Why the study?
Do baseline peak alpha frequency and corticomotor excitability predict pain severity in healthy individuals exposed to a sustained muscle pain model?
Do baseline peak alpha frequency and corticomotor excitability predict pain severity in healthy individuals exposed to a sustained muscle pain model?
Combined slow peak alpha frequency and corticomotor depression predict higher pain severity in a human model of sustained muscle pain, suggesting potential biomarkers for chronic pain susceptibility.
Exploratory EEG/TMS markers of pain susceptibility remain hypothesis-generating; leaves open clinical translation pending patient validation.
Mechanisms that predict an individual’s susceptibility to pain, before pain is present or in the first few days following pain onset, are unknown. We utilised a clinically-relevant human transitional pain model (intramuscular injections of nerve growth factor) to examine brain mechanisms that predict pain susceptibility. Resting state EEG and corticomotor excitability measured by TMS were evaluated longitudinally in healthy individuals as pain developed and resolved over 21 days. Whereas pre-pain central peak alpha frequency (PAF) correlated with peak pain occurring 4-6 days later, altered corticomotor excitability developed several days after pain onset and showed two distinct patterns (facilitation, depression). Individuals with combined slow PAF and corticomotor depression developed more severe pain. These data provide the first evidence of the temporal profile of key brain mechanisms as pain progressively develops. PAF and corticomotor excitability could represent biomarkers for susceptibility to high pain severity and subsequently, the development of chronic pain.
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Seminowicz et al. (2018) studied this question.
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