Research Article A Resting-State Brain Functional Network Study in MDD Based on Minimum Spanning Tree Analysis and the Hierarchical Clustering Xiaowei Li, 1 Zhuang Jing, 1 Bin Hu, 1 Jing Zhu, 1 Ning Zhong, 2 Mi Li, 2 Zhijie Ding, 3 Jing Yang, 4 Lan Zhang, 4 Lei Feng, 5 and Dennis Majoe 6 1 School of Information Science & Engineering, Lanzhou University, Lanzhou, China 2 International WIC Institute, Beijing University of Technology, Beijing, China 3 Te Tird People’s Hospital of Tianshui City, Tianshui, China 4 Lanzhou University Second Hospital, Lanzhou, China 5 Beijing Anding Hospital of Capital Medical University, Beijing, China 6 Computer Systems Institute, ETH Z¨ urich, Z¨ urich, Switzerland Correspondence should be addressed to Bin Hu; bh@lzu.edu.cn Received 31 March 2017; Revised 3 June 2017; Accepted 12 June 2017; Published 25 July 2017 Academic Editor: Jianxin Wang Copyright © 2017 Xiaowei Li et al. Tis 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. A large number of studies demonstrated that major depressive disorder (MDD) is characterized by the alterations in brain functional connections which is also identifable during the brain’s “resting-state.” But, in the present study, the approach of constructing functional connectivity is ofen biased by the choice of the threshold. Besides, more attention was paid to the number and length of links in brain networks, and the clustering partitioning of nodes was unclear. Terefore, minimum spanning tree (MST) analysis and the hierarchical clustering were frst used for the depression disease in this study. Resting-state electroencephalogram (EEG) sources were assessed from 15 healthy and 23 major depressive subjects. Ten the coherence, MST, and the hierarchical clustering were obtained. In the theta band, coherence analysis showed that the EEG coherence of the MDD patients was signifcantly higher than that of the healthy controls especially in the lef temporal region. Te MST results indicated the higher leaf fraction in the depressed group. Compared with the normal group, the major depressive patients lost clustering in frontal regions. Our fndings suggested that there was a stronger brain interaction in the MDD group and a lef-right functional imbalance in the frontal regions for MDD controls. 1. Introduction Major depressive disorder is a global mental disorder and has an unfavourable infuence on physical and psycholog- ical health [1]. In addition to profound personal sufering, MDD patients lack the necessary social and occupational functioning [2]. Moreover, Te World Health Organization predicted that depression would become the second leading cause of illness by the year 2020 [3]. In this light, exploring the neurobiological signature of MDD from multiple imaging modalities was considered to sharpen the reach of depression and develop treatments, including electroencephalogram (EEG), magnetoencephalogram (MEG), functional magnetic resonance imaging (fMRI), positron emission tomography (PET), and single photon emission computed tomography (SPECT) [4]. In recent years, the research results of MDD based on diferent approaches had been presented substan- tially such as frontal EEG asymmetry, “small-word” network characteristics, and increased/disrupted cognition connectiv- ity network [5–8]. Tese results revealed neurophysiology characteristics in diferent aspects for depression disease and made a great contribution to the study of the depression. However, there were disputes and contradictions in these results due to the diferences of subjects, experimental envi- ronment, methods, and other restrictions. So, more methods and techniques are expected for exploring MDD. Hindawi Complexity Volume 2017, Article ID 9514369, 11 pages https://doi.org/10.1155/2017/9514369