Available data suggest individuals with Tourette Syndrome (TS) have abnormalities in parts of the brain that help to control and coordinate movements, such as the thalamus and the basal ganglia. These abnormalities may be relevant to the pathophysiology of the disorder. Computational and analytic tools are being developed at a rapid pace in the emerging field of computational anatomy. These techniques enable precise analysis of neuroanatomical volumes, shapes and asymmetries derived from magnetic resonance (MR) images, and give us the ability to characterize subtle abnormalities of brain structures that were previously undetectable. Within the framework of computational anatomy, different individual MR images can be mapped from a common digital atlas with all of the individual details preserved. In this way, normal variability of brain structures can be quantified by studying a collection of MR images from a group of normal individuals. In this study, we will focus on the thalamus and the basal ganglia, and will establish whether computational methods are valid and reliable for these brain structures. We will then apply these methods to study of the thalamus and the basal ganglia in existing MR scans of adults with and without TS. Subtle differences in volumes and shapes of brain structures between groups of individuals with and without TS will be quantitatively defined. Tic symptoms usually peak during adolescence and level off in adulthood. Other studies have suggested that brain structural abnormalities in TS depend on age, and that scans in children are most likely to show structural brain changes relevant to pathophysiology. Although this question might be answered directly from longitudinal studies of children, we plan to study cross-sectional groups of children and teenagers with and without TS to determine the efficacy and validity of our computational approaches for assessing abnormalities. Lei Wang, Ph.D. Washington University School of Medicine, St. Louis, MO Award: $74,250 Tourette Association of America Inc. – Research Grant Award 2004-2005