| The present fMRI studies explore the connectivity among neural regions in the visual and motor systems using the analysis framework of Structural Equation Modeling (SEM). Confirming previous work, we demonstrate that SEM is an effective method to analyze the path directions and coefficients from the covariance structure in fMRI data. An important distinction of our approach, however, is that we have adapted SEM from its traditional role in confirmatory analysis to provide utility as an exploratory technique. Our current approaches include (I) determining the most statistically significant model based on a set of cortical areas and anatomic constraints, (II) detecting brain regions that fit well in a hypothesized neural network model, and (III) identifying the best connectivity model at each brain region. Our SEM methodology is demonstrated using a broad range of fMRI experiments, which explore bimanual motor coordination as well as perception of shape, motion, and color. |
