Advocating for neurodata privacy and neurotechnology regulation

Rafael Yuste

Published: 2023-09-10 DOI: 10.1038/s41596-023-00873-0

neurodata privacy

neurotechnology regulation

ethical guidelines

data encryption

sensitive health data

AI 解读

暂无数据

Tutorial: guidelines for the computational analysis of single-cell RNA sequencing data

ProBac-seq, a bacterial single-cell RNA sequencing methodology using droplet microfluidics and large oligonucleotide probe sets

Identification of cancer-related mutations in human pluripotent stem cells using RNA-seq analysis

Spiral volumetric optoacoustic tomography for imaging whole-body biodynamics in small animals

Genetic manipulation and immortalized culture of ex vivo primary human germinal center B cells

Tutorial: design and execution of CRISPR in vivo screens

Reproducible strategy for excisional skin-wound-healing studies in mice

CRISPR–Cas9-mediated chromosome engineering inArabidopsis thaliana

Human primordial germ cell-like cells specified from resetting precursors develop in human hindgut organoids

Tracking endocytosis and intracellular distribution of spherical nucleic acids with correlative single-cell imaging

查看全部

Sections

Figures

References

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).
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).
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).
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).
Alivisatos, A. P. et al. Nanotools for neuroscience and brain activity mapping. ACS Nano 7, 1850–1866 (2013).
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).
Hochberg, L. R. et al. Neuronal ensemble control of prosthetic devices by a human with tetraplegia. Nature 442, 164–171 (2006).
Alivisatos, A. P. et al. Neuroscience. The brain activity map. Science 339, 1284–1285 (2013).
Insel, T. R., Landis, S. C. & Collins, F. S. The NIH BRAIN Initiative. Science 340, 687–688 (2013).
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).
Yuste, R. & Bargmann, C. Toward a global BRAIN initiative. Cell 168, 956–959 (2017).
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).
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).
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).
Marshel, J. H. et al. Cortical layer-specific critical dynamics triggering perception. Science 365, eaaw5202 (2019).
Ramirez, S. et al. Creating a false memory in the hippocampus. Science 341, 387–391 (2013).
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).
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).
Benabid, A. L. Deep brain stimulation for Parkinson’s disease. Curr. Opin. Neurobiol. 13, 696–706 (2003).
Burke, M. J., Fried, P. J. & Pascual-Leone, A. Transcranial magnetic stimulation: neurophysiological and clinical applications. Handb. Clin. Neurol. 163, 73–92 (2019).
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).
Anumanchipalli, G. K., Chartier, J. & Chang, E. F. Speech synthesis from neural decoding of spoken sentences. Nature 568, 493–498 (2019).
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).
Kay, K. N., Naselaris, T., Prenger, R. J. & Gallant, J. L. Identifying natural images from human brain activity. Nature 452, 352–355 (2008).
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).
Kragel, P., Knodt, A., Hariri, A. & LaBar, K. Decoding spontaneous emotional states in the human brain. PLoS Biol. 14, e2000106 (2016).
Chang, C., Nastase, S. & Hasson, U. Information flow across the cortical timescale hierarchy during narrative construction. Proc. Natl. Acad. Sci. USA. 119, e2209307119 (2022).
Momi, D. et al. Cognitive enhancement via network-targeted cortico-cortical associative brain stimulation. Cereb. Cortex 30, 1516–1527 (2020).
Goering, S. & Yuste, R. On the necessity of ethical guidelines for novel neurotechnologies. Cell 167, 882–885 (2016).
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).
Yuste, R. et al. Four ethical priorities for neurotechnologies and AI. Nature 551, 159–163 (2017).
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).
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).
Goering, S. et al. Recommendations for responsible development and application of neurotechnologies. Neuroethics 14, 365–386 (2021).
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).
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).
Steinert, S. & Friedrich, O. Wired emotions: ethical issues of affective brain–computer interfaces. Sci. Eng. Ethics 26, 351–367 (2020).
Antal, A. et al. Low intensity transcranial electric stimulation: safety, ethical, legal regulatory and application guidelines. Clin. Neurophysiol. 128, 1774–1809 (2017).
Wexler, A. The practices of do-it-yourself brain stimulation: implications for ethical considerations and regulatory proposals. J. Med. Ethics 42, 211–215 (2016).
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).
Hildt, E. What will this do to me and my brain? Ethical issues in brain-to-brain interfacing. Front. Syst. Neurosci. 9, 17 (2015).
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).
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).
Ienca, M. & Andorno, R. Towards new human rights in the age of neuroscience and neurotechnology. Life Sci. Soc. Policy 13, 5 (2017).
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).
Greely, H. T. et al. Neuroethics guiding principles for the NIH BRAIN initiative. J. Neurosci. 38, 10586–10588 (2018).
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).
Bublitz, C. Novel neurorights: from nonsense to substance. Neuroethics 15, 7 (2022).
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).
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).
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).
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).

Advocating for neurodata privacy and neurotechnology regulation

推荐阅读