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Magnetoencephalography (MEG) is a functional brain imaging technique with millisecond temporal resolution and millimeter spatial sensitivity. The high temporal resolution of MEG compared to fMRI and PET (milliseconds vs. seconds and tens of seconds) makes it ideal for measuring the precise time of neuronal responses, thereby offering a powerful tool for studying temporal dynamics. We applied blind-source separation (BSS) to continuous 122-channel human magnetoencephalographic data from two subjects and five tasks. We demonstrate that without using any domain-specific knowledge and without making the common assumption of single- or multiple-current dipole sources, BSS is capable of separating non-neuronal noise sources from neuronal responses and also of separating neuronal responses from different sensory modalities, and from different processing stages within a given modality.