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This study aims to investigate the multivariate relationship between different sociodemographic, clinical, and neurophysiological variables with resting-state, high-definition, EEG spectral power in subjects with chronic knee osteoarthritis (OA) pain. This was a cross-sectional study. Sociodemographic and clinical data were collected from 66 knee OA subjects. To identify associated factors, we performed independent univariate and multivariate regression models by frequency bands (delta, theta, alpha, beta, low-beta, and high-beta) and by pre-defined regions (frontal, central, and parietal). From adjusted multivariate models, we found that: (1) increased frontocentral high-beta power and reduced central theta activity are positively correlated with pain intensity (β = 0.012, 95% CI 0.004–0.020; and β = − 0.008; 95% CI 0.014 to − 0.003; respectively); (2) delta and alpha oscillations have a direct relationship with higher cortical inhibition; (3) diffuse increased power at low frequencies (delta and theta) are associated with poor cognition, aging, and depressive symptoms; and (4) higher alpha and beta power over sensorimotor areas seem to be a maladaptive compensatory mechanism to poor motor function and severe joint degeneration. Subjects with higher pain intensity and higher OA severity (likely subjects with maladaptive compensatory mechanisms to severe OA) have higher frontocentral beta power and lower theta activity. On the other hand, subjects with less OA severity and less pain have higher theta oscillations power. These associations showed the potential role of brain oscillations as a marker of pain intensity and clinical phenotypes in chronic knee OA patients. Besides, they suggest a potential compensatory mechanism of these two brain oscillators according to OA severity.

EEG theta and beta bands as brain oscillations for different knee osteoarthritis phenotypes according to disease severity