Pain-free resting-state functional brain connectivity predicts individual pain sensitivity
Tamás SpisákiD, Bálint KincsesiD, Frederik SchlittiD, Matthias ZunhammeriD, Tobias Schmidt‐WilckeiD, Zsigmond Tamás KincsesiD, Ulrike BingeliD
Abstract
Individual differences in pain perception are of key interest in basic and clinical research as altered pain sensitivity is both a characteristic and a risk factor for many pain conditions. It is, however, unclear how individual susceptibility to pain is reflected in the pain-free resting-state brain activity and functional connectivity.\n\nHere, we identified and validated a network pattern in the pain-free resting-state functional brain connectome that is predictive of interindividual differences in pain sensitivity. Our predictive network signature (https://spisakt.github.io/RPN-signature) allows assessing the individual susceptibility to pain without applying any painful stimulation, as might be valuable in patients where reliable behavioural pain reports cannot be obtained. Additionally, as a direct, non-invasive readout of the supraspinal neural contribution to pain sensitivity, it may have broad implications for translational research and the development and assessment of analgesic treatment strategies.
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