Speaker
Dr. Andrew Brown
Associate Professor of Statistics
Clemson University
Date
Friday, March 28, 2025
11:00 A.M. – 12:00 P.M. ET
Location
Jajodia Auditorium, Room 1101
Nguyen Engineering Building
4511 Patriot Circle
Fairfax, Virginia 22030
On Bayesian approaches to brain activity mapping with complex-valued fMRI data
Abstract
Functional magnetic resonance imaging (fMRI) enables indirect detection of brain activity changes via the blood-oxygen-level-dependent (BOLD) signal. Conventional analysis methods mainly rely on the real-valued magnitude of these signals. In contrast, research suggests that analyzing both real and imaginary components of the complex-valued fMRI (cv-fMRI) signal provides a more holistic approach that can increase power to detect neuronal activation. In this talk, I will discuss some recent work on Bayesian modeling for image reconstruction and task activation with cv-fMRI data. In the first part, I will discuss how the Bayesian framework can be leveraged to improve the image de-aliasing problem in the presence of unknown receiver intensities. The second part of the talk will present a Bayesian model for activity mapping that can accommodate temporal and spatial dynamics while facilitating efficient computation via partitioning and parallelized Markov chain Monte Carlo.
About the Speaker
Andrew Brown earned his MS and PhD in Statistics from the University of Georgia under the direction of Nicole Lazar and Gauri Datta. He subsequently took a faculty position in the School of Mathematical and Statistical Sciences at Clemson University where he is now an Associate Professor. He maintains research interests in functional and structural neuroimaging data analysis from his dissertation work, and has since expanded into uncertainty quantification, computer experiments, Bayesian computation, and inverse problems. This is in addition to collaborative work he has done in areas such as veterinary medicine, engineering design, and materials science. His research has been supported by the National Science Foundation and the Department of Education. He has served as an elected officer with Industrial Statistics section of the International Society for Bayesian Analysis, the Uncertainty Quantification Interest Group of the American Statistical Association, and is past president of the South Carolina chapter of the ASA. He has had visiting positions at the Statistical and Applied Mathematical Sciences Institute, the School of Industrial and Systems Engineering at Georgia Tech, and at Los Alamos National Laboratory.
Event Organizer
David Kepplinger
Assistant Professor, Department of Statistics
College of Engineering and Computing
George Mason University