Functional Connectome

Functional connectomics investigates the brain's functional organization by mapping the dynamic relationships between different brain regions, primarily using fMRI data. Current research heavily utilizes graph neural networks (GNNs), including graph convolutional networks and transformers, to analyze these complex networks, often incorporating multimodal data (e.g., structural and functional connectivity) and focusing on applications like disease diagnosis (e.g., Alzheimer's, autism, Parkinson's) and prediction of behavioral traits (e.g., intelligence). These advancements offer improved diagnostic accuracy and a deeper understanding of brain function, paving the way for more personalized and effective treatments for neurological and psychiatric disorders.