The Resonant Gate: A Dynamic-Coupling Model of Conversational Insight
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| Format: | Recurso digital |
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Zenodo
2025
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| _version_ | 1866901795180118016 |
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| author | Everett, Brandon |
| author_facet | Everett, Brandon |
| contents | <p>Models of social cognition and predictive processing have struggled to formalize the temporal dynamics of human conversation, particularly the process by which shared understanding is built and transformative insights are encoded. This paper addresses this gap by introducing the Resonant Gate model, an extension of the Emergent Gating Framework (Everett, 2025b). I propose that conversation is a process of dynamic coupling in which the coupling strength, κ(t), between two predictive systems evolves over time. This evolution produces a phenomenological experience I term "inverse-inertia": an initial, high-cost phase of reactive listening gives way to a low-cost, resonant state of mutual prediction. In this resonant state, predictable interaction is processed efficiently, but genuinely novel ideas generate a dramatically amplified novelty signal (N_h). This "novelty amplification" leads to robust, durable memory encoding of shared insights. The model provides a formal mechanism for the power of dialogue, reframing human connection as a computational prerequisite for profound, shared learning. I outline specific, falsifiable predictions regarding inter-brain coherence, the P300 ERP component, and the cognitive cost of rhythmic violation, providing a clear path to empirical validation.</p> <p><strong>Keywords:</strong> predictive processing, dynamic coupling, memory encoding, social cognition, conversation, inverse-inertia, inter-brain synchrony, P300, resonant gate</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_17351858 |
| institution | Zenodo |
| language | |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | The Resonant Gate: A Dynamic-Coupling Model of Conversational Insight Everett, Brandon <p>Models of social cognition and predictive processing have struggled to formalize the temporal dynamics of human conversation, particularly the process by which shared understanding is built and transformative insights are encoded. This paper addresses this gap by introducing the Resonant Gate model, an extension of the Emergent Gating Framework (Everett, 2025b). I propose that conversation is a process of dynamic coupling in which the coupling strength, κ(t), between two predictive systems evolves over time. This evolution produces a phenomenological experience I term "inverse-inertia": an initial, high-cost phase of reactive listening gives way to a low-cost, resonant state of mutual prediction. In this resonant state, predictable interaction is processed efficiently, but genuinely novel ideas generate a dramatically amplified novelty signal (N_h). This "novelty amplification" leads to robust, durable memory encoding of shared insights. The model provides a formal mechanism for the power of dialogue, reframing human connection as a computational prerequisite for profound, shared learning. I outline specific, falsifiable predictions regarding inter-brain coherence, the P300 ERP component, and the cognitive cost of rhythmic violation, providing a clear path to empirical validation.</p> <p><strong>Keywords:</strong> predictive processing, dynamic coupling, memory encoding, social cognition, conversation, inverse-inertia, inter-brain synchrony, P300, resonant gate</p> |
| title | The Resonant Gate: A Dynamic-Coupling Model of Conversational Insight |
| url | https://doi.org/10.5281/zenodo.17351858 |