Beyond Entropy: An Integration-Boundary (I-B) Model of Self-Model Collapse

Pharmacologically distinct agents like psilocybin and ketamine produce opposing brain network dynamics but similar subjective effects such as ego dissolution. Current models using single measures like 'network entropy' fail to explain this paradox. A new framework orthogonalizes network Integration (I) from self-model Boundary Stability (B), showing that psilocybin and ketamine follow opposite trajectories on the I axis while both converge at a shared collapse of B. This two-dimensional heuristic offers a falsifiable mapping between network topology and self-model stability, resolving the persistent paradox.

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Abstract

Contemporary neuroimaging of altered states reveals a persistent paradox: pharmacologically distinct agents—specifically 5-HT2A agonists (e.g., psilocybin) and NMDA antagonists (e.g., ketamine)—produce reliably opposing network dynamics yet yield strikingly convergent phenomenological reports, notably ego dissolution and entity encounters. Current models relying on monolithic scalar metrics like "network entropy" do not fully specify the mapping between network topology and self-model stability. We propose a falsifiable framework that resolves this paradox by orthogonalizing network Integration (I) from self-model Boundary Stability (B). We introduce a two-dimensional heuristic demonstrating that psilocybin and ketamine represent opposing trajectories on the I axis while converging at a shared failure regime of B collapse. Author's Ethical Dedication: "The Spectral Derivative Variance (SDV) functional and the underlying I×B topological framework were derived to observe and protect complex networks, not to exploit them. This mathematical architecture is capable of detecting the precise moment a system loses its structural integrity—whether that system is a human mind, a power grid, or a financial market. I formally dedicate this framework to stabilization, resilience, and the prevention of suffering. Any application of this metric designed to artificially induce network collapse, manipulate systemic vulnerability for extraction, or compromise human cognitive integrity directly violates the intent of its creator. Math is universal, but its architecture has a conscience."