Guorong Wu
University of North Carolina School of Medicine

Understanding the Selective Mechanism of Network Vulnerability in Alzheimer’s Disease Using Computational Neuroscience Approaches

Abstract: We are now in the era of big data. The unprecedented amount of biomedical data allows us to answer the biological questions today that we couldn’t answer before. As a computer scientist, this is the most exciting time in my entire career. In the last ten years, I have been collaborating with neurology, neuroscience, genetics, and imaging experts to understand the pathophysiological mechanism of Alzheimer’s disease (AD) and how AD-related genes affect aging brains. Specifically, my lab is interested in establishing a neurobiological basis to quantify the structural/functional/behavior difference across individuals and discover reliable and putative biomarkers that will allow us to come up with personalized therapy and treatment for individuals. In this talk, I would like to share my experience of integrating the domain knowledge of neuroscience into the development of computational tools for automated image analysis, image interpretation, and outcome prediction, with the focus on imaging biomarkers and the computer-assisted early diagnostic engine for AD. At the end of this talk, I will demonstrate the preliminary results of a recent research project where we aim to understand the selective mechanism of network vulnerability and resilience in AD using state-of-the-art network analysis approaches across neuroimaging and genetics data.

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