TEVSER: a theory of evolving self-representations
Frontiers in Human Neuroscience July 9, 2026 DOI: 10.3389/fnhum.2026.1858621 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Theoretical or philosophical paper Peer reviewed |
|---|---|
| Keywords | Hierarchy Constructive Consciousness Intellect Property philosophy Control management Subjectivity Cognitive science Artificial intelligence Conceptual framework Human intelligence Character mathematics Cybernetics Position finance Epistemology Construct python library Hierarchical organization Conceptual model Complex system |
| Key points | Proposes that consciousness arises as a graded property from a hierarchy of self-representations in living systems, offering testable hypotheses linking these levels to neural organization and behavior. |
Abstract
This paper proposes TEVSER (Theory of Evolving Self-Representations), a framework describing how increasingly complex forms of regulation give rise to psyche, consciousness, and intelligence. The central idea is that a living system is a self-regulating system that maintains homeostasis. Within this perspective, regulation can be described as a hierarchy of self-representations ( Ω ), emerging as control structures that guide behavior. Within this hierarchy, distinct functional levels correspond to qualitatively different forms of cognition. In particular, the framework identifies the emergence of a phenomenological internal world (Ω 2 ), spatial subjectivity (“here,” Ω 3 ), temporal presence (“now,” Ω 6 ), behavioral intelligence (Ω 8 ), self-consciousness (“who,” Ω 10 ), and abstract symbolic intellect (Ω 11 ). Within this perspective, consciousness is not treated as a singular entity but as a structured and graded property arising from the organization of self-representing systems. The framework offers a constructive approach to the hard problem of consciousness, addressing the apparent paradox between the material nature of the brain and the seemingly immaterial character of subjective experience. TEVSER integrates and extends existing approaches, including predictive coding, active inference, higher-order theories, and integrated information theory, by situating them within a unified hierarchical architecture. Importantly, the framework generates a set of testable hypotheses linking levels of self-representation to neural organization, behavior, and evolutionary complexity. These predictions provide a basis for empirical validation and position TEVSER not only as a conceptual model but as a research program for investigating consciousness and intelligence in biological and artificial systems.