Altered salience network is related to functional dyspepsia: a structural and functional MRI data fusion study

Abstract

Multimodal data fusion analysis has been applied in brain imaging, which could be important for understanding pathogenesis of disorders and medical diagnosis. Based on patients with functional dyspepsia (FD), the aim of this study was to investigate structural and functional alterations within the salience network (SN) associated with regulating the default mode network (DMN) and central-executive network (CEN). Independent component analysis (ICA) was applied to identify these resting state networks (RSNs). Conditional Granger causality analysis (CGCA) was used to evaluate effective connectivity among the isolated RSNs and certain brain regions of interest (ROIs). Voxel-based morphometry (VBM) was then used to assess structure of gray matter in the SN. Our results showed that FD patients showed significantly increased brain activity in SN compared with healthy controls (HCs). The causal influences from the SN to DMN and CEN were weaker in patients. The anterior cingulate cortex (ACC) served as the causal outflow hub among the ROIs in FD patients. And FD patients had structural abnormality in the ACC and AI. Our findings suggest that the critical causal role of insula is disrupted in FD patients, and ACC could compensate insula dysfunction of regulating other brain regions. Our results also show that combing multimodal media data is potentially valuable to enrich our understanding of pathogenesis of FD.