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However, researchers who want to engage in centralized, large-scale data sharing and analysis must often contend with problems such as high database cost, long data transfer time, extensive manual effort, and privacy issues for sensitive data. To remove these barriers to enable easier data sharing and analysis, we introduced a new, decentralized, privacy-enabled infrastructure model for brain imaging data called COINSTAC in 2016. We have continued development of COINSTAC since this model was first introduced. One of the challenges with such a model is adapting the required algorithms to function within a decentralized framework. In this paper, we report on how we are solving this problem, along with our progress on several fronts, including additional decentralized algorithms implementation, user interface enhancement, decentralized regression statistic calculation, and complete pipeline specifications.<\/ns4:p>","DOI":"10.12688\/f1000research.12353.1","type":"journal-article","created":{"date-parts":[[2017,8,18]],"date-time":"2017-08-18T07:21:05Z","timestamp":1503040865000},"page":"1512","update-policy":"https:\/\/doi.org\/10.12688\/f1000research.crossmark-policy","source":"Crossref","is-referenced-by-count":31,"title":["COINSTAC: Decentralizing the future of brain imaging 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Science Foundation (grant numbers: 1539067 and 1631819). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.","order":2,"name":"grant-information","label":"Grant Information"},{"value":"This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.","order":0,"name":"copyright-info","label":"Copyright"}]}}