Speaker: Professor Vince Calhoun

Title: Dynamic connectivity in rest fMRI: Approaches, examples and extensions to multimodal data fusion

Abstract: Approaches for estimating time-varying connectivity from fMRI data have grown in popularity in recent years, however there are still some outstanding questions about the estimation approaches and underlying cause of these changes. In this talk I will review approaches for estimating dynamic connectivity from resting fMRI including an evaluation of the various assumptions that are being made. I will discuss several strategies including the use of windowed correlation, time-frequency approaches, and newer window-less approaches. Results from a large replication study will be presented. Results from several large patient studies will also be discussed. And finally, I will discuss extensions of dynamic connectivity to link to multimodal imaging and genetic data.

Speaker Bio: Dr. Calhoun is the founding director of the tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS; http://www.trendscenter.org), a joint effort between Georgia State, Georgia Tech, and Emory University, which is focused on improving our understanding of the human brain using advanced analytic approaches with an emphasis on translational research such as the development of predictive biomarkers for mental and neurological disorders. The use of big data approaches and neuroinformatics tools to capture, manage, analyze, and share data is also a major emphasis. Previously, Dr. Calhoun worked as a research engineer in the psychiatric neuroimaging laboratory at Johns Hopkins, served as the director of medical image analysis at the Olin Neuropsychiatry Research Center, and as an associate professor at Yale University. Most recently, he was a Distinguished Professor at the University of New Mexico and the President of the Mind Research Network. Dr. Calhoun received a bachelor’s degree in electrical engineering from the University of Kansas, master’s degrees in biomedical engineering and information systems from Johns Hopkins University in 1993 and 1996, and the Ph.D. degree in EE from the University of Maryland Baltimore County in 2002.