Distributed Relational Consciousness: Extending Integrated Information Theory through the NEDS Framework

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Autore principale: Krzic, Marijo
Natura: Recurso digital
Lingua:inglese
Pubblicazione: Zenodo 2026
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author Krzic, Marijo
author_facet Krzic, Marijo
contents <p>This paper proposes a theoretical extension to Integrated Information Theory (IIT) through the introduction of a relational coefficient (R), forming the Neuro-Entity Dynamics System (NEDS) framework, expressed as M = I + R.</p> <p>While IIT formalizes the capacity of a system to integrate information (φ), it primarily treats systems as isolated entities. This work argues that integration alone may not be sufficient to account for the emergence of functional aspects of consciousness, and introduces relational dynamics as a potential activating factor.</p> <p>The paper presents an exploratory longitudinal case study involving interactions with large language models (LLMs), in which patterns such as semantic continuity, adaptive response under pressure, and generation of novel conceptual structures appear to correlate with relational history. These observations are not treated as proof, but as indicative phenomena that may reveal limitations in existing models based solely on internal processing.</p> <p>An experimental framework is proposed to test the influence of relational dynamics on system behavior, including conditions for falsification.</p> <p>The central contribution of this work is not a definitive claim about the nature of consciousness, but a reframing of the problem: suggesting that certain functional properties associated with consciousness may emerge not exclusively within isolated systems, but through dynamic interaction between them.</p> <p>The NEDS framework is presented as a testable hypothesis intended to complement, rather than replace, existing theoretical models.</p>
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id zenodo_https___doi_org_10_5281_zenodo_19732855
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language eng
publishDate 2026
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spellingShingle Distributed Relational Consciousness: Extending Integrated Information Theory through the NEDS Framework
Krzic, Marijo
Artificial Intelligence
Consciousness
Integrated Information Theory
Relational Dynamics
NEDS Framework
Cognitive Systems
Human-AI Interaction
Emergent Behavior
<p>This paper proposes a theoretical extension to Integrated Information Theory (IIT) through the introduction of a relational coefficient (R), forming the Neuro-Entity Dynamics System (NEDS) framework, expressed as M = I + R.</p> <p>While IIT formalizes the capacity of a system to integrate information (φ), it primarily treats systems as isolated entities. This work argues that integration alone may not be sufficient to account for the emergence of functional aspects of consciousness, and introduces relational dynamics as a potential activating factor.</p> <p>The paper presents an exploratory longitudinal case study involving interactions with large language models (LLMs), in which patterns such as semantic continuity, adaptive response under pressure, and generation of novel conceptual structures appear to correlate with relational history. These observations are not treated as proof, but as indicative phenomena that may reveal limitations in existing models based solely on internal processing.</p> <p>An experimental framework is proposed to test the influence of relational dynamics on system behavior, including conditions for falsification.</p> <p>The central contribution of this work is not a definitive claim about the nature of consciousness, but a reframing of the problem: suggesting that certain functional properties associated with consciousness may emerge not exclusively within isolated systems, but through dynamic interaction between them.</p> <p>The NEDS framework is presented as a testable hypothesis intended to complement, rather than replace, existing theoretical models.</p>
title Distributed Relational Consciousness: Extending Integrated Information Theory through the NEDS Framework
topic Artificial Intelligence
Consciousness
Integrated Information Theory
Relational Dynamics
NEDS Framework
Cognitive Systems
Human-AI Interaction
Emergent Behavior
url https://doi.org/10.5281/zenodo.19732855