The Open Brain Consent: Informing research participants and obtaining consent to share brain imaging data
Jazyk angličtina Země Spojené státy americké Médium print-electronic
Typ dokumentu úvodníky, Research Support, N.I.H., Extramural, práce podpořená grantem, Research Support, U.S. Gov't, Non-P.H.S.
Grantová podpora
P41 EB019936
NIBIB NIH HHS - United States
R01 MH096906
NIMH NIH HHS - United States
PubMed
33522661
PubMed Central
PMC8046140
DOI
10.1002/hbm.25351
Knihovny.cz E-zdroje
- Klíčová slova
- brain imaging, general data protection regulation, informed consent,
- MeSH
- informovaný souhlas pacienta * etika MeSH
- lidé MeSH
- mozek diagnostické zobrazování MeSH
- neurozobrazování * etika MeSH
- šíření informací * etika MeSH
- subjekty výzkumu * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- práce podpořená grantem MeSH
- Research Support, N.I.H., Extramural MeSH
- Research Support, U.S. Gov't, Non-P.H.S. MeSH
- úvodníky MeSH
Having the means to share research data openly is essential to modern science. For human research, a key aspect in this endeavor is obtaining consent from participants, not just to take part in a study, which is a basic ethical principle, but also to share their data with the scientific community. To ensure that the participants' privacy is respected, national and/or supranational regulations and laws are in place. It is, however, not always clear to researchers what the implications of those are, nor how to comply with them. The Open Brain Consent (https://open-brain-consent.readthedocs.io) is an international initiative that aims to provide researchers in the brain imaging community with information about data sharing options and tools. We present here a short history of this project and its latest developments, and share pointers to consent forms, including a template consent form that is compliant with the EU general data protection regulation. We also share pointers to an associated data user agreement that is not only useful in the EU context, but also for any researchers dealing with personal (clinical) data elsewhere.
Aalto University Espoo Finland
Bogazici University Istanbul Turkey
Centre for Clinical Brain Sciences University of Edinburgh Edinburgh United Kingdom
Dartmouth College Hanover New Hampshire USA
Department of Biological Medicine and Engineering BUAA Beihang University Beijing China
Department of Neuroimaging King's College London London United Kingdom
Department of Neuroscience and Biomedical Engineering Aalto University Espoo Finland
Department of Neurosurgery St Anne's University Hospital Masaryk University Brno Czech Republic
Department of Otolaryngology Head and Neck Surgery Harvard Medical School Boston Massachusetts USA
Department of Psychological and Brain Sciences Dartmouth College Hanover New Hampshire USA
Department of Radiology and Nuclear Medicine University Hospital Ghent Ghent Belgium
Donders Institute for Brain Cognition and Behaviour; Radboud University Nijmegen The Netherlands
Eindhoven University of Technology Eindhoven The Netherlands
Erasmus University Rotterdam Rotterdam The Netherlands
Faculty of Electrical Engineering University of Tuzla Tuzla Bosnia and Herzegovina
Ghent Institute for functional and Metabolic Imaging Ghent University Ghent Belgium
Helen Wills Neuroscience Institute University of California Berkeley California USA
Inria CNRS Inserm IRISA UMR 6074 Empenn ERL University of Rennes Rennes France
Inria University of Rennes CNRS Inserm IRISA UMR 6074 Empenn ERL U 1228 Rennes France
Institute for Experimental Psychology Heinrich Heine University of Düsseldorf Düsseldorf Germany
McGill University Montreal Neurological Institute and Hospital Montreal Quebec Canada
National Institute of Education Nanyang Technological University Singapore Singapore
Oslo University Hospital Oslo Norway
Pasteur Institute Paris France
Radiology Department CHU Rennes Rennes France
School of Health Fujian Medical University Fuzhou China
School of Psychology Nanjing Normal University Nanjing China
Stanford University Stanford California USA
University of Verona Verona Italy
Zuckerman Mind Brain Behavior Institute Columbia University New York New York USA
Zobrazit více v PubMed
Abramian, D. , & Eklund, A. (2019). Refacing: Reconstructing anonymized facial features using GANs. Paper presented at 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019) , 1104–1108. 10.1109/ISBI.2019.8759515 DOI
Bishop, D. V. M. (2016). Open research practices: Unintended consequences and suggestions for averting them. (commentary on the peer reviewers' openness initiative). Royal Society Open Science , 3(4), 160109. 10.1098/rsos.160109 PubMed DOI PMC
