Consciousness Between Fact and Value: A Triadic Neurophenomenology
OSF Preprints January 1, 2026 Peer reviewed DOI: 10.17605/osf.io/dgkr6 via OpenAlex
Summary
The paper presents a new triadic neurophenomenological framework that connects neuroscience with embodied and phenomenological views to explore how consciousness relates empirical facts, conceptual meanings, and normative values. It proposes three core domains—object, idea, and relation—linked by consciousness. The framework suggests testable hypotheses about different cognitive processes and introduces methods for empirical research in neuroscience and artificial intelligence, highlighting the gap in current AI systems regarding axiological understanding.
Study at a glance
| Key finding | The framework predicts distinct neural and experiential signatures for fact-, idea-, and relation-based cognition. |
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Abstract
This project hosts materials related to the paper: Hammat, K. (2026). Consciousness Between Fact and Value: A Triadic Neurophenomenology. Zenodo. https://doi.org/10.5281/zenodo.18669043 For citation purposes, please cite the Zenodo DOI above. The paper introduces a novel triadic neurophenomenological framework that integrates neuroscience with embodied and phenomenological perspectives to explain how consciousness mediates between empirical facts, conceptual meaning, and normative values. The model posits three irreducible domains — object (material), idea (mental), and relation (axiological) — unified through consciousness. The paper advances testable hypotheses predicting distinct neural and experiential signatures for fact-, idea-, and relation-based cognition, and outlines methods combining multimodal neuroimaging, representational similarity analysis, and micro-phenomenology. Additionally, the framework hypothesizes that reflexive self-consciousness may emerge from recursive interaction between mental and axiological domains, analogous to iterative dynamics in complex systems. A cross-domain classification principle — cohesion, attraction, and stability — is introduced, mapping these structural characteristics across the three domains within the triadic ontology, and providing a conceptual scaffold for empirical operationalization in neuroscience. Finally, the triadic criterion is applied to artificial intelligence, clarifying why current systems simulate object/idea processing yet lack axiological participation. This framework preserves scientific intelligibility while affirming the normative authority of value, offering a foundation for interdisciplinary research across neuroscience, ethics, and AI.