Governing Brain-Computer Interfaces: The Categorical Gap Hypothesis and a Five-Dimensional Global Typology of Neurotechnology Governance (2010-2026)

Abstract

Brain-computer interfaces (BCIs) have crossed into commercial deployment, yet no jurisdiction has devised governance commensurate with the technology's capacity to read from, and write to, the human nervous system. Most regulatory responses assimilate BCIs into inherited categories---medical devices, personal data, consumer products---creating a categorical gap: a structural mismatch between available institutional tools and neural-interface risks to mental privacy, bodily integrity, and cognitive autonomy. This article maps BCI governance across thirty-four jurisdictions, develops a reusable five-dimensional coding scheme (D1-D5) evaluating regulatory-object definition, neurorights recognition (L0-L3), responsibility allocation, brain data governance (BD0-BD3), and enforcement survivability, and derives four governance regimes: risk-containment, rights-constitutionalization, market-mediated soft governance, and security-exceptionalism. We formalize the core finding as the Categorical Gap Hypothesis: jurisdictions relying on inherited regulatory categories will systematically underperform in protecting mental privacy, allocating responsibility, and enforcing neurorights in non-clinical BCI deployments. The article provides a baseline analytical toolkit for future empirical, doctrinal, and policy research, positioning neurotechnology governance as a distinct field analytically irreducible to AI or medical device governance.