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Rationales and Approaches to Protecting Brain Data: a Scoping Review

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Abstract

Advances in neurotechnologies, artificial intelligence (AI) and Big Data analytics are allowing interpretation of patterns from brain data to identify and even predict and manipulate mental states. Furthermore, there are avenues through which brain data can move into the consumer sphere, be reidentified and brokered. In response to these developments, there have been a number of approaches proposed to strengthen protections of brain data. To better understand the landscape of brain data protection discussions, we conducted a scoping review to identify the rationales for establishing brain data protections and the proposals for protecting brain data offered in the ethics and neuroscience literature. To draw comparisons, we also surveyed the rationales given in the literature for the protection of sensitive behavioral inferences drawn from other types of personal data and associated approaches to achieving protection. This systematic examination of the rationale behind heightened protection for brain data should be useful to clarify the functional and conceptual bases given for brain data protection and to provide a better grounding for evaluating how the different approaches to brain data protection address these concerns.

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The authors confirm that the data supporting the findings of this study are available within the article and its supplementary materials.

Notes

  1. For example, the article identified through this tertiary search [10] was in a preprint format at the time of the primary PubMed search.

  2. A list of target articles on brain data and themes/subthemes appeared in the articles are available in the Supp. Figure 1.

  3. A list of target articles on inferential data and themes/subthemes appeared in the articles are available in the Supp. Fig. 2.

References

  1. Martinez-Martin, N., T.R. Insel, P. Dagum, H.T. Greely, and M.K. Cho. 2018. Data mining for health: staking out the ethical territory of digital phenotyping. NPJ Digital Medicine 1: 68. https://doi.org/10.1038/s41746-018-0075-8

  2. France-Presse, A. 2021. In the face of neurotechnology advances, Chile passes ‘neuro rights’ law. ACM Technews. https://cacm.acm.org/news/255951-in-the-face-of-neurotechnology-advances-chile-passes-neuro-rights-law/fulltext. Accessed 20 Jul 2023.

  3. Arksey, H., and L. O’Malley. 2005. Scoping studies: Towards a methodological framework. International Journal of Social Research Methodology 8 (1): 19–32. https://doi.org/10.1080/1364557032000119616.

    Article  Google Scholar 

  4. Munn, Z., M.D.J. Peters, C. Stern, C. Tufanaru, A. McArthur, and E. Aromataris. 2018. Systematic review or scoping review? Guidance for authors when choosing between a systematic or scoping review approach. BMC Medical Research Methodology 18 (1): 143. https://doi.org/10.1186/s12874-018-0611-x.

    Article  Google Scholar 

  5. Levac, D., H. Colquhoun, and K.K. O’Brien. 2010. Scoping studies: Advancing the methodology. Implementation Science 5 (1): 69. https://doi.org/10.1186/1748-5908-5-69.

    Article  Google Scholar 

  6. Vaughn, P., and C. Turner. 2016. Decoding via coding: Analyzing qualitative text data through thematic coding and survey methodologies. Journal of Library Administration 56 (1): 41–51. https://doi.org/10.1080/01930826.2015.1105035.

    Article  Google Scholar 

  7. Cavanagh, S. 1997. Content analysis: Concepts, methods and applications. Nurse Researcher 4 (3): 5–16. https://doi.org/10.7748/nr.4.3.5.s2.

    Article  Google Scholar 

  8. Ienca, M., and G. Malgieri. 2022. Mental data protection and the GDPR. Journal of Law and the Biosciences 9 (1): lsac006. https://doi.org/10.1093/jlb/lsac006.

    Article  Google Scholar 

  9. Minielly, N., V. Hrincu, and J. Illes. 2020. Privacy challenges to the democratization of brain data. IScience 23 (6): 101134. https://doi.org/10.1016/j.isci.2020.101134.

    Article  Google Scholar 

  10. Ienca, M., J.J. Fins, R. J. Jox, F. Jotterand, S. Voeneky, R. Andorno, . . . P. Kellmeyer. 2022. Towards a governance framework for brain data. Neuroethics 15(2): 20. https://doi.org/10.1007/s12152-022-09498-8.

