Abstract
The purpose of this study was to explore the resting-state functional connectivity (FC) changes among the pain matrix and other brain regions in herpes zoster (HZ) and postherpetic neuralgia (PHN) patients. Fifty-four PHN patients, 52 HZ patients, and 54 healthy controls (HCs) underwent resting-state functional magnetic resonance imaging (rs-fMRI) scans. We used a seed-based FC approach to investigate whether HZ and PHN patients exhibited abnormal FC between the pain matrix and other brain regions compared to HCs. A random forest (RF) model was constructed to explore the feasibility of potential neuroimaging indicators to distinguish the two groups of patients. We found that PHN patients exhibited decreased FCs between the pain matrix and the putamen, superior temporal gyrus, middle frontal gyrus, middle cingulate gyrus, amygdala, precuneus, and supplementary motor area compared with HCs. Similar results were observed in HZ patients. The disease durations of PHN patients were negatively correlated with those aforementioned impaired FCs. The results of machine learning experiments showed that the RF model combined with FC features achieved a classification accuracy of 75%. Disrupted FC among the pain matrix and other regions in HZ and PHN patients may affect multiple dimensions of pain processing.
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