Cart (Loading....) | Create Account
Close category search window
 

A Framework for Group Analysis of fMRI Data using Dynamic Bayesian Networks

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Junning Li ; Univ. of British Columbia, Vancouver ; Wang, J. ; McKeown, M.J.

FMRI experiments are usually performed to make inferences about groups of subjects, but current group analysis methods for dynamic Bayesian networks (DBNs) do not easily allow incorporation of covariates of interest. In this paper, we propose a group-analysis method which uses multivariate analysis of variance (MANOVA) to address this issue. The method is performed in two stages: first, deriving a DBN connectivity network among brain regions for each subject separately; second, regressing the connectivity coefficients of DBNs to the factors of interest and performing MANOVA. A case study involving fMRI data from Parkinson's disease (PD) subjects yields promising results. Ten out of the thirteen potential connections between regions of interest (ROIs) which are associated with disease state are functionally improved after medication (Table I), consistent with clinical observations. The results confirm that improvement in PD symptoms after medications is in part mediated by enhanced functional brain connectivity between brain regions.

Published in:

Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE

Date of Conference:

22-26 Aug. 2007

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.