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<p>Understanding how different electrical components influence neuronal synchronization is essential for advancing neural circuit dynamics and therapeutic interventions. However, while previous studies have examined individual components separately, comprehensive comparative analyses of their integrated effects in coupled systems remain limited. This study investigates synchronization dynamics in coupled dual-capacitance neuronal models incorporated with three distinct electrical components: memristor (M), inductive coil (L), and Josephson junction (JJ). The neuronal models are driven by Bessel function-modulated external stimuli to generate rich dynamical behaviors. Using a switchable circuit design, we systematically analyze synchronization characteristics across varying coupling strengths, external stimulation parameters, and noise interference levels. Our results reveal distinct synchronization properties for each configuration: the L model demonstrates high sensitivity to frequency variations, the JJ model exhibits robust synchronization within specific parameter ranges, while the M model shows superior resilience against noise interference. These findings provide insights into component-specific contributions to neuronal synchronization and offer potential applications for neural network design and synchronization-based therapeutic approaches.</p>

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Tunable synchronization control of coupled neural dual-capacitance circuits via switchable components

  • 期刊论文

  • 发表日期：

    2025年11月8日

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  • Zhenpu Liu,
  • Suyuan Huang,
  • Yuan Chai,
  • Guodong Huang,
  • Rui Zhu

摘要

Understanding how different electrical components influence neuronal synchronization is essential for advancing neural circuit dynamics and therapeutic interventions. However, while previous studies have examined individual components separately, comprehensive comparative analyses of their integrated effects in coupled systems remain limited. This study investigates synchronization dynamics in coupled dual-capacitance neuronal models incorporated with three distinct electrical components: memristor (M), inductive coil (L), and Josephson junction (JJ). The neuronal models are driven by Bessel function-modulated external stimuli to generate rich dynamical behaviors. Using a switchable circuit design, we systematically analyze synchronization characteristics across varying coupling strengths, external stimulation parameters, and noise interference levels. Our results reveal distinct synchronization properties for each configuration: the L model demonstrates high sensitivity to frequency variations, the JJ model exhibits robust synchronization within specific parameter ranges, while the M model shows superior resilience against noise interference. These findings provide insights into component-specific contributions to neuronal synchronization and offer potential applications for neural network design and synchronization-based therapeutic approaches.