Use of parallel simulated annealing for computational modeling of human head conductivity

Abstract

We present a parallel computational environment used to determine conductivity properties of human head tissues when the effects of skull inhomogeneities are modeled. The environment employs a parallel simulated annealing algorithm to overcome poor convergence rates of the simplex method for larger numbers of head tissues required for accurate modeling of electromagnetic dynamics of brain function. To properly account for skull inhomogeneities, panellation of skull parts is necessary. The multi-level parallel simulated annealing algorithm is described and performance results presented. Significant improvements in both convergence rate and speedup are achieved. The simulated annealing algorithm was successful in extracting conductivity values for up to thirteen head tissues without showing computational deficiency. © Springer-Verlag Berlin Heidelberg 2007.