Individual variability in brain representations of pain

• Published in: Nature neuroscience 2022-06, Vol.25 (6), p.749-759
• Main Authors: Kohoutová, Lada, Atlas, Lauren Y., Büchel, Christian, Buhle, Jason T., Geuter, Stephan, Jepma, Marieke, Koban, Leonie, Krishnan, Anjali, Lee, Dong Hee, Lee, Sungwoo, Roy, Mathieu, Schafer, Scott M., Schmidt, Liane, Wager, Tor D., Woo, Choong-Wan
• Format: Article
• Language: English
• Subjects: 59/36; 631/378; 692/53; Animal Genetics and Genomics; Behavioral Sciences; Biological Techniques; Biomedical and Life Sciences; Biomedicine; Brain; Brain - diagnostic imaging; Brain Mapping; Cerebral Cortex; Cognitive science; Customization; Datasets; Functional magnetic resonance imaging; Humans; Magnetic Resonance Imaging; Neurobiology; Neuroscience; Neurosciences; Pain; Pain - diagnostic imaging; Prediction models; Representations; Variability
• ISSN: 1097-6256; 1546-1726; 1546-1726
• DOI: 10.1038/s41593-022-01081-x

Characterizing cerebral contributions to individual variability in pain processing is crucial for personalized pain medicine, but has yet to be done. In the present study, we address this problem by identifying brain regions with high versus low interindividual variability in their relationship with pain. We trained idiographic pain-predictive models with 13 single-trial functional MRI datasets ( n  = 404, discovery set) and quantified voxel-level importance for individualized pain prediction. With 21 regions identified as important pain predictors, we examined the interindividual variability of local pain-predictive weights in these regions. Higher-order transmodal regions, such as ventromedial and ventrolateral prefrontal cortices, showed larger individual variability, whereas unimodal regions, such as somatomotor cortices, showed more stable pain representations across individuals. We replicated this result in an independent dataset ( n  = 124). Overall, our study identifies cerebral sources of individual differences in pain processing, providing potential targets for personalized assessment and treatment of pain. Pain experience is highly individual, but its individual-specific brain features remain unclear. The authors identify brain regions with consistent versus variable representations of pain across a large sample of individuals.