Electroencephalography research in neuropathic pain (Review)

Abstract

Neuropathic pain (NP), arising from lesions or dysfunction of the somatosensory system, remains a major clinical challenge due to its subjective and multidimensional nature. Traditional pain assessments rely on self-report scales, which lack objectivity and reproducibility. Electroencephalography (EEG), with its high temporal resolution and accessibility, provides a promising avenue for identifying candidate neurophysiological biomarkers of pain. The current narrative review integrates mechanistic insights and electrophysiological evidence to delineate EEG alterations in NP. Resting-state θ increases and dominant-frequency slowing are relatively recurrent in chronic NP, whereas α-, β- and γ-band findings remain heterogeneous. Network analyses further reveal aberrant prefrontal-limbic and sensorimotor connectivity, as well as altered cross-frequency coupling, but the direction and topology of these findings remain dependent on the patient population, recording configuration and analytical metric. Advances in computational EEG analysis, graph theory and machine learning are facilitating exploration of objective, individualized pain assessment frameworks. Emerging portable EEG and multimodal approaches may provide opportunities for future clinical translation. Overall, EEG offers a feasible and dynamic method to bridge subjective pain perception with measurable neurophysiological signatures, paving the way toward precision diagnostics and neuromodulation in NP.