  11. Goering, S., E. Klein, L. Specker Sullivan, A. Wexler, B. Agüera y Arcas, G. Bi, . . . Bi, R. Bi. 2021. Recommendations for responsible development and application of neurotechnologies. Neuroethics 14(3): 365–386. https://doi.org/10.1007/s12152-021-09468-6.

  12. Illes, J., and E. Racine. 2005. Imaging or imagining? A neuroethics challenge informed by genetics. American Journal of Bioethics 5 (2): 5–18. https://doi.org/10.1080/15265160590923358.

    Article  Google Scholar 

  13. Wajnerman Paz, A. 2021. Is your neural data part of your mind? Exploring the conceptual basis of mental privacy. Minds Machines. https://doi.org/10.1007/s11023-021-09574-7.

    Article  Google Scholar 

  14. Naufel, S., and E. Klein. 2020. Brain-computer interface (BCI) researcher perspectives on neural data ownership and privacy. Journal of Neural Engineering 17 (1): 016039. https://doi.org/10.1088/1741-2552/ab5b7f.

    Article  Google Scholar 

  15. Wexler, A. 2019. Separating neuroethics from neurohype. Nature Biotechnology 37 (9): 988–990. https://doi.org/10.1038/s41587-019-0230-z.

    Article  Google Scholar 

  16. Wexler, A. 2020. The urgent need to better integrate neuroscience and neuroethics. AJOB Neuroscience 11 (3): 219–220. https://doi.org/10.1080/21507740.2020.1778129.

    Article  Google Scholar 

  17. Mecacci, G., and P. Haselager. 2019. Identifying criteria for the evaluation of the implications of brain reading for mental privacy. Science and Engineering Ethics 25 (2): 443–461. https://doi.org/10.1007/s11948-017-0003-3.

    Article  Google Scholar 

  18. Bonaci, T., R. Calo, and H.J. Chizeck. (2014, 23–24 May 2014). App stores for the brain: Privacy & security in Brain-Computer Interfaces. Paper presented at the 2014 IEEE International Symposium on Ethics in Science, Technology and Engineering. https://doi.org/10.1109/ETHICS.2014.6893415.

  19. Ienca, M., and R. Andorno. 2017. Towards new human rights in the age of neuroscience and neurotechnology. Life Sci Soc Policy 13 (1): 5. https://doi.org/10.1186/s40504-017-0050-1.

    Article  Google Scholar 

  20. Kellmeyer, P. 2021. Big brain data: On the responsible use of brain data from clinical and consumer-directed neurotechnological devices. Neuroethics 14 (1): 83–98. https://doi.org/10.1007/s12152-018-9371-x.

    Article  Google Scholar 

  21. Lee, S.M., and M.A. Majumder. 2022. National institutes of mental health data archive: Privacy, consent, and diversity considerations and options for improvement. AJOB Neuroscience 13 (1): 3–9. https://doi.org/10.1080/21507740.2021.1904025.

    Article  Google Scholar 

  22. Ienca, M., P. Haselager, and E.J. Emanuel. 2018. Brain leaks and consumer neurotechnology. Nature Biotechnology 36 (9): 805–810. https://doi.org/10.1038/nbt.4240.

    Article  Google Scholar 

  23. Lavazza, A. 2018. Freedom of thought and mental integrity: The moral requirements for any neural prosthesis. Frontiers in Neuroscience 12: 82. https://doi.org/10.3389/fnins.2018.00082.

    Article  Google Scholar 

  24. Bluhm, R., M. Cortright, E.D. Achtyes, and L.Y. Cabrera. 2023. They are invasive in different ways.: Stakeholders’ perceptions of the invasiveness of psychiatric electroceutical interventions. AJOB Neuroscience 14 (1): 1–2.

    Article  Google Scholar 

  25. McCall, I.C., N. Minielly, A. Bethune, N. Lipsman, P.J. McDonald, and J. Illes. 2020. Readiness for first-in-human neuromodulatory interventions. Canadian Journal of Neurological Sciences 47 (6): 785–792.

    Article  Google Scholar 

  26. Klein E. (2023). What does it mean to call a medical device invasive? Med Health Care Philos. https://doi.org/10.1007/s11019-023-10147-x

  27. Farah, M.J., and P.R. Wolpe. 2004. Monitoring and manipulating brain function: New neuroscience technologies and their ethical implications. Hastings Center Report 34 (3): 35–45. https://doi.org/10.2307/3528418.

