Description

Chronic pain is a major health burden associated with immense economic and social costs. Predictive biomarkers that can identify individuals at risk of developing severe and persistent pain, which is associated with worse disability and greater reliance on opioids, would promote aggressive, early intervention that could halt the transition to chronic pain. The investigative team has uncovered evidence of a unique cortical biomarker signature that predicts pain susceptibility (severity and duration). The biomarker signature combines resting state sensorimotor peak alpha frequency (PAF) measured using electroencephalograph (EEG) and corticomotor excitability (CME) measured using transcranial magnetic stimulation (TMS). This PAF/CME biomarker signature could be capable of predicting the severity of pain experienced by an individual minutes to months in the future, as well as the duration of pain (time to recovery). In the current study, the investigators aim to undertake analytical validation of this biomarker in healthy participants using a standardized model of the transition to sustained myofascial temporomandibular pain (masseter intramuscular injection of nerve growth factor). The investigators will record PAF/CME at multiple time points before and during the development of pain and use online diaries and in-laboratory assessments of pain, sleep, stress, and other psychosocial variables. Specifically, the investigators will test if the biomarker signature predicts an individual's pain sensitivity (high- or low-pain sensitive).