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

Tamas Spisak (), Balint Kincses, Frederik Schlitt, Matthias Zunhammer, Tobias Schmidt-Wilcke, Zsigmond T. Kincses and Ulrike Bingel
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Tamas Spisak: University Hospital Essen
Balint Kincses: University of Szeged
Frederik Schlitt: University Hospital Essen
Matthias Zunhammer: University Hospital Essen
Tobias Schmidt-Wilcke: University of Düsseldorf
Zsigmond T. Kincses: University of Szeged
Ulrike Bingel: University Hospital Essen

Nature Communications, 2020, vol. 11, issue 1, 1-12

Abstract: Abstract Individual differences in pain perception are of 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 sensitivity to pain is reflected in the pain-free resting-state brain activity and functional connectivity. Here, we identify and validate 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 allows assessing the individual sensitivity 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 implications for translational research and the development and assessment of analgesic treatment strategies.

Date: 2020
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DOI: 10.1038/s41467-019-13785-z

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