Effect sizes and test-retest reliability of the fMRI-based Neurologic Pain Signature

Abstract

Identifying biomarkers that predict mental states with large effect sizes and high test-retest reliability is a growing priority for fMRI research. We examined a well-established multivariate brain measure that tracks pain induced by nociceptive input, the Neurologic Pain Signature (NPS). In N = 295 participants across eight studies, NPS responses showed a very large effect size in predicting within-person single-trial pain reports (d = 1.45) and medium effect size in predicting individual differences in pain reports (d = 0.49). The NPS showed excellent shortterm (within-day) test-retest reliability (ICC = 0.84, with average 69.5 trials/person). Reliability scaled with the number of trials within-person, with [≥]60 trials required for excellent test-retest reliability. Reliability was tested in two additional studies across 5-day (N = 29, ICC = 0.74, 30 trials/person) and 1-month (N = 40, ICC = 0.46, 5 trials/person) test-retest intervals. The combination of strong within-person correlations and only modest between-person correlations between the NPS and pain reports indicate that the two measures have different sources of between-person variance. The NPS is not a surrogate for individual differences in pain reports but can serve as a reliable measure of pain-related physiology and mechanistic target for interventions. Significance statementCurrent efforts towards translating brain biomarkers require identifying brain measures that can strongly and reliably predict outcomes of interest. We systematically examined the performance of a well-established brain activity pattern, the Neurological Pain Signature (NPS), in a large and diverse sample of participants. The NPS showed excellent reliability, and the reliability scaled with the number of trials within-person. The NPS responses showed strong correlations with pain reports at the within-person level but only modest correlations at the between-person level. The findings suggest that the NPS is not a surrogate for individual differences in pain reports but can serve as a reliable measure of a pain-related physiological target. Author NoteThis project was supported by grants R01MH076136 (T.D.W.), R01DA046064, R01EB026549, and R01DA035484. Elizabeth A. Reynolds Losin was supported by a Mentored Research Scientist Development award from National Institute On Drug Abuse of the National Institutes of Health (K01DA045735). Lauren Y. Atlas was supported in part by funding from the Intramural Research Program of the National Center for Complementary and Integrative Health. Yoni K. Ashar was supported by NCATS Grant # TL1-TR-002386. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Code for all analyses and figures is available at https://github.com/XiaochunHan/NPS_measurement_properties. Data for all analyses and figures is available at https://osf.io/v9px7/.