Effects of Alterations in Resting-State Neural Networks on the Severity of Neuropathic Pain after Spinal Cord Injury

Neuropathic pain (NP) following spinal cord injury (SCI) is refractory to pain control strategies, and the underlying neuronal mechanisms remain poorly understood. This study aimed to determine the brain regions engaged in maintaining a spontaneous resting state and the link between those regions and the severity of NP in patients with incomplete SCI. Seventy-three subjects (41 patients and 32 age- and sex-matched healthy controls) participated in this retrospective study. Regarding the neurological level of injury, patients with incomplete SCI experienced at-level or below-level NP. The severity of NP was evaluated using a visual analog scale (VAS), and patients were divided into mild and moderate–severe NP groups based on VAS scores. Graph theory and fractional amplitude of low-frequency fluctuation (fALFF) analyses were performed to compare resting-state functional magnetic resonance imaging (fMRI) analysis results among the three groups. Graph theory analysis was performed through a region of interest (ROI)-to-ROI analysis and then fALFF analysis was performed in the brain regions demonstrating significant differences among the three groups analyzed using the graph theory. We evaluated whether the brain regions showing significant differences using graph theory and fALFF correlated with the VAS scores. Patients with moderate–severe NP showed reduced node degree and fALFF in the left middle frontal gyrus compared with those with mild NP and healthy controls. Furthermore, patients with severe NP demonstrated increased average path lengths and reduced fALFF values in the posterior cingulate gyrus. This study found that changes in intrinsic oscillations of fMRI signals in the middle frontal gyrus and posterior cingulate gyrus were significant considering the severity of NP.