REALISTIC NUMERICAL MODELS OF BRAIN ELECTRICAL CURRENTS

Source Signal Imaging, Inc., San Diego CA

Investigators

Abstract

Functional imaging techniques are important to brain researchers and clinicians alike because many phenomena cannot he 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. The aim of this work is the development, validation, and commercialization of a detailed, realistic model of electrical current flow in the head, the currents originating from sources within the brain, and measured electrically and/or magnetically on or near the surface of the scalp. 3D finite element models of individual heads will be constructed with the aid of magnetic resonance imaging (MRI). The finite element method provides the needed flexibility for modeling an asymmetric, anisotropic, and inhomogeneous medium like the head. The algorithms will he incorporated into prototype software, and the software validated with both simulated and experimental data. The software will comprise a realistic modeling module of our EMSE suite, our 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 he 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. PROPOSED COMMERCIAL APPLICATIONS: The technique which we propose is 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.