This study aimed to compare whole brain network between HZ patients and PHN patients, as well as to investigate the associations between whole brain network changes and pain intensity and the accuracy of classifying between different types of pain.

PHN patients (n = 50) and HZ patients (n = 50) and healthy controls (HCs) (n = 50) underwent resting-state functional magnetic resonance imaging (rs-fMRI). Functional connectivity and global and local graph theory metrics were calculated by using Dosenbach-160 atlas. The relationship between neuroimaging indicators and clinical scales was evaluated using correlation analysis, and receiver operating characteristic (ROC) curves evaluated the feasibility of classifying PHN and HZ patients using specific neuroimaging indicators.

1 10 greater average connectivities were found in HZ group among the default mode, frontoparietal, cingulo-opercular, sensorimotor, occipital networks, and cerebellum (p < 0.001).2 HZ patients exhibited higher global efficiency than those in the PHN and HCs (t = 2.178, p = 0.038).3 Multiple linear regression analyses indicated that functional connectivity between the ventral frontal cortex (vFC) in the cingulo-opercular network (CON) and the occipital gyrus in the occipital network (ON) influenced the VAS pain scores (β = 4.273; p = 0.004).

The variation of functional connectivity between vFC in the CON and occipital gyrus in the ON may be a robust neuroimaging marker of the transition from HZ to PHN patients.

Whole-brain network analysis may be effective in distinguishing HZ and PHN patients and predicting pain intensity.