    Article  Google Scholar 

  28. Farah, M.J., M.E. Smith, C. Gawuga, D. Lindsell, and D. Foster. 2009. Brain imaging and brain privacy: A realistic concern? Journal of Cognitive Neuroscience 21 (1): 119–127. https://doi.org/10.1162/jocn.2009.21010.

    Article  Google Scholar 

  29. Ward, H.J.T. 2011. Privacy and governance implications of wider societal uses of brain imaging data. Cortex 47 (10): 1263–1265. https://doi.org/10.1016/j.cortex.2011.04.016.

    Article  Google Scholar 

  30. Rainey, S., S. Martin, A. Christen, P. Mégevand, and E. Fourneret. 2020. Brain recording, mind-reading, and neurotechnology: Ethical Issues from consumer devices to brain-based speech decoding. Science and Engineering Ethics 26 (4): 2295–2311. https://doi.org/10.1007/s11948-020-00218-0.

    Article  Google Scholar 

  31. Shen, F.X. 2013. Neuroscience, mental privacy, and the law. Harvard Journal of Public Law and Policy 36: 653.

    Google Scholar 

  32. Beauvais, M.J.S., B.M. Knoppers, and J. Illes. 2021. A marathon, not a sprint – neuroimaging, Open Science and ethics. Neuroimage 236: 118041. https://doi.org/10.1016/j.neuroimage.2021.118041.

    Article  Google Scholar 

  33. Ienca, M., and P. Haselager. 2016. Hacking the brain: Brain–computer interfacing technology and the ethics of neurosecurity. Ethics and Information Technology 18 (2): 117–129. https://doi.org/10.1007/s10676-016-9398-9.

    Article  Google Scholar 

  34. Yuste, R., S. Goering, B. Agüera y Arcas, G. Bi, J.M. Carmena, A. Carter, . . . J. Wolpaw. 2017. Four ethical priorities for neurotechnologies and AI. Nature 551(7679): 159–163. https://doi.org/10.1038/551159a.

  35. Ligthart, S. 2019. Coercive neuroimaging, criminal law, and privacy: A European perspective. Journal of Law and the Biosciences 6 (1): 289–309. https://doi.org/10.1093/jlb/lsz015.

    Article  Google Scholar 

  36. Ligthart, S. 2020. Freedom of thought in Europe: do advances in ‘brain-reading’ technology call for revision? Journal of Law and the Biosciences 7(1). https://doi.org/10.1093/jlb/lsaa048.

  37. Ligthart, S., T. Douglas, C. Bublitz, T. Kooijmans, and G. Meynen. 2021. Forensic brain-reading and mental privacy in european human rights law: foundations and challenges. Neuroethics 14 (2): 191–203. https://doi.org/10.1007/s12152-020-09438-4.

    Article  Google Scholar 

  38. Borbón, D., and L. Borbón. 2021. A critical perspective on neurorights: Comments regarding ethics and law. Frontiers in Human Neuroscience 15: 703121. https://doi.org/10.3389/fnhum.2021.703121.

    Article  Google Scholar 

  39. Herrera-Ferrá, K., J.M. Muñoz, H. Nicolini, G. Saruwatari Zavala, and V.M. Martínez Bullé Goyri. 2022. Contextual and cultural perspectives on neurorights: Reflections toward an international consensus. AJOB Neurosci 1–9. https://doi.org/10.1080/21507740.2022.2048722.

  40. Cato, K.D., W. Bockting, and E. Larson. 2016. Did i tell you that? Ethical issues related to using computational methods to discover non-disclosed patient characteristics. Journal of Empirical Research on Human Research Ethics 11 (3): 214–219. https://doi.org/10.1177/1556264616661611.

    Article  Google Scholar 

  41. Grover, S., S. Sarkar, and R. Gupta. 2020. Data handling for E-Mental health professionals. Indian Journal of Psychological Medicine 42 (5 Suppl): 85s–91s. https://doi.org/10.1177/0253717620956732.

    Article  Google Scholar 

  42. Farahany, N.A. 2012. Searching secrets. University of Pennsylvania Law Review 160 (5): 1239–1308.

    Google Scholar 

  43. Farahany, N.A. 2012. Incriminating thoughts. Stanford Law Review 64 (2): 351–408.

    Google Scholar 

  44. Aboujaoude, E. 2019. Protecting privacy to protect mental health: The new ethical imperative. Journal of Medical Ethics 45 (9): 604–607. https://doi.org/10.1136/medethics-2018-105313.

