Advocating for neurodata privacy and neurotechnology regulation.
Journal
Nature protocols
ISSN: 1750-2799
Titre abrégé: Nat Protoc
Pays: England
ID NLM: 101284307
Informations de publication
Date de publication:
10 2023
10 2023
Historique:
received:
27
03
2023
accepted:
27
07
2023
medline:
9
10
2023
pubmed:
12
9
2023
entrez:
11
9
2023
Statut:
ppublish
Résumé
The ability to record and alter brain activity by using implantable and nonimplantable neural devices, while poised to have significant scientific and clinical benefits, also raises complex ethical concerns. In this Perspective, we raise awareness of the ability of artificial intelligence algorithms and data-aggregation tools to decode and analyze data containing highly sensitive information, jeopardizing personal neuroprivacy. Voids in existing regulatory frameworks, in fact, allow unrestricted decoding and commerce of neurodata. We advocate for the implementation of proposed ethical and human rights guidelines, alongside technical options such as data encryption, differential privacy and federated learning to ensure the protection of neurodata privacy. We further encourage regulatory bodies to consider taking a position of responsibility by categorizing all brain-derived data as sensitive health data and apply existing medical regulations to all data gathered via pre-registered neural devices. Lastly, we propose that a technocratic oath may instill a deontology for neurotechnology practitioners akin to what the Hippocratic oath represents in medicine. A conscientious societal position that thoroughly rejects the misuse of neurodata would provide the moral compass for the future development of the neurotechnology field.
Identifiants
pubmed: 37697107
doi: 10.1038/s41596-023-00873-0
pii: 10.1038/s41596-023-00873-0
doi:
Types de publication
Journal Article
Review
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
2869-2875Informations de copyright
© 2023. Springer Nature Limited.
Références
Coughlin, B. et al. Modified Neuropixels probes for recording human neurophysiology in the operating room. Nat. Protoc. https://doi.org/10.1038/s41596-023-00871-2 (2023).
Steinmetz, N. A. et al. Neuropixels 2.0: a miniaturized high-density probe for stable, long-term brain recordings. Science 372, eabf4588 (2021).
pubmed: 33859006
pmcid: 8244810
Paulk, A. C. et al. Large-scale neural recordings with single neuron resolution using Neuropixels probes in human cortex. Nat. Neurosci. 25, 252–263 (2022).
pubmed: 35102333
Tang, J., LeBel, A., Jain, S. J. & Huth, A. G. Semantic reconstruction of continuous language from non-invasive brain recordings. Nat. Neurosci. 26, 858–866 (2023).
pubmed: 37127759
Takagi, Y. & Nishimoto, S. High-resolution image reconstruction with latent diffusion models from human brain activity. Preprint at https://www.biorxiv.org/content/10.1101/2022.11.18.517004v2 (2022).
Défossez, A., Caucheteux, C., Rapin, J. & Kabeli, O. Decoding speech from non-invasive brain recordings. Preprint at https://arxiv.org/abs/2208.12266 (2022).
Chen, Z., Qing, J., Xiang, T., Yue, W. & Zhou, J. L. Seeing beyond the brain: conditional diffusion model with sparse masked modeling for vision decoding. Preprint at https://arxiv.org/abs/2211.06956 (2022).
Grover, S., Wen, W., Viswanathan, V., Gill, C. & Reinhart, R. Long-lasting, dissociable improvements in working memory and long-term memory in older adults with repetitive neuromodulation. Nat. Neurosci. 25, 1237–1246 (2022).
pubmed: 35995877
pmcid: 10068908
Alivisatos, A. P. et al. Nanotools for neuroscience and brain activity mapping. ACS Nano 7, 1850–1866 (2013).
pubmed: 23514423
pmcid: 3665747
Nicolelis, M. A. & Lebedev, M. A. Principles of neural ensemble physiology underlying the operation of brain-machine interfaces. Nat. Rev. Neurosci. 10, 530–540 (2009).
pubmed: 19543222
Hochberg, L. R. et al. Neuronal ensemble control of prosthetic devices by a human with tetraplegia. Nature 442, 164–171 (2006).
pubmed: 16838014
Alivisatos, A. P. et al. Neuroscience. The brain activity map. Science 339, 1284–1285 (2013).
pubmed: 23470729
pmcid: 3722427
Insel, T. R., Landis, S. C. & Collins, F. S. The NIH BRAIN Initiative. Science 340, 687–688 (2013).
pubmed: 23661744
pmcid: 5101945
Jorgenson, L. A. et al. The BRAIN Initiative: developing technology to catalyse neuroscience discovery. Philos. Trans. R. Soc. Lond. B Biol. Sci. 370, 20140164 (2015).
pubmed: 25823863
pmcid: 4387507
Yuste, R. & Bargmann, C. Toward a global BRAIN initiative. Cell 168, 956–959 (2017).
pubmed: 28256259
Adams, A. et al. International brain initiative: an innovative framework for coordinated global brain research efforts. Neuron 105, 212–216 (2020).
