Multimodal functional brain imaging software will be developed to estimate and visualize the estimated spatial extent and time course of brain activity by combining information from magnetic resonance imaging (MRI) with electroencephalography (EEG) and/or magnetoencephalography (MEG). Structural information from MRI will be combined with extracranial EEG and/or MEG measurements through algorithms developed to segment the MR images and to represent scalp, skull, and brain boundaries as computational objects. This structural information may then be used to improve the spatial accuracy and resolution of existing EEG and MEG source estimation algorithms, while supporting millisecond temporal resolution. The software will comprise a PC/Windows-based program suite for analysis and display. The methods will be verified both with simulated data and with physiological data. The algorithms and 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 epilepsy, 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.
