This chapter examines the convergence of neuroscience and artificial intelligence through biomimetic approaches that draw inspiration from biological neural systems to enhance AI functionality and efficiency. The central focus addresses the stability-plasticity dilemma—the fundamental challenge of balancing new learning with knowledge preservation that confronts both biological and artificial systems. This chapter explores how the brain elegantly solves this dilemma through several key mechanisms. These include complementary learning systems, synaptic consolidation, metaplasticity, and structural plasticity. These biological solutions have inspired corresponding AI approaches including experience replay, elastic weight consolidation, and dynamic architectural growth. Key neuroplasticity principles are systematically examined for their translation into machine learning algorithms, from Hebbian learning and spike-timing-dependent plasticity to homeostatic regulation and neuromodulation. The analysis extends to broader brain organizational principles that are shaping next-generation AI architectures. These principles include hierarchical processing, predictive coding, attention mechanisms, embodied cognition, and social learning. Clinical applications demonstrate the practical impact through case studies in multiple sclerosis and poststroke rehabilitation. In these conditions, biomimetic AI approaches enable personalized neurorehabilitation strategies, closed-loop adaptive systems, and computational models that guide therapeutic interventions. This chapter emphasizes the bidirectional nature of this relationship, where neuroscientific discoveries inform AI development while advances in AI provide new computational frameworks for understanding brain function. This convergence promises more efficient, adaptable AI systems that better complement human capabilities while simultaneously advancing our understanding of neural mechanisms, creating a virtuous cycle of discovery and innovation at the intersection of brain science and artificial intelligence.