  This paper describes an approach of using dynamic Structural Equation
Modeling (SEM) analysis to estimate the connectivity networks from
resting-state fMRI data measured by a multiband EPI sequence. Two structural
equation models were estimated at each voxel with respect to the sensory-motor
network and default-mode network. The resulting connectivity maps indicate that
supplementary motor area has significant connections to left/right primary
motor areas, and medial prefrontal cortex link significantly with posterior
cingulate cortex and inferior parietal lobules. The results imply that high
temporal resolution images obtained with multiband fMRI data can provide
dynamic and directional information on the neural connectivity.
