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 o!ering a powerful tool for studying temporal dynamics. We applied blind-source separation (BSS) to continuous 122-channel human magnetoencephalographic data from two subjects and "ve tasks. We demonstrate that without using any domain-speci"c 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 di!erent sensory modalities, and from di!erent processing stages within a given modality.
Abstract:Mobile media applications need to balance user and group goals, attentional constraints and limited screen real estate. In this paper, we describe the iterative development and testing of an application that explores these trade-offs. We developed early prototypes of a retrospective, time-based system as well as a prospective and space-based system. Our experiences with the prototypes led us to focus on the prospective system. We argue that attentional demands dominate and mobile media applications should be lightweight and hands-free as much as possible.
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