title: Altered anatomical patterns of depression in relation to antidepressant treatment: Evidence from a pattern recognition analysis on the topological organization of brain networks.
abstract: BACKGROUND
  Accumulated evidence has illuminated the topological infrastructure of major depressive disorder (MDD). However, the changes of topological properties of anatomical brain networks in remitted major depressive disorder patients (rMDD) remain an open question. The present study provides an exploratory examination of pattern changes among current major depressive disorder patients (cMDD), rMDD patients and healthy controls (HC) by means of a pattern recognition analysis.
  
  
  METHODS
  Twenty-eight cMDD patients (age range: 22-54, mean age: 39.57), 15 rMDD patients (age range: 23-53, mean age: 38.40) and 30 HC (23-54, mean age: 35.57) were enrolled. For each subject, we computed five kinds of weighted white matter (WM) networks via employing five physiological parameters (i.e. fractional anisotropy, mean diffusivity, λ1, λ2 and λ3) and then calculated three network measures of these weighted networks. We treated these measures as features and fed into a feature selection mechanism to choose the most discriminative features for linear support vector machine (SVM) classifiers.
  
  
  RESULTS
  Linear SVM could excellently distinguish the three groups with the 100% classification accuracy of recognizing cMDD/rMDD from HC, and 97.67% classification accuracy of recognizing cMDD from rMDD. The further pattern analysis found two types of discriminative patterns among cMDD, rMDD and HC. (i) Compared with HC, both cMDD and rMDD exhibited the similar deficit patterns of node strength primarily involving the salience network (SN), default mode network (DMN) and frontoparietal network (FPN). (ii) Compared with cMDD and rMDD showed the altered pattern of intra-communicability within DMN and inter-communicability between DMN and the other sub-networks including the visual recognition network (VRN) and SN.
  
  
  CONCLUSIONS
  The present study had a limited sample size and a lack of larger independent data set to validate the methods and confirm the findings.
  
  
  CONCLUSIONS
  These findings implied that the impairment of MDD was closely associated with the alterations of connections within SN, DMN and FPN, whereas the remission of MDD was benefitted from the network compensatory of intra-communication within DMN and inter-communication between DMN and the other sub-networks (i.e., VRN and SN).
authors.affiliation: Key Laboratory of Child Development and Learning Science (Ministry of Education), Research Centre for Learning Science, Southeast University, Si Pailou 2, Nanjing 210096, China.
authors.forename: Jiaolong
authors.initials: J
authors.lastname: Qin
authors.affiliation: Key Laboratory of Child Development and Learning Science (Ministry of Education), Research Centre for Learning Science, Southeast University, Si Pailou 2, Nanjing 210096, China.
authors.forename: Maobin
authors.initials: M
authors.lastname: Wei
authors.affiliation: Department of Psychiatry, Affiliated Nanjing Brain Hospital of Nanjing Medical University, No. 264 Guangzhou Road, Nanjing 210029, China.
authors.forename: Haiyan
authors.initials: H
authors.lastname: Liu
authors.affiliation: Department of Psychiatry, Affiliated Nanjing Brain Hospital of Nanjing Medical University, No. 264 Guangzhou Road, Nanjing 210029, China.
authors.forename: Jianhuai
authors.initials: J
authors.lastname: Chen
authors.affiliation: Department of Psychiatry, Affiliated Nanjing Brain Hospital of Nanjing Medical University, No. 264 Guangzhou Road, Nanjing 210029, China.
authors.forename: Rui
authors.initials: R
authors.lastname: Yan
authors.affiliation: Department of Psychiatry, Affiliated Nanjing Brain Hospital of Nanjing Medical University, No. 264 Guangzhou Road, Nanjing 210029, China; Nanjing Brain Hospital, Nanjing University Medical School, 22 Hankou Road, Nanjing 210093, China. Electronic address: zjyao@njmu.edu.cn.
authors.forename: Zhijian
authors.initials: Z
authors.lastname: Yao
authors.affiliation: Key Laboratory of Child Development and Learning Science (Ministry of Education), Research Centre for Learning Science, Southeast University, Si Pailou 2, Nanjing 210096, China; Suzhou Research Institute of Southeast University, 399 Linquan Street, Suzhou 215123, China. Electronic address: luq@seu.edu.cn.
authors.forename: Qing
authors.initials: Q
authors.lastname: Lu
mesh_terms: D000328:Adult; D016880:Anisotropy; D016022:Case-Control Studies; D003865:Major Depressive Disorder / Q000473:pathology*; D056324:Diffusion Tensor Imaging; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008297:Male; D008875:Middle Aged; D009434:Neural Pathways / Q000187:drug effects* / Q000473:pathology*; D059906:Neuroimaging; D012074:Remission Induction; D017367:Selective Serotonin Reuptake Inhibitors / Q000494:pharmacology* / Q000627:therapeutic use; D066127:White Matter / Q000187:drug effects* / Q000473:pathology*; D055815:Young Adult
chemical_list: D017367:Selective Serotonin Reuptake Inhibitors
keywords: Communicability; Diffusion tensor imaging; Graph theory; Network compensatory; Remitted major depressive disorder; Support vector machine