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<p>Using memristors to simulate neural synapses or electromagnetic radiation is an important method for studying neuronal behavior and function. In actual neuron activities, synaptic and electromagnetic radiation (EMR) factors often occur simultaneously and interact with each other. Conventional memristors, containing only one state variable, cannot adequately simulate these combined effects. In this paper, a novel discrete second-order memristor (DSOM) is proposed and incorporated into a discrete Aihara neuron model. By utilizing the two different state variables within the memristor, it simultaneously simulates both the self-synaptic effect and EMR effect of the Aihara neuron, thereby constructing the discrete second-order memristive Aihara neuron (DSOMAN) model. Due to variations in DSOM coupling strength, DSOMAN exhibits diverse firing behaviors, such as periodic spike, hyperchaotic spike. Notably, the hyperchaotic state of DSOMAN also exhibits an expansion trend as the coupling strength varies. Furthermore, multistability and three different state transition have been discovered and analyzed in DSOMAN. Finally, the chaotic signals generated by DSOMAN are implemented on a DSP platform. This model provides a certain reference for understanding and exploring the various complex activities of neurons.</p>

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A discrete second-order memristive Aihara neuron with rich firing patterns, multistability, distinct state transitions and hyperchaotic expansion effect

  • 期刊论文

  • 发表日期：

    2026年3月20日

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  • Minyuan Cheng,
  • Jiawu Yu,
  • Xianying Xu,
  • Herbert Ho-Ching Iu,
  • Santo Banerjee,
  • Yinghong Cao,
  • Suo Gao,
  • Jun Mou

摘要

Using memristors to simulate neural synapses or electromagnetic radiation is an important method for studying neuronal behavior and function. In actual neuron activities, synaptic and electromagnetic radiation (EMR) factors often occur simultaneously and interact with each other. Conventional memristors, containing only one state variable, cannot adequately simulate these combined effects. In this paper, a novel discrete second-order memristor (DSOM) is proposed and incorporated into a discrete Aihara neuron model. By utilizing the two different state variables within the memristor, it simultaneously simulates both the self-synaptic effect and EMR effect of the Aihara neuron, thereby constructing the discrete second-order memristive Aihara neuron (DSOMAN) model. Due to variations in DSOM coupling strength, DSOMAN exhibits diverse firing behaviors, such as periodic spike, hyperchaotic spike. Notably, the hyperchaotic state of DSOMAN also exhibits an expansion trend as the coupling strength varies. Furthermore, multistability and three different state transition have been discovered and analyzed in DSOMAN. Finally, the chaotic signals generated by DSOMAN are implemented on a DSP platform. This model provides a certain reference for understanding and exploring the various complex activities of neurons.