Group Analysis Based on Multilevel Bayesian for Fmri Data

This paper suggests one method to process fMRI time series based on Bayesian inference for group analysis. The method is based on Bayesian inference to divide group into multilevel by session, subject and group levels. It compares covariance to select prior to reinforce posterior probability in group analysis. At the same time it combines classical statistics, i.e., t-statistics to obtain voxel activation at subject level as prior for Bayesian inference at group level. Through the method, it can effectively decrease computation expensive and reduce complexity. Therefore the experimental results show robust on Bayesian inference for group analysis.