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Published on: January 26, 2024
Risk-calibrated sharing of human brain data.
Saskia Hendriks1,2, Andrea C Beckel-Mitchener3, James Eberwine4
1Department of Bioethics, NIH Clinical Center, Bethesda, MD 20892, USA.
Brain : a Journal of Neurology
|June 19, 2026
Summary
Sharing human brain data accelerates discovery but raises privacy concerns. Responsible sharing requires risk-based protections to balance scientific value with participant safety and trust.
Area of Science:
- Neuroscience
- Bioethics
- Data Science
Background:
- Growing pressure to share human brain data for neurological and psychiatric disorder research.
- Concerns exist regarding brain data misuse and mental privacy threats.
- Need for clearer ethical guidance on brain data sharing.
Purpose of the Study:
- Review bioethics and neuroscience literature on human brain data sharing risks.
- Analyze risks using NIH workshop insights and normative analysis.
- Propose a risk-based framework for responsible brain data sharing.
Main Methods:
- Literature review of bioethics and neuroscience.
- Analysis of National Institutes of Health (NIH) workshop insights.
- Normative ethical analysis of brain data risks and benefits.
Main Results:
- Brain data sharing risks are not uniform; they depend on re-identification likelihood and inference sensitivity.
- Certain brain data types pose higher risks due to re-identification and sensitive inferences.
- Risk mitigation strategies may impact scientific data value.
Conclusions:
- Responsible brain data sharing necessitates calibrating protections to dataset-specific risks.
- A tiered approach (lower, medium, higher risk) based on inferential sensitivity and re-identification likelihood is proposed.
- Safeguards include access restrictions, informed consent, and data-use governance to maximize value while protecting participants.
