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Computational and Mathematical Methods in Medicine
Volume 2012 (2012), Article ID 967380, 14 pages
doi:10.1155/2012/967380
A Computationally Efficient, Exploratory Approach to Brain Connectivity Incorporating False Discovery Rate Control, A Priori Knowledge, and Group Inference
1Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC, V6T 1Z4, Canada
2Laboratory of Neuro Imaging, Department of Neurology, UCLA School of Medicine, Los Angeles, CA 90095, USA
3Division of Neurology, Department of Medicine and Pacific Parkinson's Research Centre, University of British Columbia, Vancouver, BC, V5Z 1M9, Canada
Received 18 March 2012; Revised 6 July 2012; Accepted 10 July 2012
Academic Editor: Tianzi Jiang
Copyright © 2012 Aiping Liu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
How to Cite this Article
Aiping Liu, Junning Li, Z. Jane Wang, and Martin J. McKeown, “A Computationally Efficient, Exploratory Approach to Brain Connectivity Incorporating False Discovery Rate Control, A Priori Knowledge, and Group Inference,” Computational and Mathematical Methods in Medicine, vol. 2012, Article ID 967380, 14 pages, 2012. doi:10.1155/2012/967380