The Robles Quiroz Equation: An Integration-Boundary (I-B) Model of Self-Model Collapse
Zenodo (CERN European Organization for Nuclear Research) May 3, 2026 DOI: 10.5281/zenodo.20014263 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Theoretical or philosophical paper Peer reviewed |
|---|---|
| Keywords | Heuristic Network topology Boundary topology Falsifiability Topology electrical circuits Property philosophy Stability learning theory Artificial intelligence Mathematical economics Inverse problem |
| Key points | Proposes that orthogonalizing network Integration from self-model Boundary Stability resolves the paradox of opposing network dynamics from psilocybin and ketamine producing convergent ego dissolution and entity encounters. |
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.