Functional network-based statistics reveal abnormal resting-state functional connectivity in minimal hepatic encephalopathy

Whole-brain functional network analysis is an emerging methodology for the investigation of the pathophysiology of MHE. A nonparametric statistical approach, called “network-based statistics” (NBS), has also been used in the field of connectome analysis. However, few whole-brain NBS studies have been conducted on MHE patients, which limits the further clarification of the network pathophysiology of MHE. We performed NBS analysis to identify FC changes related to MHE at the whole-brain functional connectome level and indentified two subnetworks with significant differences in FC matrices between patients and controls. Correlation analyses revealed that the PHES score was significantly positively correlated with the strength of two FCs within the first subnetwork. In summary, our findings indicate that DMN dysfunction may be one of the core issues in the pathophysiology of MHE.