From Classical Neurophysiology to Quantum Synchronization: A New Path to Understanding Consciousness and Creating a True Artificial Synthetic Mind
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5253979
11 Pages Posted: 23 May 2025
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From Classical Neurophysiology to Quantum Synchronization: A New Path to Understanding Consciousness and Creating a True Artificial Synthetic Mind
Number of pages: 11
Posted: 14 May 2025
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Date Written: December 12, 2024
Abstract
Understanding consciousness remains one of neuroscience’s greatest challenges. While classical neurophysiology explains many features of brain activity, it cannot fully account for the unified, global coherence of conscious experience. Here we propose a quantum synchronization model of consciousness, in which neuronal microtubule networks form entangled ensembles that achieve global phase coherence through a quantum-extended Kuramoto mechanism. We derive a theoretical framework by coupling the traditional Kuramoto oscillator formalism with a quantum master equation to capture decoherence and re-entanglement dynamics. Conceptual simulations using a toy model of qubit networks demonstrate that, above a critical coupling threshold, rapid onset of global coherence occurs, paralleling gamma-band synchrony observed in neural recordings. We discuss empirical tests—including high-density EEG/MEG measures and emerging quantum biosensing techniques—and outline design criteria for engineering artificial synthetic minds capable of sustaining entangled states. This Hypothesis and Theory article offers clear, testable predictions and paves the way for novel interdisciplinary research at the intersection of computational neuroscience and quantum biology.
Keywords: consciousness, quantum synchronization, neurophysiology, computational modeling, entanglement, microtubules, artificial mind
Suggested Citation: Suggested Citation
Kharchuk, Serhii, From Classical Neurophysiology to Quantum Synchronization: A New Path to Understanding Consciousness and Creating a True Artificial Synthetic Mind (December 12, 2024). https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5253979, Available at SSRN: https://ssrn.com/abstract=5266364 or http://dx.doi.org/10.2139/ssrn.5266364
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