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Musculoskeletal pain is an aversive experience that exists within a variety of conditions and can result in significant impairment for individuals. Gaining greater understanding of the factors related to pain vulnerability and resilience to musculoskeletal pain may help target at-risk individuals for early intervention. This analysis builds on our previous work identifying regions where lower gray matter density (GMD) was associated with individuals who report pain following standardized, exercise induced musculoskeletal injury. Here we sought to examine the relationship between baseline resting state functional connectivity (rsFC) in a priori regions and networks, and delayed onset muscle soreness (DOMS) pain intensity following a single session of eccentric exercise. The present study is a secondary analysis from a portion of a larger, blinded, randomized experimental trial. All participants were healthy adults between the ages of 18 and 40 years recruited from the university and surrounding community. The primary outcome measure was functional connectivity assessed by using T2 rest image. Participants completed a baseline functional MRI scan and a high intensity trunk exercise protocol to induce DOMS in the erector spinae. Pain intensity ratings were collected 48-hours later. rsFC from four seed regions and three networks were separately regressed on pain intensity scores. Our results revealed that connectivity between left middle frontal gyrus, the left occipital gyrus and cerebellar network seeds and clusters associated with discriminative, emotional, and cognitive aspects of pain were associated with lower post-DOMS pain. Our results provide key support for the role of structural and functional coherence in regional and network connectivity in adaptive pain response and represent an important step in clarifying neural mechanisms of resilience to clinically relevant pain. Resilience to clinically relevant pain is associated with aspects of regional and network neural coherence. Investigations of pain modulatory capacity that integrate multimodal neuroimaging metrics are called for. R01AT006334, PI Dr. Mark Bishop.
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