4.7 Article

Best practices in data analysis and sharing in neuroimaging using MRI

期刊

NATURE NEUROSCIENCE
卷 20, 期 3, 页码 299-303

出版社

NATURE PORTFOLIO
DOI: 10.1038/nn.4500

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资金

  1. Wellcome Trust [100309/Z/12/Z]
  2. NIH [R01 NS075066-01A1, R01 EB015611-01, U01 MH099059, R01 AG047596]
  3. Singapore MOE Tier 2 [MOE2014-T2-2-016]
  4. NUS [DPRT/944/09/14, R185000271720]
  5. NMRC [CBRG14nov007]
  6. NUS YIA
  7. Deutsche Forschungsgemeinschaft (DFG) [EI 816/4-1, LA 3071/3-1, EI 816/6-1]
  8. National Institute of Mental Health [R01-MH074457]
  9. European Union Seventh Framework Programme (FP7) [604102]
  10. German federal state of Saxony-Anhalt
  11. CRCNS BMBF/NSF [01GQ1411/1429999]
  12. UK Medical Research Council
  13. European Research Council Starting Grant [261352]
  14. Irving Ludmer Family Foundation
  15. Ludmer Centre for Neuroinformatics and Mental Health
  16. ZonMw TOP grant [91211021]
  17. Laura and John Arnold Foundation
  18. NIBIB [P41EB019936]
  19. NIH-National Institute on Drug Abuse [U24DA038653]
  20. Helmholtz Portfolio Theme 'Supercomputing and Modeling for the Human Brain'
  21. European Regional Development Fund (ERDF)
  22. MRC [MC_U105597120] Funding Source: UKRI
  23. European Research Council (ERC) [261352] Funding Source: European Research Council (ERC)

向作者/读者索取更多资源

Given concerns about the reproducibility of scientific findings, neuroimaging must define best practices for data analysis, results reporting, and algorithm and data sharing to promote transparency, reliability and collaboration. We describe insights from developing a set of recommendations on behalf of the Organization for Human Brain Mapping and identify barriers that impede these practices, including how the discipline must change to fully exploit the potential of the world's neuroimaging data.

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