Particle filters: A new method for reconstructing multiple current dipoles from MEG data

We adapted a Bayesian tracking algorithm called particle filtering for estimating multiple current dipoles from magnetoencephalographic measurements. This method can reconstruct temporally correlated as well as moving dipolar sources in a fully automatic way. Here, we introduce the method and demonstrate its performance by modelling the highly correlated bilateral sources underlying the N100 auditory evoked response.