Making big data open: Data sharing in neuroimaging

Nature Neuroscience

Volumn 17, Issue 11, 2014, Pages 1510-1517

  Poldrack, Russell A ^a   Gorgolewski, Krzysztof J ^a,b  

^a STANFORD UNIVERSITY   (United States)

^b MAX PLANCK INSTITUTE FOR HUMAN COGNITIVE AND BRAIN SCIENCES   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

CALIBRATION; COGNITION; ELECTROENCEPHALOGRAPHY; FUNCTIONAL MAGNETIC RESONANCE IMAGING; FUNDING; GENE SEQUENCE; GENETIC ANALYSIS; HUMAN; MAGNETOENCEPHALOGRAPHY; NEUROIMAGING; QUALITY CONTROL; REVIEW; BRAIN; FACTUAL DATABASE; INFORMATION DISSEMINATION; INFORMATION PROCESSING; NUCLEAR MAGNETIC RESONANCE IMAGING;

BRAIN; DATA COLLECTION; DATABASES, FACTUAL; HUMANS; INFORMATION DISSEMINATION; MAGNETIC RESONANCE IMAGING; NEUROIMAGING;

EID: 84908520795     PISSN: 10976256     EISSN: 15461726     Source Type: Journal    
DOI: 10.1038/nn.3818     Document Type: Review

References (68)

