A Corticospinal Signature for Interindividual Pain Sensitivity

Brisbane Convention & Exhibition Centre 

Chronic pain compromises quality of life (Kuehn, 2018), yet its subjective variability complicates both research and treatment (Kohoutová et al., 2022). Identifying neural markers of individual pain sensitivity is critical for understanding why some individuals develop chronic pain while others recover (Kehlet et la., 2006). Previous imaging studies, focusing on brain networks, reveal stable resting-state features that predict pain sensitivity (Spisak et al., 2020). However, clinical translation remains limited, and the spinal cord's crucial role is understudied. Integrated corticospinal fMRI now allows simultaneous exploration of brain and cervical spinal cord activity, potentially improving prediction models (Tinnermann et al., 2017). Our study presents a pioneering approach to understanding interindividual differences in pain sensitivity by developing a novel corticospinal pain sensitivity signature (CSps). The integration of corticospinal functional connectivity with machine learning offers a significant advancement over traditional brain-centric models. The study situates itself within the broader context of pain research by addressing gaps related to the spinal cord's contribution to pain sensitivity, promising to refine pain prediction frameworks and improve clinical interventions.