Functional Connectivity
Overview
Functional connectivity studies how activity in different brain regions covaries, helping researchers characterize brain organization and its links to cognition, behavior, and disorders. Common approaches derive connectivity from fMRI or EEG using correlations or synchrony, then analyze static or time-varying networks with graph, higher-order, and geometric methods. Deep learning and multimodal models combine these networks with structural imaging, while self-supervised and foundation models aim to learn representations that transfer across tasks and datasets. A key challenge is ensuring that strong predictions generalize across sites, parcellations, and scan conditions and that identified connections are reproducible and biologically interpretable.
Latest papers
60 papers13 papers in the last four weeks, up 117% on the four weeks before. 0.1% of all new papers.