Research Stories 게시판읽기 ( Discovering the ‘ Brain Fingerprints ’ of Chronic Pain )

Research Stories

Discovering the ‘Brain Fingerprints’ of Chronic Pain

- Personalized Pain Assessment Using Extensively Sampled Functional MRI Data

Biomedical Engineering
Prof. WOO, CHOONG-WAN

A research team led by Woo Choong-Wan, Associate Professor in the Department of Biomedical Engineering at Sungkyunkwan University and Associate Director of the Center for Neuroscience Imaging Research (CNIR) at the Institute for Basic Science (IBS), has successfully decoded the intensity of spontaneous pain using functional magnetic resonance imaging (fMRI) in collaboration with Professor Cho Sungkun’s team at Chungnam National University.

Chronic pain is one of the most common reasons for hospital visits worldwide, affecting approximately one in five adults. Despite its prevalence, there has been no objective method to measure pain intensity, unlike blood pressure or body temperature. A hallmark of chronic pain is that pain arises spontaneously without an external trigger. As a result, medical tests often appear normal, making an objective assessment extremely challenging. Consequently, treatment tends to focus on symptom relief rather than addressing underlying causes, potentially leading to long-term issues such as side effects and drug dependence.

In recent years, researchers have increasingly focused on the brain, which ultimately constructs the experience of pain. Structural and functional abnormalities in the brain may underlie chronic pain. However, most previous studies have sought neural correlates that are common across patients. Because pain is inherently subjective and varies from person to person, such approaches face fundamental limitations in accuracy and clinical utility. Recognizing the need to account for individual differences, the research team adopted a personalized approach tailored to each patient.

The team conducted repeated fMRI scans over several months in patients with fibromyalgia, a disorder characterized by widespread, persistent pain. fMRI detects changes in blood oxygen levels to reveal which brain regions are active. By applying machine learning techniques to this extensive brain imaging dataset, the researchers identified each patient’s unique functional brain connectome for pain—a map representing the complex interactions through which different brain regions communicate. These newly developed biomarkers successfully predicted fluctuations in each patient’s pain intensity over several months based solely on brain imaging data, achieving a high level of accuracy.

The most significant finding of the study is that pain-related brain response patterns differ across individuals. A pain connectome identified in one patient could not explain the pain experienced by another. This provides scientific evidence that chronic pain reflects highly individualized brain responses and underscores the necessity of personalized approaches that account for each patient’s unique characteristics.

“The fact that pain cannot be seen adds to the suffering of patients with chronic pain. This study empirically demonstrates that precision neuroimaging can be useful for evaluating invisible pain more objectively,” stated Dr. Choong-Wan WOO, who led the study.

“Hopefully, our findings will ultimately help facilitate the application of precision medicine approaches to pain assessment and treatment.” Jae-Joong LEE, a postdoctoral researcher at SKKU IBS and the first author of this study, emphasized, “The key finding of this study is that each patient has a unique brain connectivity pattern associated with pain,” adding, “We will continue our research so that neuroscience-based precision diagnostics can be actively implemented in clinical settings.”

※ Title: Personalized Brain Decoding of Spontaneous Pain in Individuals With Chronic Pain
※ Journal: Nature Neuroscience
※ DOI: https://www.nature.com/articles/s41593-026-02221-3

※ PURE: https://pure.skku.edu/en/persons/choong-wan-woo/

▲ Figure 1. Pain intensity predicted by fMRI-based chronic pain marker

The horizontal axis represents the actual pain intensity reported by each participant, and the vertical axis represents the pain intensity predicted by the brain imaging marker, demonstrating the correspondence between actual and predicted pain. Different colors indicate different temporal units of prediction.