The Neurorights Foundation: Market Analysis: Neurotechnology. Available at https://neurorightsfoundation.org/publications (2023).
Yuste, R. From the neuron doctrine to neural networks. Nat. Rev. Neurosci. 16, 487–497 (2015).
pubmed: 26152865
Miller, J. E., Ayzenshtat, I., Carrillo-Reid, L. & Yuste, R. Visual stimuli recruit intrinsically generated cortical ensembles. Proc. Natl. Acad. Sci. USA. 111, E4053–E4061 (2014).
pubmed: 25201983
pmcid: 4183303
Carrillo-Reid, L., Han, S., Yang, W., Akrough, A. & Yuste, R. Controlling visually guided behavior by holographic recalling of cortical ensembles. Cell 178, 447–457.e5 (2019).
pubmed: 31257030
pmcid: 6747687
Marshel, J. H. et al. Cortical layer-specific critical dynamics triggering perception. Science 365, eaaw5202 (2019).
pubmed: 31320556
pmcid: 6711485
Ramirez, S. et al. Creating a false memory in the hippocampus. Science 341, 387–391 (2013).
pubmed: 23888038
Hamm, J. P., Peterka, D. S., Gogos, J. A. & Yuste, R. Altered cortical ensembles in mouse models of schizophrenia. Neuron 94, 153–167.e8 (2017).
pubmed: 28384469
pmcid: 5394986
Wenzel, M., Hamm, J. P., Peterka, D. S. & Yuste, R. Acute focal seizures start as local synchronizations of neuronal ensembles. J. Neurosci. 39, 8562–8575 (2019).
pubmed: 31427393
pmcid: 6807279
Benabid, A. L. Deep brain stimulation for Parkinson’s disease. Curr. Opin. Neurobiol. 13, 696–706 (2003).
pubmed: 14662371
Burke, M. J., Fried, P. J. & Pascual-Leone, A. Transcranial magnetic stimulation: neurophysiological and clinical applications. Handb. Clin. Neurol. 163, 73–92 (2019).
pubmed: 31590749
Tripp, S. & Grueber, M. Economic Impact of the Human Genome Project. Battelle Laboratory. Available at https://www.battelle.org/docs/default-source/misc/battelle-2011-misc-economic-impact-human-genome-project.pdf (Battelle Memorial Institute, 2011).
Wexler, A. & Reiner, P. B. Oversight of direct-to-consumer neurotechnologies. Science 363, 234–235 (2019).
pubmed: 30655433
pmcid: 6629579
Anumanchipalli, G. K., Chartier, J. & Chang, E. F. Speech synthesis from neural decoding of spoken sentences. Nature 568, 493–498 (2019).
pubmed: 31019317
pmcid: 9714519
Willett, F. R., Avansino, D. T., Hochberg, L. R., Henderson, J. M. & Shenoy, K. V. High-performance brain-to-text communication via handwriting. Nature 593, 249–254 (2021).
pubmed: 33981047
pmcid: 8163299
Kay, K. N., Naselaris, T., Prenger, R. J. & Gallant, J. L. Identifying natural images from human brain activity. Nature 452, 352–355 (2008).
pubmed: 18322462
pmcid: 3556484
Ghashghaei, H. T., Hilgetag, C. C. & Barbas, H. Sequence of information processing for emotions based on the anatomic dialogue between prefrontal cortex and amygdala. Neuroimage 34, 905–923 (2007).
pubmed: 17126037
Kragel, P., Knodt, A., Hariri, A. & LaBar, K. Decoding spontaneous emotional states in the human brain. PLoS Biol. 14, e2000106 (2016).
pubmed: 27627738
pmcid: 5023171
Chang, C., Nastase, S. & Hasson, U. Information flow across the cortical timescale hierarchy during narrative construction. Proc. Natl. Acad. Sci. USA. 119, e2209307119 (2022).
