Current artificial neurons, the foundation of modern AI, lack the time-dependent behaviors intrinsic to biological neurons, limiting their ability to dynamically regulate emotions and exhibit proactive adaptability. This study introduces a novel computational neuron model inspired by electrical engineering, leveraging RC circuits with capacitors and resistors to emulate the time-dependent, dynamic interactions of human emotions such as satisfaction, ambition, and fear. Experimental results demonstrate the model’s ability to adapt to diverse inputs, maintain emotional stability, and simulate human-like emotional responses. This work establishes a foundation for creating more autonomous, adaptive, and emotionally intelligent AI systems, paving the way for advanced applications in human-like interaction and decision-making.