Multilevel Group Analysis on Bayesian in fMRI Time Series

Feng Yang, Kuang Fu, Ai Zhou

Abstract

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.

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Paper Citation


in Harvard Style

Yang F., Fu K. and Zhou A. (2014). Multilevel Group Analysis on Bayesian in fMRI Time Series . In Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2014) ISBN 978-989-758-009-3, pages 91-97. DOI: 10.5220/0004655000910097


in Bibtex Style

@conference{visapp14,
author={Feng Yang and Kuang Fu and Ai Zhou},
title={Multilevel Group Analysis on Bayesian in fMRI Time Series},
booktitle={Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2014)},
year={2014},
pages={91-97},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004655000910097},
isbn={978-989-758-009-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2014)
TI - Multilevel Group Analysis on Bayesian in fMRI Time Series
SN - 978-989-758-009-3
AU - Yang F.
AU - Fu K.
AU - Zhou A.
PY - 2014
SP - 91
EP - 97
DO - 10.5220/0004655000910097