MATLAB Toolbox for the Analysis of fMRI Data: A Bayesian Spatial Model for Activation and Connectivity

• Activity Number: 536
• Type: Contributed
• Date/Time: Wednesday, August 4, 2010 : 10:30 AM to 12:20 PM
• Sponsor: Section on Bayesian Statistical Science
• Author(s): Lijun Zhang*+ and Sanjay Agravat and Gordana Derado and DuBois Bowman
• Companies: Emory University and Emory University and Emory University and Emory University
• Keywords: Functional magnetic resonance imaging (fMRI) ; Bayesian spatial model ; Functional connectivity ; Activation analyses

Abstract

We present a graphical visualization and statistical MATLAB toolbox for the analysis of fMRI data, called the Bayesian Spatial Model for activation and connectivity (BSMac). BSMac simultaneously performs whole-brain activation analyses at voxel and region of interest levels as well as functional connectivity (FC) analyses using a flexible Bayesian modeling framework (Bowman et al., 2008). BSMac allows input data in either Analyze or Nifti file formats. The user also provides information pertaining to subgroup memberships, scanning sessions, and experimental tasks (stimuli), from which the design matrix is constructed. BSMac then performs parameter estimation based on MCMC methods and generates plots for activation and FC, such as interactive 2D maps of voxel and region-level task-related changes in activation, and animated 3D graphics of FC results. (http://www.sph.emory.edu/bios/CBIS).