    Article  Google Scholar 

  45. Wachter, S., and B. Mittelstadt. 2019. A right to reasonable inferences: re-thinking data protection law in the age of big data and AI. Columbia Business Law Review 2019 (2): 494–620. https://doi.org/10.7916/cblr.v2019i2.3424.

    Article  Google Scholar 

  46. Cosgrove, L., J.M. Karter, M. McGinley, and Z. Morrill. 2020. Digital phenotyping and digital psychotropic drugs: mental health surveillance tools that threaten human rights. Health and Human Rights 22 (2): 33–39.

    Google Scholar 

  47. Poldrack, R.A. 2011. Inferring mental states from neuroimaging data: From reverse inference to large-scale decoding. Neuron 72 (5): 692–697. https://doi.org/10.1016/j.neuron.2011.11.001.

    Article  Google Scholar 

  48. Poldrack, R.A., G. Huckins, and G. Varoquaux. 2020. Establishment of best practices for evidence for prediction: A review. JAMA Psychiatry 77 (5): 534–540. https://doi.org/10.1001/jamapsychiatry.2019.3671.

    Article  Google Scholar 

  49. Hosseini, M., M. Powell, J. Collins, C. Callahan-Flintoft, W. Jones, H. Bowman, and B. Wyble. 2020. I tried a bunch of things: The dangers of unexpected overfitting in classification of brain data. Neuroscience and Biobehavioral Reviews 119: 456–467. https://doi.org/10.1016/j.neubiorev.2020.09.036.

    Article  Google Scholar 

  50. Callanan, G.A., D.F. Perri, and S.M. Tomkowicz. 2021. Targeting vulnerable populations: The ethical implications of data mining, automated prediction, and focused marketing. Business and Society Review 126 (2): 155–167. https://doi.org/10.1111/basr.12233.

    Article  Google Scholar 

  51. Perez-Pozuelo, I., D. Spathis, J. Gifford-Moore, J. Morley, and J. Cowls. 2021. Digital phenotyping and sensitive health data: Implications for data governance. Journal of the American Medical Informatics Association 28 (9): 2002–2008. https://doi.org/10.1093/jamia/ocab012.

    Article  Google Scholar 

  52. Marks, M. 2021. Emergent medical data: Health information inferred by artificial intelligence. University of California Irvine Law Review 11 (4): 995–1066.

    Google Scholar 

  53. Chancellor, S., M.L. Birnbaum, E.D. Caine, V.M.B. Silenzio, and M.D. Choudhury. 2019. A taxonomy of ethical tensions in inferring mental health states from social media. Paper presented at the Proceedings of the Conference on Fairness, Accountability, and Transparency, Atlanta, GA, USA. https://doi.org/10.1145/3287560.3287587.

  54. Human Rights Council, Resolution adopted by the Human Rights Council on 6 October 2022. https://documents-dds-ny.un.org/doc/UNDOC/GEN/G22/525/01/PDF/G2252501.pdf?OpenElement.

  55. Kostiuk, S.A. 2012. After GINA, NINA? Neuroscience-based discrimination in the workplace. Vanderbilt Law Review 65: 933.

    Google Scholar 

  56. Shin, J.J. 2015. Closing the gap: Protecting predictive neuroscience information from health insurance discrimination. Emory Law Journal 64: 1433-1465.

    Google Scholar 

  57. Jwa, A.S., and R.A. Poldrack. 2022. Addressing privacy risk in neuroscience data: from data protection to harm prevention. Journal of Law and the Biosciences 9(2). https://doi.org/10.1093/jlb/lsac025.

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Funding

AJ is supported by National Institute of Mental Health R24 MH117179-04S1. NM is supported by NIH/National Institute of Mental Health K01 MH118375-01A1.

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Correspondence to Anita S. Jwa.

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Jwa, A.S., Martinez-Martin, N. Rationales and Approaches to Protecting Brain Data: a Scoping Review. Neuroethics 17, 2 (2024). https://doi.org/10.1007/s12152-023-09534-1

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