Blind source separation (BSS) decomposes a multidimensional time series into a set of sources, each with a one-dimensional time course and a xed spatial distribution. For EEG and MEG, the former corresponds to the simultaneously separated and temporally overlapping signals for continuous non-averaged data; the latter corresponds to the set of attenuations from the sources to the sensors. These sensor projection vectors give information on the spatial locations of the sources. Here we use standard Neuromag dipole-tting software to localize BSS-separated components of MEG data collected in several tasks in which visual, auditory, and somatosensory stimuli all play a role. We found that BSS-separated components with stimulusor motor-locked responses can be localized to physiological and anatomically meaningful locations within the brain.