The processing and interpretation of M/EEG signals is, however, challenging. While fMRI provides unambiguous localization of the measured blood-oxygen-level dependent signal, estimating the neural currents underlying M/EEG is difficult. This complex task involves segmenting various structures from anatomical MRIs, numerical solution of the electromagnetic forward problem, signal denoising, a solution to the ill-posed electromagnetic inverse problem, and appropriate statistical control. This complexity not only constitutes methodological challenges to MEG investigators, but also offers a great deal of flexibility in data analysis. To successfully process M/EEG data, a comprehensive and well-documented analysis pipeline is therefore required.
