Title: The Geometry of Consciousness as a Fundamental Constraint
Zenodo (CERN European Organization for Nuclear Research) September 6, 2026 DOI: 10.5281/zenodo.22499350 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Theoretical or philosophical paper Peer reviewed |
|---|---|
| Key points | Proposes that consciousness emerges from the geometry of interconnected neural networks, shaped by a 'geometry-based constraint' where networks refine internal representations, arguing this geometric structure, rather than computation alone, underlies subjective experience. |
Abstract
This paper explores the potential for a mathematical model to describe consciousness as an emergent property arising from the geometry of interconnected neural networks. Traditional theories focus on information processing, but we propose a novel framework – the 'geometry-based constraint' – suggesting that neural networks actively shape and refine their internal representations, directly influencing the geometry of consciousness. We detail this proposed model, its underlying mathematical principles, and its implications for understanding the fundamental constraints underlying subjective experience. The paper argues that consciousness isn't simply a product of computation, but a manifestation of the inherent geometric structure of the brain.