Chronic neuropathic pain (CNP) remains a significant clinical challenge, with complex neurophysiological underpinnings that are not fully understood. Identifying specific neural oscillatory patterns related to pain perception and interference can enhance our understanding and management of CNP. The present study aimed to analyze resting electroencephalography data from individuals with CNP to explore potential neural signatures associated with pain intensity, pain interference, and specific characteristics of neuropathic pain. This was achieved through a secondary analysis of electroencephalography data and Brief Pain Inventory responses from 36 patients with CNP, originally collected in a previous cross-sectional study. For statistical analysis, we modeled a linear or logistic regression by dependent variable for each model. As independent variables, we used electroencephalography data with such brain oscillations: as delta, theta, alpha, and beta, as well as the oscillations low alpha, high alpha, low beta, and high beta, for the central, frontal, and parietal regions. All models were tested for confounding factors, such as age and medication. There were no significant models for pain interference in general activity, walking, work, relationships, sleep, and enjoyment of life. However, the model for pain intensity during the past 4 weeks showed decreased alpha oscillations, and increased delta and theta oscillations were associated with decreased levels of pain, especially in the central area. In terms of pain interference in mood, the model showed high oscillatory alpha signals in the frontal and central regions correlated with mood impairment due to pain. Our models confirm recent findings proposing that lower oscillatory frequencies, likely related to subcortical pain sources, may be associated with brain compensatory mechanisms and thus may be associated with decreased pain levels. On the other hand, higher frequencies, including alpha oscillations, may disrupt top-down compensatory mechanisms.
