Specific Electroencephalographic Signatures for Pain and Descending Pain Inhibitory System in Spinal Cord Injury

Marcel Simis, Kevin Pacheco-Barrios, Elif Uygur-Kucukseymen, Luis Castelo-Branco, Linamara R. Battistella, Felipe Fregni*

*Autor correspondiente de este trabajo

Producción científica: Contribución a una revistaArtículorevisión exhaustiva

14 Citas (Scopus)


Objectives: The pain related to spinal cord injury (SCI) is difficult to treat, and it is associated with significant morbidity. One aspect to improve therapeutics is to explore markers of pain and its correlates in SCI. Methods: In this cross-sectional neurophysiological analysis of a randomized, double-blind controlled trial, 39 patients with SCI were included. We analyzed conditioned pain modulation (CPM) efficiency as the index of the descending pain inhibitory system, EEG variables, and clinical pain levels as measured by the Visual Analogue Scale. Regression analyses were performed to assess the relationship among EEG variables, pain levels, and CPM. Results: We included 39 SCI patients, 74% reported SCI-related pain. We found that (1) less alpha and beta power are related to pain presence, (2) less alpha and beta power are associated with higher pain levels among patients with pain, (3) patients with pain have decreased peak alpha-theta frequency compared to no-pain group, (4) more relative theta power are related to the presence of low CPM efficiency, (5) higher relative theta power is associated with lower CPM efficiency. Conclusions: Our results confirm and provide additional data on the relationship between decreased alpha and beta frequencies and higher pain levels. One important finding, though, was a specific and different EEG signature for the descending inhibitory pain system, as we showed that increased theta EEG power is related to decreased CPM efficiency; suggesting that, although low CPM efficiency plays a major role in pain in these participants, it does seem to be associated with a specific oscillatory brain rhythm different from clinical pain. These findings have significant implications for future research on EEG-based biomarkers of pain in post-SCI and new interventions as neurofeedback to manage pain in this population.

Idioma originalInglés
Páginas (desde-hasta)955-964
Número de páginas10
PublicaciónPain Medicine
EstadoPublicada - 1 may. 2022


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