The overall aim of this thesis is a better understanding of the main brain mechanisms through different magnetoencephalography (MEG) analysis methods, during a task-switching experiment. MEG is a non-invasive functional neuroimaging technique that relies on the measurement – outside of the head – of the magnetic field produced by neuronal activity. Because of its high temporal and spatial resolution yet complex and expensive system, MEG is still considered today a cutting-edge technology whose use is still mainly for research purposes and not a widely established diagnosis method like fMRI or EEG. This work has the objective to localize and investigate in space, time and frequency, the origin and propagation of the cortical signal, implementing specific functions provided mostly by the MNE-Python package.