pubmed: 36508677
pmcid: 9907070
Momi, D. et al. Cognitive enhancement via network-targeted cortico-cortical associative brain stimulation. Cereb. Cortex 30, 1516–1527 (2020).
pubmed: 31667497
Goering, S. & Yuste, R. On the necessity of ethical guidelines for novel neurotechnologies. Cell 167, 882–885 (2016).
pubmed: 27814514
Klein, E., Brown, T., Sample, M., Truitt, A. R. & Goering, S. Engineering the brain: ethical issues and the introduction of neural devices. Hastings Cent. Rep. 45, 26–35 (2015).
pubmed: 26556144
Yuste, R. et al. Four ethical priorities for neurotechnologies and AI. Nature 551, 159–163 (2017).
pubmed: 29120438
pmcid: 8021272
Lewis, C. J. et al. Subjectively perceived personality and mood changes associated with subthalamic stimulation in patients with Parkinson’s disease. Psychol. Med. 45, 73–85 (2015).
pubmed: 25066623
Pham, U. et al. Personality changes after deep brain stimulation in Parkinson’s disease. Parkinsons Dis. 2015, 49057 (2015).
Goering, S., Klein, E., Dougherty, D. D. & Widge, A. S. Staying in the loop: relational agency and identity in next-generation DBS for psychiatry. AJOB Neurosci. 8, 59–70 (2017).
Farah, M. J. & Heberlein, A. S. Personhood and neuroscience: naturalizing or nihilating? Am. J. Bioeth. 7, 37–48 (2007).
pubmed: 17366164
Goering, S. et al. Recommendations for responsible development and application of neurotechnologies. Neuroethics 14, 365–386 (2021).
pubmed: 33942016
pmcid: 8081770
Information Commissioner’s Office. ICO Tech Futures: Neurotechnology. Available at https://ico.org.uk/about-the-ico/research-and-reports/ico-tech-futures-neurotechnology/ (2023).
Eaton, M. L. & Illes, J. Commercializing cognitive neurotechnology—the ethical terrain. Nat. Biotechnol. 25, 393–397 (2007).
pubmed: 17420741
Kellmeyer, P. Ethical issues in the application of machine learning to brain disorders. In Machine Learning (eds. Mechelli, A. & Vieira, S.) 329–342 (Academic Press, 2020).
Kreitmair, K. V. Dimensions of ethical direct-to-consumer neurotechnologies. AJOB Neurosci. 10, 152–166 (2019).
pubmed: 31642755
Steinert, S. & Friedrich, O. Wired emotions: ethical issues of affective brain–computer interfaces. Sci. Eng. Ethics 26, 351–367 (2020).
pubmed: 30868377
Antal, A. et al. Low intensity transcranial electric stimulation: safety, ethical, legal regulatory and application guidelines. Clin. Neurophysiol. 128, 1774–1809 (2017).
pubmed: 28709880
pmcid: 5985830
Wexler, A. The practices of do-it-yourself brain stimulation: implications for ethical considerations and regulatory proposals. J. Med. Ethics 42, 211–215 (2016).
pubmed: 26324456
Klein, E. et al. Brain-computer interface-based control of closed-loop brain stimulation: attitudes and ethical considerations. Brain Comput. Interfaces (Abingdon) 3, 140–148 (2016).
Riggall, K. et al. Researchers’ perspectives on scientific and ethical issues with transcranial direct current stimulation: an international survey. Sci. Rep. 5, 10618 (2015).
pubmed: 26068889
pmcid: 4464285
Hildt, E. What will this do to me and my brain? Ethical issues in brain-to-brain interfacing. Front. Syst. Neurosci. 9, 17 (2015).
pubmed: 25762903
pmcid: 4340163
Parens, E. Enhancing Human Traits: Ethical and Social Implications (Georgetown University Press, 2000).
Juengst, E. What does “enhancement” mean? In (ed., Parens, E.) Enhancing Human Traits: Ethical and Social Implications (Georgetown University Press, 1998).
Wexler, A. Who uses direct-to-consumer brain stimulation products, and why? A study of home users of tDCS devices. J. Cogn. Enhanc. 2, 114–134 (2018).
Wexler, A. A pragmatic analysis of the regulation of consumer transcranial direct current stimulation (TDCS) devices in the United States. J. Law Biosci. 2, 669–696 (2016).
