Functional imaging techniques are important to brain researchers and clinicians alike because many phenomena cannot be observed by anatomical techniques alone. Among functional imaging methods, only magneto- and electro-encephalography (MEG, EEG, or jointly M/EEG) can noninvasively resolve events with a millisecond time scale. Statistical tools for M/BEG functional brain imaging software will be developed to estimate and visualize the spatial extent and time course of brain activity. Algorithms will be developed for the incorporation of a priori information into source estimation, and for estimating the uncertainty of the estimates. These tools will permit the use of information derived from anatomy, physiology, and other functional imaging modalities (such as fMR1 and PET) to be combined with M/EEG data to improve the robustness, reliability, and objectivity of the M/EEG analysis. The algorithms will be incorporated into prototype software, and the software validated with both simulated and experimental data. The software will comprise a PC/Windows-based program suite for analysis and display. The algorithms and resulting software may be used to study both normal brain function, such as measurements in cognitive neuroscience which may be studied with evoked response/event related potentials or spontaneous EEG, and in diseases of the brain, such as the epilepsies, where precise spatial and temporal resolution may be of value for diagnosis and presurgical evaluation.
The techniques which we propose are a non-invasive, non-radiological and relatively low cost addition to existing EEG, MEG and MRI systems, and provides information which is not currently available from these systems independently. The resulting software will have direct application in clinical and cognitive neuroscience research. If clinical value is demonstrated, systems based on this methodology may find applications in the areas of psychiatry, neurology and psychology.
