<p>Delay mechanisms are fundamental for enabling temporal dynamics in neuromorphic systems, supporting critical functions such as information synchronization, sequential processing, and temporal learning. However, most existing delay regulation methods suffer from limited adaptability, narrow tuning ranges, and poor compatibility with event-driven neuromorphic architectures. To address these challenges, this paper proposes a biologically inspired delay regulation method based on myelinated neuron dynamics, achieving high adaptability, flexible and scalable delay modulation, and efficient hardware implementation. Specifically, a digital neuron model is first developed to validate the myelination mechanism and determine key parameter configurations. Based on this model, an analog myelinated neuron circuit is designed and evaluated through PSpice simulations and hardware prototype experiments. Furthermore, the effects of synaptic weight, myelin segment number, and degree of myelination on delay modulation are systematically analyzed. The proposed design enables dynamic adjustment of delays according to practical requirements, maintaining low hardware overhead while providing precise and flexible temporal control, thus offering a foundation for programmable, efficient, and temporally aware neuromorphic systems.</p>