| Autor: |
Xiaochun Han, Yoni K. Ashar, Philip Kragel, Bogdan Petre, Victoria Schelkun, Lauren Y. Atlas, Luke J. Chang, Marieke Jepma, Leonie Koban, Elizabeth A. Reynolds Losin, Mathieu Roy, Choong-Wan Woo, Tor D. Wager |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
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| Zdroj: |
NeuroImage, Vol 247, Iss , Pp 118844- (2022) |
| Druh dokumentu: |
article |
| ISSN: |
1095-9572 |
| DOI: |
10.1016/j.neuroimage.2021.118844 |
| Popis: |
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 short-term (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. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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Full Text from ScienceDirect