Multilevel Group Analysis on Bayesian in fMRI Time Series

被引：0

作者：

Yang, Feng ^{[1
]}

Fu, Kuang ^{[2
]}

Zhou, Ai ^{[3
]}

机构：

[1] Heilongjiang Univ, Sch Comp Sci & Technol, Harbin, Heilongjiang, Peoples R China

[2] Harbin Med Univ, Affiliated Hosp 2, Harbin, Heilongjiang, Peoples R China

[3] Jilin Univ, Coll Human, Changchun, Jilin, Peoples R China

来源：

PROCEEDINGS OF THE 2014 9TH INTERNATIONAL CONFERENCE ON COMPUTER VISION, THEORY AND APPLICATIONS (VISAPP 2014), VOL 3 | 2014年

关键词：

fMRI Time Series; Classical Statistics; Bayesian Inference; Group Analysis; INFERENCE;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper suggests one method to process fMRI time series based on Bayesian inference for group analysis. The method uses multilevel divided by session, 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 solved computation expensive and complexity. And it shows robust on Bayesian inference for group analysis.

引用

页码：91 / 97

页数：7

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