Talk: Analytic approaches to study the chronnectome

Sun, 02 Oct 2016 13:37:32 -0400

Analytic approaches to study the chronnectome
(time-varying brain connectivity)

Recent years have witnessed a rapid growth in moving functional magnetic resonance imaging (fMRI) connectivity beyond simple scan-length averages into approaches that capture time-varying properties of connectivity. In this perspective we use the term “chronnectome” to describe such metrics that allow a dynamic view of coupling. We discuss the potential of these to improve characterization and understanding of brain function, which is inherently dynamic, not-well understood, and thus poorly suited to conventional scan-averaged connectivity measurements.

Prof. Vince Calhoun (EE Ph.D.’02, UMBC) is this year’s distinguished alum in the Engineering and Information Technology category and is the first speaker in our departmental seminar series.

Dr. Calhoun is currently Executive Science Officer at the Mind Research Network and a Distinguished Professor in the Department of Electrical and Computer Engineering at the University of New Mexico. He is the author of more than 450 full journal articles and over 550 technical reports, abstracts and conference proceedings. His work includes the development of flexible methods to analyze functional magnetic resonance imaging such as independent component analysis (ICA), data fusion of multimodal imaging and genetics data, and the identification of biomarkers for disease. Among other things, he leads an NIH P20 COBRE center grant on multimodal imaging of schizophrenia, bipolar disorder, and major depression as well as an NSF EPSCoR grant focused on brain imaging and epigenetics of adolescent development. Dr. Calhoun is a fellow of the Institute of Electrical and Electronic Engineers (IEEE), The Association for the Advancement of Science, The American Institute of Biomedical and Medical Engineers, The American College of Neuropsychopharmacology, and the International Society of Magnetic Resonance in Medicine. He is currently chair of the IEEE Machine Learning for Signal Processing (MLSP) technical committee.

Host: Tulay Adali

About the CSEE Seminar Series: The UMBC Department of Computer Science and Electrical Engineering presents technical talks on current significant research projects of broad interest to the Department and the research community. Each talk is free and open to the public. We welcome your feedback and suggestions for future talks.

Organizers: Tulay Adali and Alan Sherman