Brain Network

Brain network research aims to understand the complex interactions between brain regions, using neuroimaging data to map functional and structural connectivity. Current research focuses on developing advanced machine learning models, including graph neural networks, transformers, and diffusion models, to analyze these networks, often incorporating multimodal data (e.g., fMRI, EEG) and addressing challenges like noise and data heterogeneity. These advancements are improving the accuracy of disease diagnosis (e.g., Alzheimer's, autism, schizophrenia) and providing deeper insights into brain function and cognitive processes, with implications for personalized medicine and treatment strategies.