Alzheimer’s disease (AD) is an irreversible, progressive neurodegenerative disorder characterized by cognitive and memory impairments, accompanied by brain atrophy. With no effective treatment available, early diagnosis and slowing disease progression are crucial clinical priorities. Research indicates that brain structural and functional connectivity play vital roles in AD pathology, closely related to cognitive abilities and clinical manifestations. This study proposes a multimodal structural-functional coupling model to explore the mechanisms between brain structural connections and neural activity, providing a comprehensive analysis of brain structure-function integration. By analyzing and validating data based on specific white matter network functions and neural connectivity changes, we aim to develop quantitative diagnostic indicators for AD, predict disease severity and cognitive function changes, and achieve disease diagnosis and treatment evaluation. This approach will enhance our understanding of AD progression and potentially improve patient outcomes through earlier intervention and more targeted therapies.