Before revision:  A common approach to modeling dynamic connectivity in resting-state whole-brain  fMRI is to compute (across moving temporal windows) the Pearson-correlation between anatomical regions derived from predefined brain parcellation. Due to image acquisition and physiological noise , the direct use of the sample correlation matrices is not reliable for the subsequent modeling of the dynamically-evolving connectivity matrices.
After revision:  A common approach to modeling dynamic connectivity in resting-state whole-brain fMRI is to compute (across moving temporal windows) the Pearson-correlation between anatomical regions via sliding time windows. However , the direct use of the sample correlation matrices is not reliable for the subsequent modeling of the dynamically-evolving connectivity matrices.