Researchers have recorded pain-related data from inside the brain of individuals with chronic pain disorders caused by stroke or amputation (phantom limb pain). A long sought-after goal has been to understand how pain is represented by brain activity and how to modulate that activity to relieve suffering from chronic pain. Data were collected over months while patients were at home, and they were analyzed using machine learning tools. Doing so, the researchers identified an area of the brain associated with chronic pain and objective biomarkers of chronic pain in individual patients.
These findings, which represent a first step towards developing novel methods for tracking and treating chronic pain, were published in Nature Neuroscience and funded by the National Institutes of Health’s Brain Research Through Advancing Innovative Neurotechnologies (BRAIN) Initiative and the Helping to End Addiction Long-term Initiative, or NIH HEAL Initiative.
Four participants, three with post-stroke pain and one with phantom limb pain, were surgically implanted with electrodes targeting their ACC and OFC. Several times a day, each participant was asked to answer questions related to how they would rate the pain they were experiencing, including strength, type of pain, and how their level of pain was making them feel emotionally. They would then initiate a brain recording by clicking a remote-control device, which provided a snapshot of the activity in the ACC and OFC at that exact moment. Using machine learning analyses, the research team was able to use activity in the OFC to predict the participants’ chronic pain state.
