Bayesian方法对fMRI数据的多层群组分析

摘要

This paper suggests a method to process fMRI time series based on Bayesian inference for group analysis. The method uses multilevel divided by voxel, subject and group as pair comparison to reinforce posterior probability in group analysis from single subjects as priors. And also it combines classical statistics, i.e., t-test to obtain voxel activation at subject level as prior for Bayesian inference at group level. It effectively solves computation expensive and complexity. And it shows robust on Bayesian inference for group analysis.%本文采用Bayesian方法对fMRI时间序列数据对群组进行分析，群组按照体素、脑体、个体分为多层，比较个体的特征选取作为先验加强群组的后验计算，对个体的参数估计结合经典统计方法获得体素的激活区域作为群组Bayesian推理的先验，可以有效解决计算复杂性和计算成本，有效应用在群组分析中。