MET Brain Structure (MBS): A Structural Runtime Hypothesis for Embodied Cognition, Dreaming, Retrieval, Learning, and Cognitive Convergence

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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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-06-09
DOI
https://doi.org/10.5281/zenodo.20604632
Primary Topic
Cognitive Computing and Networks
Type
article
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article

MET Brain Structure (MBS): A Structural Runtime Hypothesis for Embodied Cognition, Dreaming, Retrieval, Learning, and Cognitive Convergence

Sizhe Tan
Zenodo (CERN European Organization for Nuclear Research)
Cognitive Computing and Networks
article

MET Brain Structure (MBS): A Structural Runtime Hypothesis for Embodied Cognition, Dreaming, Retrieval, Learning, and Cognitive Convergence

Sizhe Tan
article en

Abstract

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.

Zenodo (CERN European Organization for Nuclear Research)
Quality Education
Openalex Percentile: Top 5%
Cognitive Computing and Networks
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MET Brain Structure (MBS): A Structural Runtime Hypothesis for Embodied Cognition, Dreaming, Retrieval, Learning, and Cognitive Convergence — Sizhe Tan · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS