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There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
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Advisor:
Xiaoping Hu, Ph.D. (Georgia Institute of Technology/Emory University)
Committee:
Helen S. Mayberg, M.D. (Emory University)
Paul E. Holtzheimer, M.D. (Dartmouth College)
Xiaoming Huo, Ph.D. (Georgia Institute of Technology)
Shella Keilholz, Ph.D. (Georgia Institute of Technology/Emory University)
Robert Gross, M.D. Ph.D. (Georgia Institute of Technology/Emory University)
Diffusion tensor imaging (DTI) is a noninvasive MRI technique used to assess white matter (WM) integrity, fiber orientation, and structural connectivity (SC) using water diffusion properties. DTI techniques are rapidly evolving and are now having a dramatic effect on depression research. Major depressive disorder (MDD) is highly prevalent and a leading cause of worldwide disability. Despite decades of research, the neurobiology of MDD remains poorly understood. MDD is increasingly viewed as a disorder of neural circuitry in which a network of brain regions involved in mood regulation is dysfunctional. In an effort to better understand the pathophysiology of MDD and develop more effective treatments, much research has focused on delineating the structure and function of this mood regulation network. Although many studies have focused on the structural connectivity of the mood regulation network, their findings using DTI for depression were shown highly variable due to many technical and analytical limitations. In addition to inconsistent previous finding, structural connectivity (SC) pattern analysis hasn’t been utilized for critical clinical treatment such as deep brain stimulation (DBS). The proposed work seeks to characterize and optimize for subcallosal cingulate cortex (SCC) DBS treatment in depression. First, a definitive analysis of WM abnormalities will be performed with large population in depressed patients by optimized pre- /post-processing. Assessment of WM integrity in depression can be used to design future DBS treatment approaches. Second, key therapeutic pathways of SCC DBS will be identified by SC analysis from current active stimulation. After specific fiber bundles and pathways critical for the antidepressant effect of SCC DBS are defined, those pathways will be used for future optimization of SCC DBS. The third aim of the proposed work will establish a new strategy for precise electrode implementation of SCC DBS by quantitative SC pattern analysis. These studies will lead to better characterization of pathophysiology in depression and improve an efficacy of SCC DBS.
