title: Test-retest reliability of graph metrics in high-resolution functional connectomics: a resting-state functional MRI study.
abstract: BACKGROUND
  The combination of resting-state functional MRI (R-fMRI) technique and graph theoretical approaches has emerged as a promising tool for characterizing the topological organization of brain networks, that is, functional connectomics. In particular, the construction and analysis of high-resolution brain connectomics at a voxel scale are important because they do not require prior regional parcellations and provide finer spatial information about brain connectivity. However, the test-retest reliability of voxel-based functional connectomics remains largely unclear.
  
  
  OBJECTIVE
  This study tended to investigate both short-term (∼20 min apart) and long-term (6 weeks apart) test-retest (TRT) reliability of graph metrics of voxel-based brain networks.
  
  
  METHODS
  Based on graph theoretical approaches, we analyzed R-fMRI data from 53 young healthy adults who completed two scanning sessions (session 1 included two scans 20 min apart; session 2 included one scan that was performed after an interval of ∼6 weeks).
  
  
  RESULTS
  The high-resolution networks exhibited prominent small-world and modular properties and included functional hubs mainly located at the default-mode, salience, and executive control systems. Further analysis revealed that test-retest reliabilities of network metrics were sensitive to the scanning orders and intervals, with fair to excellent long-term reliability between Scan 1 and Scan 3 and lower reliability involving Scan 2. In the long-term case (Scan 1 and Scan 3), most network metrics were generally test-retest reliable, with the highest reliability in global metrics in the clustering coefficient and in the nodal metrics in nodal degree and efficiency.
  
  
  CONCLUSIONS
  We showed high test-retest reliability for graph properties in the high-resolution functional connectomics, which provides important guidance for choosing reliable network metrics and analysis strategies in future studies.
authors.affiliation: Department of E.E., Tsinghua National Laboratory for Information Science and Technology (TNList), Center for Brain Inspired Computing Research (CBICR), Tsinghua University, Beijing, China.
authors.forename: Hai-Xiao
authors.initials: HX
authors.lastname: Du
authors.affiliation: State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.
authors.forename: Xu-Hong
authors.initials: XH
authors.lastname: Liao
authors.affiliation: State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.
authors.forename: Qi-Xiang
authors.initials: QX
authors.lastname: Lin
authors.affiliation: Department of E.E., Tsinghua National Laboratory for Information Science and Technology (TNList), Center for Brain Inspired Computing Research (CBICR), Tsinghua University, Beijing, China.
authors.forename: Gu-Shu
authors.initials: GS
authors.lastname: Li
authors.affiliation: Department of E.E., Tsinghua National Laboratory for Information Science and Technology (TNList), Center for Brain Inspired Computing Research (CBICR), Tsinghua University, Beijing, China.
authors.forename: Yu-Ze
authors.initials: YZ
authors.lastname: Chi
authors.affiliation: Department of E.E., Tsinghua National Laboratory for Information Science and Technology (TNList), Center for Brain Inspired Computing Research (CBICR), Tsinghua University, Beijing, China.
authors.forename: Xiang
authors.initials: X
authors.lastname: Liu
authors.affiliation: Department of E.E., Tsinghua National Laboratory for Information Science and Technology (TNList), Center for Brain Inspired Computing Research (CBICR), Tsinghua University, Beijing, China.
authors.forename: Hua-Zhong
authors.initials: HZ
authors.lastname: Yang
authors.affiliation: Department of E.E., Tsinghua National Laboratory for Information Science and Technology (TNList), Center for Brain Inspired Computing Research (CBICR), Tsinghua University, Beijing, China.
authors.forename: Yu
authors.initials: Y
authors.lastname: Wang
authors.affiliation: State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.
authors.forename: Ming-Rui
authors.initials: MR
authors.lastname: Xia
mesh_terms: D000328:Adult; D001921:Brain / Q000502:physiology*; D063132:Connectome / Q000379:methods*; D005260:Female; D019416:Head Movements; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D009434:Neural Pathways / Q000502:physiology; D015203:Reproducibility of Results; D012146:Rest; D013997:Time Factors; D055815:Young Adult
keywords: Connectomics; Functional connectivity; Graph theory; Hub; Small world; Test-retest