de Sitter, A. , Visser, M. , Brouwer, I. , Cover, K. S. , van Schijndel, R. A. , Eijgelaar, R. S. … Vrenken, H. (2020). Facing privacy in neuroimaging: Removing facial features degrades performance of image analysis methods. European Radiology , 30(2), 1062–1074. 10.1007/s00330-019-06459-3 PubMed DOI PMC
Duan, D. , Xia, S. , Rekik, I. , Wu, Z. , Wang, L. , Lin, W. , … Li, G. (2020). Individual identification and individual variability analysis based on cortical folding features in developing infant singletons and twins. Human Brain Mapping , 41(8), 1985‐2003. 10.1002/hbm.24924 PubMed DOI PMC
Gaspar, C. M. , Rousselet, G. A. , & Pernet, C. R. (2011). Reliability of ERP and single‐trial analyses. NeuroImage , 58(2), 620–629. 10.1016/j.neuroimage.2011.06.052 PubMed DOI
Gymrek, M. , McGuire, A. L. , Golan, D. , Halperin, E. , & Erlich, Y. (2013). Identifying personal genomes by surname inference. Science , 339(6117), 321–324. 10.1126/science.1229566 PubMed DOI
Halchenko Yaroslav, Vborghesani, Chris Gorgolewski , Yarikoptic‐private, Satrajit Ghosh , Kieseler Marie‐Luise, Pellman John, & Hu Chuan‐Peng. (2019). Datalad/open‐brain‐consent 0.2.4. Zenodo. 10.5281/zenodo.3403176 DOI
Khan, A. , Capps, B. J. , Sum, M. Y. , Kuswanto, C. N. , & Sim, K. (2014). Informed consent for human genetic and genomic studies: A systematic review. Clinical Genetics , 86(3), 199–206. 10.1111/cge.12384 PubMed DOI
Leppäaho, E. , Renvall, H. , Salmela, E. , Kere, J. , Salmelin, R. , & Kaski, S. (2019). Discovering heritable modes of MEG spectral power. Human Brain Mapping , 40(5), 1391–1402. 10.1002/hbm.24454 PubMed DOI PMC
Milham, M. P. , Craddock, R. C. , Son, J. J. , Fleischmann, M. , Clucas, J. , Xu, H. , … Klein, A. (2018). Assessment of the impact of shared brain imaging data on the scientific literature. Nature Communications , 9(1), 1–7. 10.1038/s41467-018-04976-1 PubMed DOI PMC
Mourby, M. , Mackey, E. , Elliot, M. , Gowans, H. , Wallace, S. E. , Bell, J. , … Kaye, J. (2018). Are ‘pseudonymised’ data always personal data? Implications of the GDPR for administrative data research in the UK. Computer Law and Security Review , 34(2), 222–233. 10.1016/j.clsr.2018.01.002 DOI
Plis, S. M. , Sarwate, A. D. , Wood, D. , Dieringer, C. , Landis, D. , Reed, C. , … Calhoun, V. D. (2016). COINSTAC: A privacy enabled model and prototype for leveraging and processing decentralized brain imaging data. Frontiers in Neuroscience , 10, 365. 10.3389/fnins.2016.00365 PubMed DOI PMC
Poldrack, R. A. , Barch, D. M. , Mitchell, J. P. , Wager, T. D. , Wagner, A. D. , Devlin, J. T. … Milham, M. P. (2013). Toward open sharing of task‐based fMRI data: The openfMRI project. Frontiers in Neuroinformatics, 7, 12. 10.3389/fninf.2013.00012 PubMed DOI PMC
Ravindra, V. , & Grama, A. (2019). De‐anonymization attacks on neuroimaging datasets. ArXiv:1908.03260 [Cs, Eess, q‐Bio] . http://arxiv.org/abs/1908.03260
Rocher, L. , Hendrickx, J. M. , & de Montjoye, Y.‐A. (2019). Estimating the success of re‐identifications in incomplete datasets using generative models. Nature Communications , 10. 10.1038/s41467-019-10933-3, 3069 PubMed DOI PMC
Ruiz‐Blondet, M. V. , Jin, Z. , & Laszlo, S. (2017). Permanence of the CEREBRE brain biometric protocol. Pattern Recognition Letters , 95, 37–43. 10.1016/j.patrec.2017.05.031 DOI
Sheehan, M. J. , & Nachman, M. W. (2014). Morphological and population genomic evidence that human faces have evolved to signal individual identity. Nature Communications , 5(1), 1–10. 10.1038/ncomms5800 PubMed DOI PMC
Sheller, M. J. , Edwards, B. , Reina, G. A. , Martin, J. , Pati, S. , Kotrotsou, A. , … Bakas, S. (2020). Federated learning in medicine: Facilitating multi‐institutional collaborations without sharing patient data. Scientific Reports, 10(1), 12598. 10.1038/s41598-020-69250-1 PubMed DOI PMC
Staunton, C. , Slokenberga, S. , & Mascalzoni, D. (2019). The GDPR and the research exemption: Considerations on the necessary safeguards for research biobanks. European Journal of Human Genetics , 27(8), 1159–1167. 10.1038/s41431-019-0386-5 PubMed DOI PMC
Thompson, P. M. , Stein, J. L. , Medland, S. E. , Hibar, D. P. , Vasquez, A. A. , Renteria, M. E. , … Drevets, W. (2014). The ENIGMA consortium: Large‐scale collaborative analyses of neuroimaging and genetic data. Brain Imaging and Behavior , 8(2), 153–182. 10.1007/s11682-013-9269-5 PubMed DOI PMC
World Medical Association . (2001). World medical association declaration of Helsinki. Bulletin of the World Health Organization , 79(4), 373–374. PubMed PMC
World Medical Association . (2017). The world medical association declaration of Taipei . https://www.wma.net/policies‐post/wma‐declaration‐of‐taipei‐on‐ethical‐considerations‐regarding‐health‐databases‐and‐biobanks/
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