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The past thirty years have witnessed remarkable progress in neuroimaging technologies such as magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI). These imaging modalities have allowed researchers to map the human brain in exquisite detail, with often extraordinary consequences upon medical practice. For example, neuroimaging techniques such as MRI and DTI have been extremely useful for understanding traumatic brain injury (TBI), a poorly understood and previously neglected condition whose potential severity is now finally being acknowledged. Research suggests that TBI victims may be at higher risk for Alzheimer’s disease (AD), Parkinson's disease (PD), vascular dementia (VD) and brain cancer, but the reasons for this remain shrouded in mystery. The aging brain and the young brain are affected by TBI differently, and brain scans can assist us in our attempts to understand why certain TBI patients are at higher risk for neurodegenerative disorders than others. In the future, the brain scans of concussion victims may even help scientists to early identify such high-risk individuals, whether they are civilians, athletes or members of the armed forces. As a neuroimaging researcher, my primary interest is understanding how concussions and other forms of TBI can alter brain aging and even increase the risk of neurodegenerative conditions. I am an Assistant Professor of Gerontology and Neuroscience at the USC Leonard Davis School of Gerontology in Los Angeles, California. Throughout my career, I have been involved in the development of novel image processing and visualization strategies for multimodal brain imaging [via magnetic resonance imaging (MRI), diffusion tensor imaging (DTI), computed tomography (CT), etc.], for studying the human connectome and for quantifying the effects of TBI and neurodegenerative diseases upon brain structure and function. I and my colleagues have pioneered the connectogram, which is an award-winning approach to the visualization, exploration and quantification of white matter circuitry in the human brain. I am also interested in the relationship between cardiovascular disease and brain health, as quantified in populations with atypical aging trajectories, such as the Tsimane people of Bolivia. Throughout the years, my research has required the use of a vast array of theoretical, experimental and computational approaches, ranging from nonlinear dynamics and machine learning to electro- and magnetoencephalography.
© Andrei Irimia, Ph.D. (2000-present)