Brain morphology predicts individual sensitivity to pain: a multicenter machine learning approach.

ABSTRACT:

Abstract

Sensitivity to pain shows a remarkable interindividual variance that has been reported to both forecast and accompany various clinical pain conditions. Although pain thresholds have been reported to be associated to brain morphology, it is still unclear how well these findings replicate in independent data and whether they are powerful enough to provide reliable pain sensitivity predictions on the individual level. In this study, we constructed a predictive model of pain sensitivity (as measured with pain thresholds) using structural magnetic resonance imaging-based cortical thickness data from a multicentre data set (3 centres and 131 healthy participants). Cross-validated estimates revealed a statistically significant and clinically relevant predictive performance (Pears

SUBMITTER: Kotikalapudi R 

PROVIDER: S-EPMC10578427 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature