The Missing Control Boundary: Deterministic Governance Architecture for Brain-Computer Interfaces and Cognitive-Write Systems

This paper describes the first deterministic governance architecture for brain-computer interfaces and cognitive-write systems, the systems that will download information directly to the human brain. The problem. Seven jurisdictions have enacted neural data legislation. Vermont, Colorado, California, Montana, and Connecticut have operative laws on the books. The MIND Act is the first federal bill to address neurotechnology. The regulatory landscape is writing consent and authorization requirements into law, and no existing compliance platform provides the technical mechanism to enforce them at the point of execution. The architecture. The evidence-bound authority kernel renders binary, replayable, cryptographically attested authorization decisions for neural-interface operations as a pure function of signed inputs. It introduces five mechanisms absent from existing approaches: signed evidence envelopes binding each decision to the provenance of the neural signal; multi-party authority bundles requiring up to six independently signed roles for the most consequential operations; content manifests attesting to reversibility, scope, and safety of cognitive-write payloads; stream-scoped receipt chains scaling to concurrent subjects; and content-minimizing attestation proving what was authorized without archiving neural activity. Cognitive-write governance. The paper provides the first published taxonomy of cognitive-write operations: motor-skill downloads, factual knowledge writes, memory modifications, perceptual model installations, and cognitive framework updates. Each operation is governed independently with distinct authority requirements. Memory modification requires six-role authorization, including subject, clinician, content reviewer, ethics board, device controller, and legal authority. Threat model. Five attack scenarios are mapped to the architectural mechanisms that close them, including passive observation miscategorized as command, unauthorized memory modification, consent bypass, and decoder tampering. Part of the ExecLayer governance trilogy. The Agentic Governance Benchmark (AGB) measures machines. The Override Health Benchmark (OHB) measures humans. This paper governs the boundary where machines and humans merge. Architecture documentation. https://kernel.execlayer.io Patent pending. U.S. Provisional Application No. 64/099,216.