The Human Connectome Project (HCP) has developed an integrated approach to neuroimaging data acquisition, analysis, and sharing, emphasizing high-resolution, multi-modal data collection and advanced processing techniques. The HCP-style paradigm includes seven core tenets: (1) collecting multimodal data from many subjects; (2) acquiring data at high spatial and temporal resolution; (3) preprocessing to minimize distortions and artifacts; (4) representing data using the natural geometry of brain structures; (5) accurately aligning brain areas across subjects; (6) using neurobiologically accurate brain parcellations; and (7) sharing data via user-friendly databases. The HCP has contributed significantly to neuroimaging, including advanced MRI protocols, high-quality data sharing, and software tools. The HCP-style paradigm has improved the accuracy and reliability of neuroimaging data, enabling better understanding of brain function and disorders. The HCP has also developed multi-modal parcellations, such as HCP_MMP1.0, which provide accurate and consistent brain area definitions. The HCP has also emphasized data sharing and advanced informatics for large-scale data management, including the ConnectomeDB database. The HCP's data and tools are widely used by the neuroscience community to advance research on brain structure and function.The Human Connectome Project (HCP) has developed an integrated approach to neuroimaging data acquisition, analysis, and sharing, emphasizing high-resolution, multi-modal data collection and advanced processing techniques. The HCP-style paradigm includes seven core tenets: (1) collecting multimodal data from many subjects; (2) acquiring data at high spatial and temporal resolution; (3) preprocessing to minimize distortions and artifacts; (4) representing data using the natural geometry of brain structures; (5) accurately aligning brain areas across subjects; (6) using neurobiologically accurate brain parcellations; and (7) sharing data via user-friendly databases. The HCP has contributed significantly to neuroimaging, including advanced MRI protocols, high-quality data sharing, and software tools. The HCP-style paradigm has improved the accuracy and reliability of neuroimaging data, enabling better understanding of brain function and disorders. The HCP has also developed multi-modal parcellations, such as HCP_MMP1.0, which provide accurate and consistent brain area definitions. The HCP has also emphasized data sharing and advanced informatics for large-scale data management, including the ConnectomeDB database. The HCP's data and tools are widely used by the neuroscience community to advance research on brain structure and function.