Identification of functional cortico-subcortical networks in resting-state fMRI: A combined nedica and GLM analysis

While the cortical components of functional networks detected by spatial independent component analysis (sICA) in functional magnetic resonance imaging (fMRI) have been reproducibly described in various While the cortical components of functional networks detected by spatial independent component analysis (sICA) in functional magnetic resonance imaging (fMRI) have been reproducibly described in various studies, little is known about their subcortical components. In this study, we propose a method that extracts cortico-subcortical networks from fMRI data by first detecting cortical networks with sICA and then by complementing them with subcortical components using multiple regression, at both the individual and the group levels.studies, little is known about their subcortical components. In this study, we propose a method that extracts cortico-subcortical networks from fMRI data by first detecting cortical networks with sICA and then by complementing them with subcortical components using multiple regression, at both the individual and the group levels.