Journal
NATURE COMMUNICATIONS
Volume 8, Issue -, Pages -Publisher
NATURE PUBLISHING GROUP
DOI: 10.1038/ncomms14211
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Funding
- NIH [R01DA035484, R01MH076136]
- Intramural Research program of the NIH's National Center for Complementary and Integrative Health
- VENI grant of the Netherlands Organization for Scientific Research
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Cerebral processes contribute to pain beyond the level of nociceptive input and mediate psychological and behavioural influences. However, cerebral contributions beyond nociception are not yet well characterized, leading to a predominant focus on nociception when studying pain and developing interventions. Here we use functional magnetic resonance imaging combined with machine learning to develop a multivariate pattern signature-termed the stimulus intensity independent pain signature-1 (SIIPS1)-that predicts pain above and beyond nociceptive input in four training data sets (Studies 1-4, N = 137). The SIIPS1 includes patterns of activity in nucleus accumbens, lateral prefrontal and parahippocampal cortices, and other regions. In cross-validated analyses of Studies 1-4 and in two independent test data sets (Studies 5-6, N = 46), SIIPS1 responses explain variation in trial-by-trial pain ratings not captured by a previous fMRI-based marker for nociceptive pain. In addition, SIIPS1 responses mediate the pain-modulating effects of three psychological manipulations of expectations and perceived control. The SIIPS1 provides an extensible characterization of cerebral contributions to pain and specific brain targets for interventions.
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