Linking graph features of anatomical architecture to regional brain activity: A multi-modal MRI study

Abstract

BackgroundPrevious empirical research has treated regional neural responses and network architecture separately. However, anecdotal reports have suggested a close relationship between the two. This study aims to investigate the influence of structural connectivity on regional spontaneous activities. MethodsDatasets of structural magnetic resonance imaging (sMRI), resting state functional MRI (rs-fMRI) and diffusion weighted imaging (DWI) of 36 right-handed healthy subjects (average age 27.4) were selected from the NKI Rockland sample. In the sMRI data, the cerebral cortex was parcellated into 70 regions of interest (ROIs) according to an anatomical atlas. Two indices were calculated from rs-fMRI for each ROI: the regional homogeneity (ReHo) and the amplitude of low frequency fluctuation (ALFF). Diffusion tensor imaging was computed from DWI and was converted to tractography. Four graph indices of structural connectivity were retrieved from the tractography results and the 70 ROIs, as follows: nodal degree, clustering coefficient, local efficiency and betweenness centrality. ResultsReHo values were significantly correlated with all 4 graph features, whereas ALFF values were significantly correlated with nodal degrees and clustering coefficients. Both ReHo and ALFF tended to increase with segregation (clustering coefficient and local efficiency) and decrease with centrality (nodal degree and betweenness centrality). DiscussionThough derived from local spontaneous activities, ReHo and ALFF may reflect the network properties of the underlying anatomical architecture. The results supported the hypothesis that the properties of the network structure may shape the regional neural response profiles.