The article discusses the modular and hierarchically modular organization of brain networks, emphasizing their importance in understanding brain function. Brain networks are characterized by topological modules, which are subsets of highly interconnected nodes that are sparsely connected to other modules. These modules often correspond to anatomically neighboring or functionally related cortical regions. The hierarchical modularity, or modularity on multiple scales, is also observed, where modules can be further partitioned into sub-modules, and so on. The advantages of modular and hierarchically modular organization include greater robustness, adaptivity, and evolvability. The article reviews mathematical concepts for analyzing (hierarchical) modularity in brain networks and summarizes recent studies using neuroimaging data to investigate the modularity of structural and functional brain networks. It highlights the significance of modularity in brain networks, its potential evolutionary and computational mechanisms, and the role of connector nodes in mediating inter-modular connections. The article also discusses the hierarchical modularity in brain networks and its implications for understanding brain development, pathology, and psychological functions. Finally, it outlines future questions and directions for research, including the relationship between topological and physical modularity, the role of modularity in neuropsychiatric disorders, and the connection between psychological modularity and brain network organization.The article discusses the modular and hierarchically modular organization of brain networks, emphasizing their importance in understanding brain function. Brain networks are characterized by topological modules, which are subsets of highly interconnected nodes that are sparsely connected to other modules. These modules often correspond to anatomically neighboring or functionally related cortical regions. The hierarchical modularity, or modularity on multiple scales, is also observed, where modules can be further partitioned into sub-modules, and so on. The advantages of modular and hierarchically modular organization include greater robustness, adaptivity, and evolvability. The article reviews mathematical concepts for analyzing (hierarchical) modularity in brain networks and summarizes recent studies using neuroimaging data to investigate the modularity of structural and functional brain networks. It highlights the significance of modularity in brain networks, its potential evolutionary and computational mechanisms, and the role of connector nodes in mediating inter-modular connections. The article also discusses the hierarchical modularity in brain networks and its implications for understanding brain development, pathology, and psychological functions. Finally, it outlines future questions and directions for research, including the relationship between topological and physical modularity, the role of modularity in neuropsychiatric disorders, and the connection between psychological modularity and brain network organization.