Chronic pain and oscillatory neuroplasticity: Review on impaired compensatory network responses in resting-state electroencephalography.

Chronic pain is a multidimensional condition that involves persistent alterations in sensory, cognitive, and affective processes. Owing to its high temporal resolution and capacity to measure large-scale neural communications, electroencephalography (EEG) has emerged as a promising tool for identifying objective biomarkers of chronic pain. However, the findings of existing studies remain heterogeneous, which limits their clinical translation. In this narrative review, we synthesized recent resting-state EEG functional connectivity studies across a range of chronic pain conditions, highlighting the consistent frequency-specific abnormalities in the theta, alpha, beta, and gamma bands. Across studies, theta connectivity consistently increased prominently within sensory-limbic pathways, but decreased in cognitive-control networks, suggesting a maladaptive reallocation of learning-related neural resources. Alpha neurons showed reduced inhibitory maintenance in regulatory regions and excessive stabilization of neuropathic gating circuits. Beta oscillations demonstrated both overstabilization of affective-salience networks and weakened maintenance of top-down control, consistent with its role as a "status quo" rhythm. Gamma findings reflect disrupted high-frequency plasticity, ranging from excessive sensory precision to global microcircuit fragmentation. To integrate these findings, we propose a theoretical oscillatory neuroplasticity framework that may help to organize current observations across populations with chronic pain. Within this framework, frequency-specific alterations observed across studies can be interpreted as reflecting an imbalance across the learning (theta), maintenance (alpha), stabilization (beta), and fast plasticity (gamma) systems. This review further outlines methodological recommendations for enhancing reproducibility, improving cross-study comparability, and supporting the development of mechanistically informed EEG biomarkers of chronic pain.