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Quantum Wave-Impulse Model of Consciousness: A Rigorous, Falsifiable, and Simulation-Validated Framework

Year: 2025
Type: article
Abstract: The scientific study of consciousness remains one of the most challenging frontiers in contemporary science. Classicalneurophysiology and cognitive neuroscience have achieved remarkable progress in mapping neural correlates of per-ception, attention, and memory. Yet, fundamental questions remain unresolved: How do distributed neural processesgive rise to unified subjective experience? What mechanisms underlie the sudden emergence of insight, intuition, orcreativity?Traditional models grounded in classical physics often treat cognition as a sequence of deterministic or stochasticcomputations. While such approaches capture many aspects of behavior, they face persistent limitations, includingthe binding problem, the explanation of qualia, and the unpredictability of intuitive leaps. These gaps suggest thatnon-classical principles may be required to complement existing accounts.In parallel, advances in quantum biology have demonstrated that quantum coherence and entanglement can persistin warm, noisy biological environments [lambert2013, engel2007]. Inspired by this evidence, a growing body ofinterdisciplinary research explores whether quantum dynamics may contribute to cognitive phenomena.In this work, we propose a unified Quantum Wave-Impulse Model of Consciousness (QWIM). The model integratesa wave framework, describing consciousness as a quantum state ψ(C, t) evolving in a multidimensional cognitiveHilbert space, with an impulse framework, formalizing thought formation as a two-phase process: an intuitive phase(superposition and entanglement) followed by a logical phase (collapse or decoherence).A central feature of the model is its empirical grounding. We introduce measurable parameters (Table I) that linkthe formalism to observable neurophysiological and behavioral correlates. We provide explicit positive predictionsand falsification criteria, ensuring that the framework is testable with current or near-future neurotechn
Language: English
Field: Psychology
Open Access status: green
OpenAlex ID: W7102411741
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