Pain-free resting-state functional brain connectivity predicts individual pain sensitivity

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. Here, 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.