<p>Sharp wave–ripples (SWRs) and hippocampal sequence replay are central to memory consolidation. While learning-induced structuring of synaptic circuitry enables the emergence of replay and SWRs, learning is not merely a prerequisite—rather, the extent and duration of learning may fundamentally shape the progressive refinement of synaptic weight structures over time. However, how learning duration influences the stabilization of replay and SWR dynamics, and how prolonged learning shapes mature synaptic circuitry to support network-level activity, remain poorly understood. Here, we developed a biologically realistic network model of the hippocampal CA3 region to systematically investigate the effects of learning duration on sequence replay and SWR mediated by spike-timing-dependent and homeostatic plasticity. By analyzing the evolution of synaptic weight structures, replay performance, and SWR dynamics following learning of varying durations, we identified a mechanistic link between learning-driven synaptic weight reorganization and network-level dynamics. Prolonged learning progressively enhanced replay accuracy and stability, accompanied by more orderly and efficient SWR patterns. Notably, synaptic connections among thorny pyramidal cells evolved toward a sparse and focused architecture, characterized by selective strengthening of synapses between place cells with adjacent place fields and consolidation of local trajectory pathways. The structural organization of synaptic weights supports improved replay precision and enhanced stability of SWR dynamics. Together, these findings establish learning duration as a key determinant of synaptic weight structure maturation and network dynamical stability in hippocampal memory processing. Furthermore, this study clarifies how biologically plausible synaptic plasticity mechanisms support stable and efficient memory replay during consolidation.</p>