Connectivity Pattern

Connectivity patterns, describing the relationships between nodes in a network (e.g., brain regions, social actors, or components of a neural network), are studied to understand system-level behavior and function. Current research focuses on developing sophisticated graph-based models, including graph neural networks and transformers, to analyze both static and dynamic connectivity, often integrating multimodal data (e.g., fMRI, DTI, sMRI) to improve accuracy and interpretability. These analyses are crucial for advancing our understanding of complex systems in diverse fields, from neuroscience and disease diagnosis to social network analysis and the design of efficient artificial neural networks.