Research On Static And Dynamic Brain Networks In Schizophrenia Patients

Background:Schizophrenia is a common and severe mental disorder,but its pathogenesis remains unclear.Resting-state functional magnetic resonance imaging(rs-fMRI)-based brain network measures have been widely used to investigate the pathogenesis of schizophrenia.Among these measures,it is commonly assumed that the brain network remains unchanged during the rs-fMRI scanning.Recently,studies put forward the theory of “dynamic brain networks” that the brain network fluctuates over time.It was thought that such fluctuations can reflect important information which may be ignored by the traditional “static” analyzing methods of brain networks.In this study,the changes in static and dynamic brain networks of schizophrenia were analyzed simultaneously,in order to further explore the neuropathological mechanisms of schizophrenia.Methods:In this study,82 patients with schizophrenia and 76 age-and sex-matched healthy controls were recruited.Both groups underwent rs-fMRI scans.We calculated and compared the measurements of both static and dynamic brain networks at the level of the whole brain,nodes and edges.Meanwhile,the correlation analysis between the brain network measurements and the score of the Positive and Negative Syndrome Scale(PANSS)in schizophrenia patients was also processed.Results:When analyzing static brain network in patients with schizophrenia,the clustering coefficient and characteristic path length of schizophrenia were significantly reduced,while the global efficiency was significantly increased at the whole brain level.At the node level,patients of schizophrenia showed significantly decreasing nodal clustering coefficient and nodal efficiency in the somatomotor network and the dorsal attention network.From the perspective of edge,lower functional connectivity within the somatomotor network and functional connectivity between the somatomotor network and other subnetworks were detected in patients of schizophrenia.In the analysis of dynamic brain network,patients of schizophrenia demonstrated lower temporal characteristic path length significantly at the whole brain level.At the level of node,temporal clustering coefficient of schizophrenia was significantly decreased in the somatomotor network.Meanwhile,patients of schizophrenia demonstrated lower temporal characteristic path length of node in the frontoparietal network and the default mode network significantly.From the perspective of edge,the temporal variability was significantly increased within and between sub-networks widely.In addition,in the patients of schizophrenia,the score of PANSS negative syndrome scale was positively correlated with clustering coefficient,local efficiency,temporal characteristic path length and temporal clustering coefficient at the level of the whole brain.Discussion:Both static and dynamic brain networks in schizophrenia showed abnormal changes,suggesting the randomization of brain networks.Some brain regions,such as the regions related to the somatomotor network,showed similar functional changes in both static and dynamic brain networks.While some abnormal changes in frontoparietal network and default network only reflected in the dynamic brain network,which may indicate that the analysis of dynamic brain network is more sensitive than the static brain network.These findings may contribute to a further understanding of the neuropathological mechanisms of schizophrenia.