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

Zuo, X.-N., Anderson, J. S., Bellec, P., Birn, R. M., Biswal, B. B., Blautzik, J., et al. (2014). An open science resource for establishing reliability and reproducibility in functional connectomics. Scientific Data, 1: 140049. doi:10.1038/sdata.2014.49.

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Zuo, Xi-Nian1, Author
Anderson, Jeffrey S.1, Author
Bellec, Pierre1, Author
Birn, Rasmus M.1, Author
Biswal, Bharat B.1, Author
Blautzik, Janusch1, Author
Breitner, John C.S.1, Author
Buckner, Randy L.1, Author
Calhoun, Vince D.1, Author
Castellanos, F. Xavier1, Author
Chen, Antao1, Author
Chen, Bing1, Author
Chen, Jiangtao1, Author
Chen, Xu1, Author
Colcombe, Stanley J.1, Author
Courtney, William1, Author
Craddock, R. Cameron1, Author
Martino, Adriana Di1, Author
Dong, Hao-Ming1, Author
Fu, Xiaolan1, Author
Gong, Qiyong1, AuthorGorgolewski, Krzysztof J.2, Author           Han, Ying1, AuthorHe, Ye1, AuthorHe, Yong1, AuthorHo, Erica1, AuthorHolmes, Avram1, AuthorHou, Xiao-Hui1, AuthorHuckins, Jeremy1, AuthorJiang, Tianzi1, AuthorJiang, Yi1, AuthorKelley, William1, AuthorKelly, Clare1, AuthorKing, Margaret1, AuthorLaConte, Stephen M.1, AuthorLainhart, Janet E.1, AuthorLei, Xu1, AuthorLi, Hui-Jie1, AuthorLi, Kaiming1, AuthorLi, Kuncheng1, AuthorLin, Qixiang1, AuthorLiu, Dongqiang1, AuthorLiu, Jia1, AuthorLiu, Xun1, AuthorLiu, Yijun1, AuthorLu, Guangming1, AuthorLu, Jie1, AuthorLuna, Beatriz1, AuthorLuo, Jing1, AuthorLurie, Daniel1, AuthorMao, Ying1, AuthorMargulies, Daniel S.2, Author           Mayer, Andrew R.1, AuthorMeindl, Thomas1, AuthorMeyerand, Mary E.1, AuthorNan, Weizhi1, AuthorNielsen, Jared A.1, AuthorO’Connor, David1, AuthorPaulsen, David1, AuthorPrabhakaran, Vivek1, AuthorQi, Zhigang1, AuthorQiu, Jiang1, AuthorShao, Chunhong1, AuthorShehzad, Zarrar1, AuthorTang, Weijun1, AuthorVillringer, Arno3, Author           Wang, Huiling1, AuthorWang, Kai1, AuthorWei, Dongtao1, AuthorWei, Gao-Xia1, AuthorWeng, Xu-Chu1, AuthorWu, Xuehai1, AuthorXu, Ting1, AuthorYang, Ning1, AuthorYang, Zhi1, AuthorZang, Yu-Feng1, AuthorZhang, Lei1, AuthorZhang, Qinglin1, AuthorZhang, Zhe1, AuthorZhang, Zhiqiang1, AuthorZhao, Ke1, AuthorZhen, Zonglei1, AuthorZhou, Yuan1, AuthorZhu, Xing-Ting1, AuthorMilham, Michael P.1, Author more..
Affiliations:
1External Organizations, ou_persistent22              
2Max Planck Research Group Neuroanatomy and Connectivity, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_1356546              
3Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634549              

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Free keywords: Brain imaging; Cognitive neuroscience; Computational neuroscience; Functional magnetic resonance imaging
 Abstract: 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.

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Language(s): eng - English
 Dates: 2014-06-192014-10-142014-12-09
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1038/sdata.2014.49
PMID: 25977800
PMC: PMC4421932
Other: eCollection 2014
 Degree: -

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Title: Scientific Data
  Abbreviation : Sci. Data
Source Genre: Journal
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Publ. Info: London, United Kingdom : Nature Publishing Group
Pages: - Volume / Issue: 1 Sequence Number: 140049 Start / End Page: - Identifier: Other: 2052-4463
CoNE: https://pure.mpg.de/cone/journals/resource/2052-4463