OECD-Council. OECD Recommendation on Responsible Innovation in Neurotechnology. (Organisation for Economic Co-operation and Development, 2019).
Ienca, M., Haselager, P. & Emanuel, E. J. Brain leaks and consumer neurotechnology. Nat. Biotechnol. 36, 805–810 (2018).
pubmed: 30188521
Ienca, M., Jotterand, F. & Elger, B. S. From healthcare to warfare and reverse: how should we regulate dual-use neurotechnology? Neuron 97, 269–274 (2018).
pubmed: 29346750
Ienca, M. & Andorno, R. Towards new human rights in the age of neuroscience and neurotechnology. Life Sci. Soc. Policy 13, 5 (2017).
pubmed: 28444626
pmcid: 5447561
Ienca, M. et al. Towards a governance framework for brain data. Neuroethics 15, 20 (2022).
Wexler, A. Separating neuroethics from neurohype. Nat. Biotechnol. 37, 988–990 (2019).
pubmed: 31399721
Greely, H. T. et al. Neuroethics guiding principles for the NIH BRAIN initiative. J. Neurosci. 38, 10586–10588 (2018).
pubmed: 30541767
pmcid: 6297371
IEEE. IEEE Neuroethics Framework. Available at https://brain.ieee.org/publications/ieee-neuroethics-framework/ (2021).
International Bioethics Committee of UNESCO. Ethical Issues of Neurotechnology. Available at https://unesdoc.unesco.org/ark:/48223/pf0000383559 (2022).
Farahany, N. A. The Battle for Your Brain: Defending the Right to Think Freely in the Age of Neurotechnology (St. Martin’s Press, 2023).
Yuste, R., Genser, J. & Herrmann, S. It’s time for Neuro-Rights. Horizons 18, 154–164 (2021).
Borbón, D. & Borbón, L. A critical perspective on NeuroRights: comments regarding ethics and law. Front. Hum. Neurosci. 15, 703121 (2021).
pubmed: 34759805
pmcid: 8573066
Bublitz, C. Novel neurorights: from nonsense to substance. Neuroethics 15, 7 (2022).
pubmed: 35154507
pmcid: 8821782
Susser, D. & Cabrera, L. Brain data in context: are new rights the way to mental and brain privacy? AJOB Neurosci. 5, 1–12 (2023).
Fins, J. J. The unintended consequences of Chile’s neurorights constitutional reform: moving beyond negative rights to capabilities. Neuroethics 15, 26 (2022).
Rainey, S. Neurorights as Hohfeldian privileges. Neuroethics 16, 9 (2023).
Herrmann, S., Yuste, R. & Genser, J. Neurorights Foundation: Gap Analysis. Available at https://static1.squarespace.com/static/60e5c0c4c4f37276f4d458cf/t/6275130256dd5e2e11d4bd1b/1651839747023/Neurorights+Foundation+PUBLIC+Analysis+5.6.22.pdf (2022).
Library of the National Congress of Chile. Law 21383: Amends the Fundamental Charter, to Establish Scientific and Technological Development at the Service of People. Available at https://www.bcn.cl/leychile/navegar?idNorma=1166983&tipoVersion=0 (2021).
Republica de Chile Senado. C.N. BIll. Available at https://www.senado.cl/appsenado/templates/tramitacion/index.php?boletin_ini=13828-19 (2020).
Government of Spain. Carta Derechos Digitales. Available at https://www.lamoncloa.gob.es/presidente/actividades/Documents/2021/140721-Carta_Derechos_Digitales_RedEs.pdf (2021).
Yuste, R., Quadra-Salcedo, T. & Fernandez, M. G. Neurorights and new charts of digital rights: a dialogue. Indiana J. Global Leg. Studies 30, 1 (2023).
Organization of American States. Declaration of the Interamerican Juridical Committee on Neuroscience, Neurotechnologies and Human Rights: New Legal Challenges for the Americas. CJI/DEC. 01 (XCIX-O/21) (2021).
Committee of the Council of Europe. Committee on Bioethics of the Council of Europe, Strategic Action Plan on Human Rights and Technologies in Biomedicine (2020–2025). Adopted by the Committee on Bioethics (DH-BIO) at its 16th meeting (19–21 November 2019) (2019).
UNESCO. Report of the International Bioethics Committee of UNESCO, Ethical Issues of Neurotechnology, SHS/BIO/IBC28/2021/3Rev (2021).
