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<p>This study introduces a quantum-inspired deep learning model that integrates principles of myelin plasticity and neural efficiency using quantum computing. A novel quantum-classical hybrid approach simulates adaptive myelin dynamics, enhancing learning rates and decision stability in workplace environments. Simulations demonstrate the model’s adaptive response to varying stress levels and motivational states, providing insights into how myelin thickness, quantum entanglement, and consciousness proxy collectively influence cognitive performance. This interdisciplinary framework advances cognitive modeling and offers practical implications for workplace interventions targeting employee resilience and productivity.</p>

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Quantum-inspired modeling of workplace self-confidence: a hybrid approach integrating myelin plasticity and adaptive learning

  • 期刊论文

  • 发表日期：

    2025年7月19日

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  • Billel Arbaoui

摘要

This study introduces a quantum-inspired deep learning model that integrates principles of myelin plasticity and neural efficiency using quantum computing. A novel quantum-classical hybrid approach simulates adaptive myelin dynamics, enhancing learning rates and decision stability in workplace environments. Simulations demonstrate the model’s adaptive response to varying stress levels and motivational states, providing insights into how myelin thickness, quantum entanglement, and consciousness proxy collectively influence cognitive performance. This interdisciplinary framework advances cognitive modeling and offers practical implications for workplace interventions targeting employee resilience and productivity.