This chapter examines institutional models for maintaining scientific integrity in the rapidly evolving intersection of neuroscience and artificial intelligence research. As brain-computer interfaces achieve unprecedented capabilities to decode neural activity and AI algorithms’ ‘turbocharge’ neuroscience research, traditional governance frameworks prove inadequate. These frameworks struggle with unique challenges posed by brain data that operate continuously, algorithms capable of inferring mental states, and technologies that raise fundamental questions about mental privacy and cognitive liberty. This chapter analyzes three distinct institutional approaches: the Max Planck Society’s scientific self-control model featuring ombudspersons across 86 institutes who address 80% of integrity challenges before escalation, Finland’s national TENK framework where 105 research institutions voluntarily committed to transparency-based governance, and emerging specialized frameworks designed specifically for neuroscience-AI convergence challenges. Through systematic comparison of these models, the analysis reveals that effective governance requires moving beyond traditional research oversight. It must create multilevel frameworks that integrate internal advisory systems, external review mechanisms, transparent reporting processes, and international coordination mechanisms. UNESCO now recognizes these as essential for protecting human rights in the neurotechnology age. This chapter argues that as neuroscience research becomes increasingly powerful and consequential—with capabilities ranging from decoding Pink Floyd songs from neural activity to potential applications in surveillance—the institutional structures governing it must become equally sophisticated, creating architectures where scientific excellence and ethical consideration naturally align rather than compete. The analysis concludes that successful governance requires substantial ongoing investment in capacity building, proactive rather than reactive oversight approaches, and institutional innovations that can coordinate across different regulatory, cultural, and disciplinary contexts while maintaining essential protections for the brain data that presents unprecedented inferential risks about human identity, privacy, and autonomy.