title: MIC as an appropriate method to construct the brain functional network.
abstract: 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.
authors.affiliation: Key Laboratory of Magnetic Resonance in Biological Systems, Wuhan Institute of Physics and Mathematics, Chinese Academy of Sciences, Wuhan 430071, China ; University of Chinese Academy of Sciences, Beijing 100049, China.
authors.forename: Ziqing
authors.identifier: 0000-0002-3946-3518
authors.initials: Z
authors.lastname: Zhang
authors.affiliation: School of Mathematics and Statistics, Wuhan University, Wuhan 430072, China.
authors.forename: Shu
authors.identifier: 0000-0001-9138-051X
authors.initials: S
authors.lastname: Sun
authors.affiliation: Key Laboratory of Magnetic Resonance in Biological Systems, Wuhan Institute of Physics and Mathematics, Chinese Academy of Sciences, Wuhan 430071, China.
authors.forename: Ming
authors.initials: M
authors.lastname: Yi
authors.affiliation: College of Information Science and Technology, Beijing Normal University, Beijing 100875, China ; State Key Laboratories of Transducer Technology, Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, China.
authors.forename: Xia
authors.initials: X
authors.lastname: Wu
authors.affiliation: Key Laboratory of Magnetic Resonance in Biological Systems, Wuhan Institute of Physics and Mathematics, Chinese Academy of Sciences, Wuhan 430071, China.
authors.forename: Yiming
authors.identifier: 0000-0002-7029-8207
authors.initials: Y
authors.lastname: Ding
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000465:Algorithms; D001921:Brain / Q000502:physiology*; D003198:Computer Simulation; D063132:Connectome / Q000379:methods*; D003627:Data Interpretation, Statistical; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008875:Middle Aged; D008959:Models, Neurological; D015233:Models, Statistical; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D055815:Young Adult