Formal Model of Consciousness based on Integrated Information Theory and Graph Representation
Zenodo (CERN European Organization for Nuclear Research) September 6, 2026 DOI: 10.5281/zenodo.22457445 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Theoretical or philosophical paper Peer reviewed |
|---|---|
| Key points | Proposes that representing the brain as a graph and quantifying integrated information via Φ(G) can yield a testable metric of consciousness, moving beyond descriptive approaches. |
Abstract
This paper proposes a novel formal model of consciousness grounded in the principles of Integrated Information Theory (IIT) and graph representation. The core idea is to represent the brain as a complex graph, where nodes correspond to neurons and edges denote synaptic connections. Utilizing IIT, we quantitatively assess the integrated information within this graph, aiming to correlate this measure with the subjective experience of consciousness. The model moves beyond purely descriptive approaches by introducing a mathematically rigorous framework. We define key concepts, including the graph structure (G = (V, E)), the measure of integrated information (Φ(G)), and the relationship between Φ and the level of consciousness. This work offers a foundation for future research exploring the neural correlates of consciousness and potentially providing a testable framework for IIT. The primary contribution lies in the systematic application of graph theory and IIT to create a quantifiable metric of consciousness, allowing for deeper analysis and theoretical development.