for estimation of the localization error was developed. The methods were applied to analysis of actual measurement data.