Energy supply plays a key role in metabolism and signal transmission of biological individuals, neurons in a complex electromagnetic environment must be accompanied by the absorption and release of energy. In this paper, the discharge mode and the Hamiltonian energy are investigated within the Izhikevich neuronal model driven by external signals in the presence of electromagnetic induction. It is found that multiple electrical activity modes can be observed by changing external stimulus, and the Hamiltonian energy is more dependent on the discharge mode. In particular, there is a distinct shift and transition in the Hamiltonian energy when the discharge mode is switched quickly. Furthermore, the amplitude of periodic stimulus signal has a greater effect on the neuronal energy compared to the angular frequency, and the average Hamiltonian energy decreases when the discharge rhythm becomes higher. Based on the principle of energy minimization, the system should choose the minimum Hamiltonian energy when maintaining various trigger states to reduce the metabolic energy of signal processing in biological systems. Therefore, our results give the possible clues for predicting and selecting appropriate parameters, and help to understand the sudden and paroxysmal mechanisms of epilepsy symptoms.

能量供应在生物个体的新陈代谢和信号传递中起着关键作用，复杂电磁环境中的神经元必须伴随着能量的吸收和释放。在本文中，在存在电磁感应的情况下，在外部信号驱动的 Izhikevich 神经元模型中研究了放电模式和哈密顿能量。发现通过改变外部刺激可以观察到多种电活动模式，并且哈密顿能量更依赖于放电模式。特别是，当放电模式快速切换时，哈密顿能量会发生明显的转变和转变。此外，与角频率相比，周期性刺激信号的幅度对神经元能量的影响更大，当放电节律变高时，平均哈密顿能量降低。基于能量最小化原则，系统在维持各种触发状态时应选择最小的哈密顿能量，以减少生物系统中信号处理的代谢能量。因此，我们的研究结果为预测和选择合适的参数提供了可能的线索，有助于理解癫痫症状的突发性和阵发性机制。