The human connectome is a comprehensive structural description of the human brain, essential for understanding brain function and structure. The article discusses the need for a detailed connectome, which would provide insights into how brain function emerges from its structural substrate. It outlines a research strategy to create this connectome, emphasizing the importance of integrating anatomical and functional data. The connectome would serve as a unified, time-invariant neuroinformatics resource, enabling the study of brain function across various areas of neuroscience. The connectome is defined by two main descriptors: neural elements and neural connections. Neural elements include superordinate or subordinate structures, their positions, and physiological metadata. Neural connections are represented in a matrix, with entries indicating the presence or absence of connections. The connectome faces challenges, including the complexity of the human brain and the difficulty in defining basic structural elements. It is proposed that the connectome be built at multiple scales: microscale (single neurons and synapses), macroscale (brain regions and pathways), and mesoscale (minicolumns and their connections). At the macroscale, the connectome could be built using diffusion-weighted imaging and tractography to map brain regions and pathways. At the mesoscale, minicolumns, which are basic functional units, could be used to describe brain connectivity. The connectome would also need to account for individual variability and development, as brain connectivity varies between individuals and changes over time. The article outlines a five-step strategy for compiling the connectome, including diffusion-weighted imaging, functional connectivity analysis, cluster analysis, comparison with macaque data, and validation. It also discusses the importance of population analysis and the integration of data from various sources. The connectome has the potential to significantly impact neuroscience by providing a detailed structural framework for understanding brain function, disease, and recovery. It could also serve as a foundation for computational models and help in the development of new therapies. The connectome is a complex and evolving project that requires extensive collaboration, data collection, and analysis.The human connectome is a comprehensive structural description of the human brain, essential for understanding brain function and structure. The article discusses the need for a detailed connectome, which would provide insights into how brain function emerges from its structural substrate. It outlines a research strategy to create this connectome, emphasizing the importance of integrating anatomical and functional data. The connectome would serve as a unified, time-invariant neuroinformatics resource, enabling the study of brain function across various areas of neuroscience. The connectome is defined by two main descriptors: neural elements and neural connections. Neural elements include superordinate or subordinate structures, their positions, and physiological metadata. Neural connections are represented in a matrix, with entries indicating the presence or absence of connections. The connectome faces challenges, including the complexity of the human brain and the difficulty in defining basic structural elements. It is proposed that the connectome be built at multiple scales: microscale (single neurons and synapses), macroscale (brain regions and pathways), and mesoscale (minicolumns and their connections). At the macroscale, the connectome could be built using diffusion-weighted imaging and tractography to map brain regions and pathways. At the mesoscale, minicolumns, which are basic functional units, could be used to describe brain connectivity. The connectome would also need to account for individual variability and development, as brain connectivity varies between individuals and changes over time. The article outlines a five-step strategy for compiling the connectome, including diffusion-weighted imaging, functional connectivity analysis, cluster analysis, comparison with macaque data, and validation. It also discusses the importance of population analysis and the integration of data from various sources. The connectome has the potential to significantly impact neuroscience by providing a detailed structural framework for understanding brain function, disease, and recovery. It could also serve as a foundation for computational models and help in the development of new therapies. The connectome is a complex and evolving project that requires extensive collaboration, data collection, and analysis.