Computational Neuroscience

Computational neuroscience (CN) is strictly defined as the quantitative understanding of the function of the brain at the level of neuronal dynamics and neural networks. Natural outputs of CN studies are dynamic network models of brain regions or processes that, via computer simulation, provide a theoretical foundation and technology that enhances our understanding of their function. Emerging studies demonstrate the utility of CN to drug discovery and understanding of drug action/interaction.

Translated into the clinical environment of the Department of Psychiatry and Neurobehavioral Sciences, this definition is both narrowed and expanded by simultaneously focusing on area of strength at UVA and accounting for the diversity of studies in our department:

• The basic research focus area is on neural networks and feedback bioprocesses in health and disease, particularly on neuroendocrine control networks;
• The translational research focus is on eHealth, investigating the application and the utility of new technology into health care;
• An essential CN function is also the computational support to clinical studies in the department, accompanied by teaching and outreach activities.

Thus, the Computational Neuroscience section joins several complementary, cutting-edge, technology-related translational research and clinical areas with an underlying focus in neuroscience, neuroendocrinology, psychiatry and behavioral medicine creating a very unique and stimulating division, which helps put our department in the forefront of psychiatry and technology. It includes the Divisions of Quantitative Neuroendocrinology, Behavioral Health & Technology, and Behavioral Informatics:

• Behavioral Health & Technology is the bridging of healthcare and technology.  The primary focus of this area is in the development and testing of Internet health interventions.  These currently include interventions for insomnia, pediatric encopresis, and type 1 diabetes.  In addition, this division concentrates on the use of cutting-edge technologies in research and clinical care, such as the use of the Internet and hand held computers for prospective data collection.
• The staff at the Center for Diabetes Technology understand where the treatment of type 1 diabetes is headed tomorrow. Our familiarity with current technology and our advancement and innovation of new technology, gives us a special perspective not offered anywhere else. Here, current technologies and new developments come together to advance the future of diabetes care.