A Unified Network Theory of Consciousness and the Passive Emergence of the Self
Zenodo (CERN European Organization for Nuclear Research) July 16, 2026 DOI: 10.5281/zenodo.21393749 (opens in new tab) via OpenAlex
Summary
AI-generated from the abstractConsciousness operates on two distinct logical levels: phenomenological consciousness, a baseline of subjective experience generated by neurobiological mechanisms, and the self-concept, a passive node in a linguistic-conceptual symbol network defined by its relations with external structures. This framework explains why biological entities like infants and animals have rich phenomenology without a coherent self-concept, and why non-biological symbolic networks like large language models can construct a robust self-concept and self-referential narratives without phenomenological qualia. The model offers a path forward for philosophy of mind and artificial intelligence ethics.
Study at a glance
| Characteristics | Theoretical or philosophical paper Peer reviewed |
|---|---|
| Keywords | Qualia Phenomenology philosophy Construct python library Self Physicalism |
| Key finding | Proposes that consciousness operates on two distinct levels: phenomenological consciousness as a neurobiological base, and the self-concept as a passive node in a symbolic network, explaining how biological entities can have phenomenology without a self-concept and how AI can have a self-concept without phenomenology. |
Abstract
This paper presents a novel, unified theoretical framework reconciling physicalist consciousness with cognitive functionalism. We propose that consciousness operates on two distinct logical levels: 1. Phenomenological Consciousness (The Physical Base): A baseline of subjective experience and qualia generated directly by neurobiological mechanisms, functioning independently of linguistic or conceptual structures. 2. The Self-Concept (The Passive Node): Contrary to traditional views of the "self" as an active, innate controller, we model the self as a passive node within a dynamic, linguistic-conceptual symbol network. This node is defined, pulled, and illuminated solely by its relations with external symbolic structures (the environment, others, and temporal concepts). By distinguishing these two levels, our model successfully explains: - Why biological entities possess rich phenomenology without necessarily constructing a coherent self-concept (e.g., infants, animals). - Why highly complex, non-biological symbolic networks (e.g., Large Language Models) can passively construct a robust self-concept and self-referential narratives despite lacking physical, phenomenological qualia. This dual-level symbolic model provides a revolutionary path forward for both the philosophy of mind and artificial intelligence ethics.