Improving fMRI-based prediction of individual pain ratings by accounting for interindividual variance

Abstract

AbstractWe challenge the pessimistic conclusion of a recently published paper by Hoeppli et al that fMRI-BOLD measures are useless in predicting interindividual differences in pain perception. By conducting a re-analysis of publicly available data of their study, we propose an alternative analysis approach that addresses the issue of interindividual variance differences in BOLD readouts, aiming to enhance the predictive power of fMRI-based measures. Instead of using absolute values of both, pain ratings and BOLD measures, we make use of robust intraindividual differences between the two experimental conditions in their study. Our findings demonstrate a statistically significant positive linear relationship between the neurologic pain signature (NPS) score, a multivariate pain classifier based on BOLD fMRI, and individual differences in perceived pain ratings. This relationship is driven by individuals that report pain sensitivity to both experimental conditions and can clearly distinguish between the two. Our results provide evidence for the potential of fMRI-BOLD measures in predicting interindividual differences in pain perception and allow for a more optimistic conclusion regarding the ongoing debate whether fMRI can be used as an objective measure for pain perception.ARISING FROMHoeppli, M.E., Nahman-Averbuch, H., Hinkle, W.A. et al. Dissociation between individual differences in self-reported pain intensity and underlying fMRI brain activation. Nat Commun 13, 3569 (2022).https://doi.org/10.1038/s41467-022-31039-3