Deep Brain Structural Shape as Biomarkers for Neuropsychiatric Disorders

The brain’s deep nuclei – hippocampus, amygdala, thalamus, and basal ganglia – are an integral part of the brain’s distributed networks. I will provide an overview on how we use computational anatomy tools to characterize structural shape of these subcortical structures. In computational anatomy, spinal-temporal vector field information is used to assess anatomical shape, which can increase statistical power over volume in detecting abnormalities of brain structures in subjects with neuropsychiatric disorders. Patterns of shape deformity can provide further insight on disease pathophysiology. I will present applications in schizophrenia and Alzheimer’s disease, and discuss opportunities offered by the big-data era.

Dr. Wang received his PhD in Engineering Sciences from Harvard University, followed by post-doctoral work with Dr. Michael Miller at Washington University in St. Louis, working on computational anatomy. He joined Northwestern University in 2008.

Dr. Wang’s research is focused on developing neuroimaging biomarkers through computational tools, clinical and preclinical studies, and neuroinformatics. He applies computational anatomy tools to analyze structural MRI, functional MRI and histological neuroimaging data to investigate neuropsychiatric disorders including schizophrenia, Alzheimer’s disease, pediatric HIV and cancer treatments related cognitive impairment. Dr. Wang is also interested in reproducibility research through data sharing efforts.

Dr. Wang’s research has received grant support from the NIH, NSF, Alzheimer Association and the Brain Research Foundation. He is a Fellow of the American College of Neuropsychopharmacology.

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