Brain Network Analysis

Brain network analysis uses neuroimaging data to model the brain as a complex network of interconnected regions, aiming to understand brain function and dysfunction. Current research focuses on developing advanced computational models, including graph neural networks, transformers, and ordinary differential equation-based approaches, to analyze dynamic brain activity and integrate information from multiple imaging modalities (e.g., fMRI and DTI). These methods are improving the identification of biomarkers for neurological disorders and enhancing our understanding of brain organization, with implications for diagnosis and treatment. The field is also actively addressing challenges like data heterogeneity, missing values, and the need for more interpretable models.