Brain Networks: Modules and Community Structure

This lecture delves into the concepts of modules and community structure within brain networks, exploring their functional and structural aspects. The presentation covers the natural modular structure of the functional connectome, the mathematical formulation of network modularity, and the Louvain algorithm for community detection. It also discusses the resolution limit in community detection, consensus clustering, and multilayer modularity. The dynamic modularity of brain networks during a motor learning task is analyzed, revealing stable modules across different training stages. The session concludes with a reminder about the upcoming midterm exam, emphasizing a mix of multiple-choice, open-ended, and out-of-the-box questions.