Dr. Inga Taylor was born in Washington, D.C. on December 28, 1943 to Karin G. and Rufus L. Taylor, Jr. After receiving her Bachelor’s degree from the University of Maryland, she went on to study at the Medical University of South Carolina, where she would earn her M.D. Dr. Taylor served a three year residency at the university, during which her final year, was named Chief Resident and Teaching Fellow. She was appointed to the faculty of the Department of Psychiatry and Behavioral Sciences in 1975, becoming a highly active member of the faculty. Dr. Taylor was involved in college of medicine and departmental committee work, in community and education service, and in church work. She was also a Diplomate of the American Board of Psychiatry and Neurology, and by 1980 had risen to the academic rank of Associate Professor. In 1971, she married Kenneth M. Klyce, and they had a daughter, Karin. H. Klyce, in 1973. Dr. Taylor successfully combined a productive career in medicine with her life as a wife and mother, and with her active involvement and interests in her church, her community, and the arts. Although she passed at the age of thirty-six to cancer, Dr. Taylor is remembered for living an energetic and productive life. Her energy made her a person who was both effective in her personal and professional spheres and unfailingly stimulating to those who knew her.
Join us as we host Dr. Martin Paulus. Computational psychiatry is a burgeoning field that utilizes mathematical approaches to investigate psychiatric disorders, derive quantitative predictions, and integrate data across multiple levels of description. Three examples of computational approaches will be presented. First, a simple computational model for anxiety will be reviewed that focuses on the reduced ability of anxious individuals to adjust their learning rate as a function of volatility. Second, a Bayesian Decision-Making model will be presented that can be used to predict the propensity of methamphetamine dependent individuals to relapse. Third, a multilevel Bayesian Group Factor Analysis approach will be used to show how multiple variables can be used to relate media behavior in youth to brain development. Taken together, these examples serve as a template to make progress in using computational approaches to make clinically relevant predictions and to deepen our understanding of the underlying neural processes.
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