OECD. Recommendation on Responsible Innovation in Neurotechnology, Adopted by the OECD Council on 11 December 2019 (2019).
United Nations. United Nations, Our Common Agenda—Report of the Secretary-General, New York 2021, par. 35 (2021).
Human Rights Council. Assessing the Human Rights Impact of Neurotechnology: Towards the Recognition of ‘Neurorights’. Available at https://www.ohchr.org/sites/default/files/documents/hrbodies/hrcouncil/advisorycommittee/session28/2022-08-09/AC28-Human-rights-impact-of-neurotechnology.docx (2022).
Lauter, K., Naehrig, M. & Vaikuntanathan, V. Can homomorphic encryption be practical? Available at https://eprint.iacr.org/2011/405.pdf (2011).
Dwork, C. Differential Privacy and the US Census. Available at https://dl.acm.org/doi/pdf/10.1145/3294052.3322188?download=true (2019).
Abadi, M. et al. Deep Learning with Differential Privacy. Available at https://dl.acm.org/doi/pdf/10.1145/2976749.2978318?download=true (2016).
McMahan, B. & Ramage, D. Federated Learning: Collaborative Machine Learning without Centralized Training Data. Available at https://ai.googleblog.com/2017/04/federated-learning-collaborative.html (2017).
Choudhury, O. et al. Differential privacy-enabled federated learning for sensitive health data. Preprint at https://arxiv.org/abs/1910.02578 (2020).
US Congress. Health Insurance Portability and Accountability Act of 1996. Public Law 104, 191 (1996).
Voigt, P. & Von dem Bussche, A. The EU general data protection regulation (GDPR). In A Practical Guide (Springer, 2017).
Rainey, S. et al. Is the European data protection regulation sufficient to deal with emerging data concerns relating to neurotechnology? J. Law Biosci. 7, lsaa051 (2020).
pubmed: 34386243
pmcid: 8355473
State of California. California Legislative Information. Title 1.81.5. California Consumer Privacy Act of 2018. Available at https://leginfo.legislature.ca.gov/faces/codes_displayText.xhtml?division=3.&part=4.&lawCode=CIV&title=1.81.5 (1988).
Observational Health Data Sciences and Informatics (OHDSI). Available at https://www.ohdsi.org/ (2023).
McMahan, H. B., Moore, E., Ramage, D. & Hampson, S. Communication-efficient learning of deep networks from decentralized data. Preprint at https://arxiv.org/abs/1602.05629 (2016).
Rieke, A., Yu, H., Robinson, D. & van Hoboken, J. Data Brokers in an Open Society (Open Society Foundation, London, UK, 2016).
Tanner, A. How data brokers make money off your medical records. Sci. Am. 314, 26–27 (2016).
pubmed: 26930824
Rocher, L., Hendrickx, J. M. & de Montjoye, Y.-A. Estimating the success of re-identifications in incomplete datasets using generative models. Nat. Commun. 10, 3069 (2019).
pubmed: 31337762
pmcid: 6650473
Sweeney, L. Simple demographics often identify people uniquely. Health (San Francisco) 671, 1–34 (2000).
Azemi, E. et al. Biosignal sensing device using dynamic selection of electrodes. US Patent 20230225659 A1 Available at https://ppubs.uspto.gov/pubwebapp/ (2023).
Government of the United Kingdom. Regulatory Horizons Council (RHC) Publishes Independent Recommendations on the Future Regulation of Neurotechnology and AI as a Medical Device. Available at https://www.gov.uk/government/news/regulatory-horizons-council-rhc-publishes-independent-recommendations-on-the-future-regulation-of-neurotechnology-and-ai-as-a-medical-device (2022).
European Union. Commission Implementing Regulation (EU) 2022/2346 of 1 December 2022 Laying Down Common Specifications for the Groups of Products without an Intended Medical Purpose Listed in Annex XVI to Regulation (EU) 2017/745 of the European Parliament and of the Council on Medical Devices. Available at https://eur-lex.europa.eu/eli/reg_impl/2022/2346/oj (2023).
US Department of Health and Human Services. The Belmont Report. Available at https://www.hhs.gov/ohrp/regulations-and-policy/belmont-report/read-the-belmont-report/index.html (1979).
Alamos, M. F. et al. A technochratic oath. In Protecting the Mind: Challenges in Law, Neuroprotection, and Neurorights (eds. Varela, L. & Lopez, P.) (Springer, 2022).