Benefits of sharing neurophysiology data from the BRAIN Initiative Research Opportunities in Humans Consortium

Rahimzadeh, Vasiliki; Jones, Kathryn Maxson; Majumder, Mary A.; Kahana, Michael J.; Rutishauser, Ueli; Williams, Ziv M.; Cash, Sydney S.; Paulk, Angelique C.; Zheng, Jie; Beauchamp, Michael S.; Collinger, Jennifer L.; Pouratian, Nader; McGuire, Amy L.; Sheth, Sameer A.; Adolphs, Ralph; Andersen, Richard A.; Baltuch, Gordon; Brunner, Peter; Cash, Sydney S.; Chang, Edward; Collinger, Jennifer L.; Crone, Nathan; Fedorenko, Evelina; Fried, Itzhak; Gold, Josh; Henderson, Jaimie; Hochberg, Leigh; Howard, Matthew; Kahana, Michael J.; Magnotti, John; Mamelak, Adam; Pouratian, Nader; Richardson, Robert Mark; Rutishauser, Ueli; Schalk, Gerwin; Schroeder, Charlie; Shenoy, Krishna; Sheth, Sameer A.; Suthana, Nanthia; Tandon, Nitin; Williams, Ziv M.; Wolpaw, Jonathan

doi:10.1016/j.neuron.2023.09.029

Cited by 4 publications

(1 citation statement)

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“…These gaps in data protection are made more complex by enduring uncertainties around health data ownership, given the multiple stakeholder groups that aid in its collection, storage, management and stewardship, which complicate understandings about what various entities are permitted to do with neural data (e.g., buy, sell, exchange). Outside of the consumer space, research groups such as those in the BRAIN Initiative, the National Institutes of Health and the National Institutes of Mental Health are encouraged and even mandated to share neural data with the research community in order to promote reuse of neural data in pursuit of new research directions and scientific discoveries and to minimize cost and waste around new data acquisition (Rahimzadeh et al, 2023). These well-intentioned policies are accompanied by an important tradeoff, particularly the risks that open data sharing introduces for data subjects (research participants) who are placed at greater risk for reidentification as capacities for data fusion and triangulation continue to expand.…”

Section: Considerations Related To Informed Consent and Privacymentioning

confidence: 99%

Ethical considerations for integrating multimodal computer perception and neurotechnology

Hurley,

Sonig,

Herrington

et al. 2024

Front. Hum. Neurosci.

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BackgroundArtificial intelligence (AI)-based computer perception technologies (e.g., digital phenotyping and affective computing) promise to transform clinical approaches to personalized care in psychiatry and beyond by offering more objective measures of emotional states and behavior, enabling precision treatment, diagnosis, and symptom monitoring. At the same time, passive and continuous nature by which they often collect data from patients in non-clinical settings raises ethical issues related to privacy and self-determination. Little is known about how such concerns may be exacerbated by the integration of neural data, as parallel advances in computer perception, AI, and neurotechnology enable new insights into subjective states. Here, we present findings from a multi-site NCATS-funded study of ethical considerations for translating computer perception into clinical care and contextualize them within the neuroethics and neurorights literatures.MethodsWe conducted qualitative interviews with patients (n = 20), caregivers (n = 20), clinicians (n = 12), developers (n = 12), and clinician developers (n = 2) regarding their perspective toward using PC in clinical care. Transcripts were analyzed in MAXQDA using Thematic Content Analysis.ResultsStakeholder groups voiced concerns related to (1) perceived invasiveness of passive and continuous data collection in private settings; (2) data protection and security and the potential for negative downstream/future impacts on patients of unintended disclosure; and (3) ethical issues related to patients’ limited versus hyper awareness of passive and continuous data collection and monitoring. Clinicians and developers highlighted that these concerns may be exacerbated by the integration of neural data with other computer perception data.DiscussionOur findings suggest that the integration of neurotechnologies with existing computer perception technologies raises novel concerns around dignity-related and other harms (e.g., stigma, discrimination) that stem from data security threats and the growing potential for reidentification of sensitive data. Further, our findings suggest that patients’ awareness and preoccupation with feeling monitored via computer sensors ranges from hypo- to hyper-awareness, with either extreme accompanied by ethical concerns (consent vs. anxiety and preoccupation). These results highlight the need for systematic research into how best to implement these technologies into clinical care in ways that reduce disruption, maximize patient benefits, and mitigate long-term risks associated with the passive collection of sensitive emotional, behavioral and neural data.

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Section: Considerations Related To Informed Consent and Privacymentioning

confidence: 99%