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BioMed Research International
Volume 2015 (2015), Article ID 825136, 10 pages
Research Article

MIC as an Appropriate Method to Construct the Brain Functional Network

1Key Laboratory of Magnetic Resonance in Biological Systems, Wuhan Institute of Physics and Mathematics, Chinese Academy of Sciences, Wuhan 430071, China
2University of Chinese Academy of Sciences, Beijing 100049, China
3School of Mathematics and Statistics, Wuhan University, Wuhan 430072, China
4College of Information Science and Technology, Beijing Normal University, Beijing 100875, China
5State Key Laboratories of Transducer Technology, Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, China

Received 29 July 2014; Revised 12 October 2014; Accepted 14 October 2014

Academic Editor: Yoshiki Kaneoke

Copyright © 2015 Ziqing Zhang 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.


Using an effective method to measure the brain functional connectivity is an important step to study the brain functional network. The main methods for constructing an undirected brain functional network include correlation coefficient (CF), partial correlation coefficient (PCF), mutual information (MI), wavelet correlation coefficient (WCF), and coherence (CH). In this paper we demonstrate that the maximal information coefficient (MIC) proposed by Reshef et al. is relevant to constructing a brain functional network because it performs best in the comprehensive comparisons in consistency and robustness. Our work can be used to validate the possible new functional connection measures.