Electroencephalographic (EEG) imaging techniques have recently been developed to deal with the problem of data reduction and interpretation of brain electrical activity. Topographic imaging of EEG results in condensation, summary and color display of spectral, spatial and temporal data recorded from multiple scalp electrodes. The product of this data handling is a topographic map of electrical activity across the entire scalp. This EEG display technique has been useful in psychiatric and neurologic research. For example, in previous studies, characteristic electrophysiological features were discovered in a group of schizophrenics. The neuroanatomical correlates of these features of EEG are unknown at the present time. Magnetic resonance imaging is also a recently developed non- invasive diagnostic tool, which yields resolution images of the anatomy of the brain. Thus, two techniques are available, one which provides unique physiological information about the brain; the other an anatomical window into the brain. In addition to these tools, computer graphics research has developed advanced high resolution 3-D graphics capabilities which can be utilized for medical applications. What we propose is an interdisciplinary project which will utilize all three of these technologies to produce for the first time high resolution overlapping images incorporating both brain anatomy and brain function within a given subject. Our overall goal is to improve our naive understanding of regional correlations between scalp-recorded EEG and underlying brain anatomy. In order to achieve this goal we plan to 1) develop and refine a combinational EEG/MRI imaging technique; 2) demonstrate its clinical relevance in value in patients with known pathology (solitary tumors) and patients with well diagnosed schizophrenia; correlating functional abnormalities seen on EEG with underlying brain anatomy. We strongly believe that this technique, when fully developed, will be a powerful new approach in the assessment of functional and structural brain disorders and provide dramatic new insights into the pathophysiology of schizophrenia. It will also represent a major refinement in Electroencephalography.
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