Exploratory hypothesis investigates cognitive organization principles, suggesting insights for neuroscience and AI systems.
MET Brain Structure (MBS) is an exploratory structural runtime hypothesis investigating possible organizational principles underlying biological cognition. The project emerged from research in Structural Intelligence, Calling Graphs, Function Tunnel Intelligence (FTI), Function Tunnel Math and Networks (FTMN), Autonomous Structural Intelligence (ASI), and Human-AI Hybrid Cognition. MBS proposes that many cognitive phenomena may be viewed through a common Trigger-Retrieval-Tunnel Architecture involving trigger systems, retrieval structures, graph and tunnel knowledge organization, embodied scene runtime, and continuous in-situ adaptation. The repository explores possible structural explanations for dreaming, danger response, memory recall, imagination, planning, navigation, learning, cognitive convergence, and trigger-centered runtime selection. MBS is not intended to replace neuroscience. Instead, it aims to provide a complementary structural perspective and a digital modeling framework that may help organize observations across neuroscience, cognitive science, animal behavior, artificial intelligence, and future human-AI hybrid intelligence systems.
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Sizhe Tan (2026) studied this question.
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