Improved estimation of dynamic connectivity from resting-state fMRI data

Functional magnetic resonance imaging (fMRI) has been widely used for neuronal connectivity analysis. As a datadriven technique, independent component analysis (ICA) has become a valuable tool for fMRI studies. Recently, due to the dynamic nature of the human brain, time-varying connectivity analysis is regarded as an important measure to reveal essential information within the network. The sliding window approach has been commonly used to...