An open science resource for establishing reliability and reproducibility in functional connectomics

Xi Nian Zuo, Jeffrey S. Anderson, Pierre Bellec, Rasmus M. Birn, Bharat B. Biswal, Janusch Blautzik, John C.S. Breitner, Randy L. Buckner, Vince D. Calhoun, F. Xavier Castellanos, Antao Chen, Bing Chen, Jiangtao Chen, Xu Chen, Stanley J. Colcombe, William Courtney, R. Cameron Craddock, Adriana Di Martino, Hao Ming Dong, Xiaolan FuQiyong Gong, Krzysztof J. Gorgolewski, Ying Han, Ye He, Yong He, Erica Ho, Avram Holmes, Xiao Hui Hou, Jeremy Huckins, Tianzi Jiang, Yi Jiang, William Kelley, Clare Kelly, Margaret King, Stephen M. LaConte, Janet E. Lainhart, Xu Lei, Hui Jie Li, Kaiming Li, Kuncheng Li, Qixiang Lin, Dongqiang Liu, Jia Liu, Xun Liu, Yijun Liu, Guangming Lu, Jie Lu, Beatriz Luna, Jing Luo, Daniel Lurie, Ying Mao, Daniel S. Margulies, Andrew R. Mayer, Thomas Meindl, Mary E. Meyerand, Weizhi Nan, Jared A. Nielsen, David O'Connor, David Paulsen, Vivek Prabhakaran, Zhigang Qi, Jiang Qiu, Chunhong Shao, Zarrar Shehzad, Weijun Tang, Arno Villringer, Huiling Wang, Kai Wang, Dongtao Wei, Gao Xia Wei, Xu Chu Weng, Xuehai Wu, Ting Xu, Ning Yang, Zhi Yang, Yu Feng Zang, Lei Zhang, Qinglin Zhang, Zhe Zhang, Zhiqiang Zhang, Ke Zhao, Zonglei Zhen, Yuan Zhou, Xing Ting Zhu, Michael P. Milham

Research output: Contribution to journalArticlepeer-review

290 Scopus citations


Efforts to identify meaningful functional imaging-based biomarkers are limited by the ability to reliably characterize inter-individual differences in human brain function. Although a growing number of connectomics-based measures are reported to have moderate to high test-retest reliability, the variability in data acquisition, experimental designs, and analytic methods precludes the ability to generalize results. The Consortium for Reliability and Reproducibility (CoRR) is working to address this challenge and establish test-retest reliability as a minimum standard for methods development in functional connectomics. Specifically, CoRR has aggregated 1,629 typical individuals' resting state fMRI (rfMRI) data (5,093 rfMRI scans) from 18 international sites, and is openly sharing them via the International Data-sharing Neuroimaging Initiative (INDI). To allow researchers to generate various estimates of reliability and reproducibility, a variety of data acquisition procedures and experimental designs are included. Similarly, to enable users to assess the impact of commonly encountered artifacts (for example, motion) on characterizations of inter-individual variation, datasets of varying quality are included.

Original languageEnglish (US)
Article number140049
JournalScientific Data
StatePublished - Dec 9 2014

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Information Systems
  • Education
  • Computer Science Applications
  • Statistics, Probability and Uncertainty
  • Library and Information Sciences


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