Risk-calibrated sharing of human brain data.

Risk-calibrated protections for individual-level human brain data are needed because reidentification likelihood and inferential sensitivity vary, creating uneven misuse and mental-privacy risks.

• Why it matters: Brain data sharing faces pressure to accelerate discovery and improve outcomes, but concerns about misuse and threats to mental privacy create a need for clearer ethical guidance.
• What they did: The article reviews bioethics and neuroscience literature, adds insights from an NIH workshop, and uses normative analysis to propose lower-, medium-, and higher-risk categories based on inferential sensitivity and reidentification or linkage to harm-relevant groups.
• The result: It argues that matching safeguards to dataset-specific risks can maximize scientific and clinical value while protecting participants, with suggested measures spanning access limits, reduced granularity, consent approaches, and data-use governance.

AI summary of the abstract · may contain errors · not medical advice · read the paper.