Predicting Individual Pain Thresholds From Morphological Connectivity Using Structural MRI: A Multivariate Analysis Study

Abstract

Pain sensitivity is highly variable among individuals, and it is clinically important to predict an individual’s pain sensitivity for individualized diagnosis and management of pain. Literature has shown that pain sensitivity is associated with regional structural features of the brain, but it remains unclear whether pain sensitivity is also related to structural brain connectivity. In the present study, we investigated the relationship between pain thresholds and morphological connectivity (MC) inferred from structural MRI based on data of 221 healthy participants. We found that MC was highly predictive of an individual’s pain thresholds and, importantly, it had a better prediction performance than regional structural features. We also identified a number of most predictive MC features and confirmed the crucial role of the prefrontal cortex in the determination of pain sensitivity. These results suggest the potential of using structural MRI-based MC to predict an individual’s pain sensitivity in clinical settings, and hence this study has important implications for diagnosis and treatment of pain.

Gan Huang

My research interests include Neural Modulation, Brain Computer Interface and Neural Prosthetics.