1. Van Essen, D.C. et al. The WU-Minn human connectome project: an overview. Neuroimage 80, 62-79 (2013
2. Poline, J.-B. et al. Data sharing in neuroimaging research. Front. Neuroinform. 6, 9 (2012
3. Keator, D.B. et al. Towards structured sharing of raw and derived neuroimaging data across existing resources. Neuroimage 82, 647-661 (2013
4. Mennes, M., Biswal, B.B., Castellanos, F.X. & Milham, M.P. Making data sharing work: The FCP/INDI experience. Neuroimage 82, 683-691 (2013
5. Brakewood, B. & Poldrack, R.A. The ethics of secondary data analysis: considering the application of Belmont Principles to the sharing of neuroimaging data. Neuroimage 82, 671-676 (2013
6. Posner, M.I., Petersen, S.E., Fox, P.T. & Raichle, M.E. Localization of cognitive operations in the human brain. Science 240, 1627-1631 (1988
7. Poldrack, R.A. Mapping mental function to brain structure: how can cognitive neuroimaging succeed?. Perspect. Psychol. Sci. 5, 753-761 (2010
8. Lloyd, D. Functional MRI and the study of human consciousness. J. Cogn. Neurosci. 14, 818-831 (2002
9. Poldrack, R.A., Halchenko, Y.O. & Hanson, S.J. Decoding the large-scale structure of brain function by classifying mental states across individuals. Psychol. Sci. 20, 1364-1372 (2009
10. Schwartz, Y., Thirion, B. & Varoquaux, G. Mapping paradigm ontologies to and from the brain. Adv. Neural. Inf. Process. Syst. 26, 1673-1681 (2013
11. Poldrack, R.A. et al. Discovering relations between mind, brain, and mental disorders using topic mapping. PLoS Comput. Biol. 8, e1002707 (2012
12. Anonymous. Announcement: reducing our irreproducibility. Nature 496, 398 (2013
13. Anonymous. How science goes wrong. The Economist (19 October 2013
14. Button, K.S. et al. Power failure: why small sample size undermines the reliability of neuroscience. Nat. Rev. Neurosci. 14, 365-376 (2013
15. Ioannidis, J.P.A. Why most published research findings are false. PLoS Med. 2, e124 (2005
16. David, S.P. et al. Potential reporting bias in FMRI studies of the brain. PLoS ONE 8, e70104 (2013
17. Medland, S.E., Jahanshad, N., Neale, B.M. & Thompson, P.M. Whole-genome analyses of whole-brain data: working within an expanded search space. Nat. Neurosci. 17, 791-800 (2014
18. Carp, J. On the plurality of (methodological) worlds: estimating the analytic flexibility of fMRI experiments. Front. Neurosci. 6, 149 (2012
19. Ioannidis, J.P.A. Why most discovered true associations are inflated. Epidemiology 19, 640-648 (2008
20. Kriegeskorte, N., Lindquist, M.A., Nichols, T.E., Poldrack, R.A. & Vul, E. Everything you never wanted to know about circular analysis, but were afraid to ask. J. Cereb. Blood Flow Metab. 30, 1551-1557 (2010
21. Kriegeskorte, N., Simmons, W.K., Bellgowan, P.S.F. & Baker, C.I. Circular analysis in systems neuroscience: the dangers of double dipping. Nat. Neurosci. 12, 535-540 (2009
22. Vul, E., Harris, C., Winkielman, P. & Pashler, H. Puzzlingly high correlations in fMRI studies of emotion, personality, and social cognition. Perspect. Psychol. Sci. 4, 274-290 (2009
23. Simmons, J.P., Nelson, L.D. & Simonsohn, U. False-positive psychology: undisclosed flexibility in data collection and analysis allows presenting anything as significant. Psychol. Sci. 22, 1359-1366 (2011
24. Wicherts, J.M., Bakker, M. & Molenaar, D. Willingness to share research data is related to the strength of the evidence and the quality of reporting of statistical results. PLoS ONE 6, e26828 (2011
25. Biswal, B.B. et al. Toward discovery science of human brain function. Proc. Natl. Acad. Sci. USA 107, 4734-4739 (2010
26. Tomasi, D. & Volkow, N.D. Functional connectivity density mapping. Proc. Natl. Acad. Sci. USA 107, 9885-9890 (2010
27. Rubinov, M. & Sporns, O. Weight-conserving characterization of complex functional brain networks. Neuroimage 56, 2068-2079 (2011
28. Yan, C.-G., Craddock, R.C., Zuo, X.-N., Zang, Y.-F. & Milham, M.P. Standardizing the intrinsic brain: towards robust measurement of inter-individual variation in 1,000 functional connectomes. Neuroimage 80, 246-262 (2013
29. Zuo, X.-N. et al. Network centrality in the human functional connectome. Cereb. Cortex 22, 1862-1875 (2012
30. Yeo, B.T.T., Krienen, F.M., Chee, M.W.L. & Buckner, R.L. Estimates of segregation and overlap of functional connectivity networks in the human cerebral cortex. Neuroimage 88C, 212-227 (2013
31. Zalesky, A., Fornito, A., Cocchi, L., Gollo, L.L. & Breakspear, M. Time-resolved resting-state brain networks. Proc. Natl. Acad. Sci. USA 111, 10341-10346 (2014
32. Webb, J.T., Ferguson, M.A., Nielsen, J.A. & Anderson, J.S. BOLD Granger causality reflects vascular anatomy. PLoS ONE 8, e84279 (2013
33. Salimi-Khorshidi, G., Smith, S.M., Keltner, J.R., Wager, T.D. & Nichols, T.E. Meta-analysis of neuroimaging data: a comparison of image-based and coordinate-based pooling of studies. Neuroimage 45, 810-823 (2009
34. Laird, A.R., Lancaster, J.L. & Fox, P.T. BrainMap: the social evolution of a human brain mapping database. Neuroinformatics 3, 65-78 (2005
