Researchers led by Dr. KONG Yazhuo from the Institute of Psychology have developed a new neuroimaging model that integrates corticospinal activity to predict human pain perception. Combining corticospinal functional magnetic resonance imaging (fMRI) with machine learning, the model outperformed conventional brain-only approaches and showed promise for assessing both experimental and chronic pain.

The study was published in Cell Reports Medicineon June 18.

Pain is not generated by the brain alone. Nociceptive signals are first processed in the spinal cord and then transmitted to the brain, where sensory, emotional, and cognitive factors jointly shape pain experience. However, most existing pain biomarkers are brain-centered, partly because simultaneous imaging of the brain and spinal cord remains technically challenging.

In this study, the researchers developed the Corticospinal Pain Intensity Pattern (CsPIP), a model trained on thermal pain data from healthy participants and tested across independent datasets involving heat pain, itch, electrical pain, pain empathy, neuromodulation-induced analgesia, and chronic pain in patients with irritable bowel syndrome.

They found that CsPIP accurately predicted subjective pain intensity and outperformed models based solely on the brain or spinal cord. The model also generalized from heat pain to electrical pain, suggesting that it captured shared neural representations of physical pain across different types of nociceptive stimulation.

Importantly, CsPIP did not predict itch intensity or empathy ratings when participants observed others receiving painful stimulation, indicating its relative specificity to first-hand physical pain.

"Our findings suggest that pain perception is better captured by integrated corticospinal activity than by brain activity alone," said Dr. KONG, corresponding author of the study.

The model also tracked pain relief induced by active transcutaneous electrical nerve stimulation in healthy participants. In patients with irritable bowel syndrome, resting-state CsPIP expression predicted baseline chronic pain severity in patients with the low-burden subtype and tracked pain relief after electroacupuncture treatment.

These findings underscore the importance of considering the spinal cord alongside the brain in pain research. The study provides a corticospinal biomarker that may help bridge the gap between experimental and clinical pain assessment and support the evaluation of personalized treatments.

This study was supported by the National Key R&D Program of China, the National Natural Science Foundation of China, and the Beijing Natural Science Foundation, etc.