Modelling background activity of the brain in single trial MEG experiments

We address the problem of fitting ARMA models to the background activity of the brain corrupting the signals in Magneto-Encephalography (MEG) experiments. We discuss different ways of reducing the non-stationarity of the signals, selecting the model order and estimating the model parameters, and we propose a process of estimating the best model in single trial experiments.