35. Yarkoni, T., Poldrack, R.A., Nichols, T.E., Van Essen, D.C. & Wager, T.D. Large-scale automated synthesis of human functional neuroimaging data. Nat. Methods 8, 665-670 (2011
36. Van Horn, J.D. et al. The Functional Magnetic Resonance Imaging Data Center (fMRIDC): the challenges and rewards of large-scale databasing of neuroimaging studies. Phil. Trans. R. Soc. Lond. B 356, 1323-1339 (2001
37. Poldrack, R.A. et al. Toward open sharing of task-based fMRI data: the OpenfMRI project. Front. Neuroinform. 7, 12 (2013
38. Van Horn, J.D. & Gazzaniga, M.S. Why share data?. lessons learned from the fMRIDC. Neuroimage 82, 677-682 (2013
39. Marques, J.P. et al. MP2RAGE, a self bias-field corrected sequence for improved segmentation and T1-mapping at high field. Neuroimage 49, 1271-1281 (2010
40. Hoge, R.D. Calibrated fMRI. Neuroimage 62, 930-937 (2012
41. Gauthier, C.J., Desjardins-Crépeau, L., Madjar, C., Bherer, L. & Hoge, R.D. Absolute quantification of resting oxygen metabolism and metabolic reactivity during functional activation using QUO2 MRI. Neuroimage 63, 1353-1363 (2012
42. Hurko, O. et al. The ADNI publication policy: commensurate recognition of critical contributors who are not authors. Neuroimage 59, 4196-4200 (2012
43. Rohlfing, T. & Poline, J.-B. Why shared data should not be acknowledged on the author byline. Neuroimage 59, 4189-4195 (2012
44. Gorgolewski, K.J., Margulies, D.S. & Milham, M.P. Making data sharing count: a publication-based solution. Front. Neurosci. 7, 9 (2013
45. Gorgolewski, K.J. et al. A test-retest fMRI dataset for motor, language and spatial attention functions. Gigascience 2, 6 (2013
46. Hanke, M. et al. A high-resolution 7-tesla fMRI dataset from complex natural stimulation with an audio movie. Sci. Data 1, 140003 (2014
47. Anonymous. Using someone else's data. practiCal fMRI: the nuts & bolts http://practicalfmri.blogspot.com/2014/02/using-someone-elses-data.html (2014
48. Meehl, P. Theory testing in psychology and physics: a methodological paradox. Philos. Sci. 34, 103-115 (1967
49. Monogan, J.E. III. A case for registering studies of political outcomes: an application in the 2010 house elections. Polit. Anal. 21, 21-37 (2013
50. HD-200 Consortium. The ADHD-200 consortium: a model to advance the translational potential of neuroimaging in clinical neuroscience. Front. Syst. Neurosci. 6, 62 (2012
51. Guyon, I., Hur, A.B., Gunn, S. & Dror, G. Result analysis of the NIPS 2003 feature selection challenge. Adv. Neural Inf. Process. Syst. 17, 545-552 (2004
52. Marshall, E. Bermuda rules: community spirit, with teeth. Science 291, 1192 (2001
53. Gardner, D. et al. The neuroscience information framework: a data and knowledge environment for neuroscience. Neuroinformatics 6, 149-160 (2008
54. Marenco, L., Ascoli, G.A., Martone, M.E., Shepherd, G.M. & Miller, P.L. The NIF LinkOut broker: a web resource to facilitate federated data integration using NCBI identifiers. Neuroinformatics 6, 219-227 (2008
55. Langille, M.G.I. & Eisen, J.A. BioTorrents: a file sharing service for scientific data. PLoS ONE 5, e10071 (2010
56. Gadde, S. et al. XCEDE: an extensible schema for biomedical data. Neuroinformatics 10, 19-32 (2012
57. Turner, J.A. & Laird, A.R. The cognitive paradigm ontology: design and application. Neuroinformatics 10, 57-66 (2012
58. Poldrack, R.A. et al. The cognitive atlas: toward a knowledge foundation for cognitive neuroscience. Front. Neuroinform. 5, 17 (2011
59. Marcus, D.S., Olsen, T.R., Ramaratnam, M. & Buckner, R.L. The extensible neuroimaging archive toolkit: an informatics platform for managing, exploring, and sharing neuroimaging data. Neuroinformatics 5, 11-34 (2007
60. Van Horn, J.D. & Toga, A.W. Is it time to re-prioritize neuroimaging databases and digital repositories?. Neuroimage 47, 1720-1734 (2009
61. Das, S., Zijdenbos, A.P., Harlap, J., Vins, D. & Evans, A.C. LORIS: a web-based data management system for multi-center studies. Front. Neuroinform. 5, 37 (2011
62. Scott, A. et al. COINS: an innovative informatics and neuroimaging tool suite built for large heterogeneous datasets. Front. Neuroinform. 5, 33 (2011
63. Marcus, D.S. et al. Human connectome project informatics: quality control, database services, and data visualization. Neuroimage 80, 202-219 (2013
64. Rex, D.E., Ma, J.Q. & Toga, A.W. The LONI pipeline processing environment. Neuroimage 19, 1033-1048 (2003
65. Dinov, I. et al. Neuroimaging study designs, computational analyses and data provenance using the LONI pipeline. PLoS ONE 5, e13070 (2010
66. Gorgolewski, K. et al. Nipype: a flexible, lightweight and extensible neuroimaging data processing framework in Python. Front. Neuroinform. 5, 13 (2011
67. MacKenzie-Graham, A.J., Van Horn, J.D., Woods, R.P., Crawford, K.L. & Toga, A.W. Provenance in neuroimaging. Neuroimage 42, 178-195 (2008
68. Bellec, P. et al. The pipeline system for octave and MATLAB (PSOM): a lightweight scripting framework and execution engine for scientific workflows. Front. Neuroinform. 6, 7 (2012