Comparative analysis of rs-fMRI markers in heat and mechanical pain sensitivity

This study investigates the comparative analysis of resting-state functional magnetic imaging (rs-fMRI) markers in heat and mechanical pain sensitivity among healthy adults. Using quantitative sensory testing (QST) in the orofacial area and rs-fMRI, we explored the relationship between pain sensitivities and resting-state functional connectivity (rsFC) across whole brain areas. Brain regions were spatially divided using group independent component analysis (gICA), and additional masked gICA was performed for brainstem regions. Our findings revealed that a significant number of rsFCs were correlated with either heat or mechanical pain sensitivity, with a substantial portion originating from the Sensorimotor Network (SMN). Furthermore, multivariable regression models incorporating rsFC features demonstrated predictive capabilities for pain sensitivities, with the inclusion of brainstem gICA components significantly enhancing model accuracy. Finally, a composite critical rsFC value was introduced to simplify and describe overall abnormal communication in the brain network, which could also be used in univariable regression models to predict heat and mechanical pain sensitivity.