Novel and Computationally Efficient Bayesian Methods in Neuroimaging

• Activity Number: 118
• Type: Topic Contributed
• Date/Time: Monday, August 5, 2013 : 8:30 AM to 10:20 AM
• Sponsor: Section on Bayesian Statistical Science
• Author(s): Theodore Kypraios*+
• Companies: University of Nottingham, United Kingdom
• Keywords: Bayesian Statistics ; Neuroimaging ; Markov Chain Monte Carlo ; DW-MRI ; fMRI

Abstract

The human brain is the most complex system encountered in living organisms. It is a network of more than 1e11 individual nerve cells and 1e16 interconnections. Due to the brain's complexity, many aspects of its function remain unclear. During the last decade there has been a significant amount of effort in developing mathematical/statistical models as well as methods with the aim to construct a map of the complete structural and functional neural connections in vivo within and across individuals. Given the recent advances in technologies the acquired brain images contain a growing amount on information. This talk is concerned with the development of novel efficient Bayesian methods in neuroimaging. Examples include models and methods for doing Global tractography using Diffusion-Weighted MRI data as well as fitting Exponential Random Graph Models to functional MRI (fMRI) data.