Chronic Pain Experience Recorded in Patients’ Brains

Scientists from the University of California San Francisco (UCSF) have, for the first time, recorded pain-related data from the brains of patients with chronic pain conditions. The research, published in Nature Neuroscience, was funded by the National Institutes of Health (NIH)’s Brain Research Through Advancing Innovative Neurotechnologies (BRAIN) Initiative and the Helping to End Addiction Long-term Initiative, or NIH HEAL Initiative.

What does pain look like in the brain?

The experience of pain, though often unpleasant, is one of the human body’s most important communication systems. It can alert us to dangerous stimuli, such as the heat emitted from a hot stove, which triggers a behavioral reaction, e.g., moving your hand away from the stove to avoid a burn.

Understanding the biological processes that underpin pain is a complex, as it is highly subjective; my experience of pain might differ wildly from the next person’s. “When you think about it, pain is one of the most fundamental experiences an organism can have,” says Dr. Prasad Shirvalkar, associate professor of anesthesia and neurological surgery at UCSF. “Despite this, there is still so much we don’t understand about how pain works.”

Typically, pain-related research relies on self-report data submitted by patients through questionnaires. Shirvalkar is the lead author of a new study that adopted a different approach. The team surgically implanted electrodes into the brains of four participants, three of whom were experiencing post-stroke pain and one that had phantom limb pain, to understand the brain signals that correlate with different levels of pain. Specifically, the researchers focused on brain activity in two regions: the anterior cingulate cortex (ACC) and the orbitofrontal cortex (OFC).

“Functional MRI studies show that the ACC and OFC regions of the brain light up during acute pain experiments. We were interested to see whether these regions also played a role in how the brain processes chronic pain,” says Shirvalkar. “We were most interested in questions like how pain changes over time, and what brain signals might correspond to or predict high levels of chronic pain?”

Towards objective biomarkers of chronic pain in individual patients

To accompany the electrical recordings, the researchers asked the four participants questions about how they rated their experiences of pain; for example, could they describe the type of pain they felt? How strong was the pain? How did the pain make them feel on an emotional level?

Brain recordings were then taken immediately after, providing a real-time recording of ACC and OFC activity. Applying machine learning – a sophisticated AI tool – Shirvalkar and colleagues could use the brain activity to predict the chronic pain state of the participants.

Next, the researchers analyzed how these same brain regions responded to acute pain by applying heat to different parts of the participant’s bodies. In half of the patients, the brain activity could be used to predict the pain responses. However, in this study, the ACC appeared to be most involved in the pain experience. The team suggest these findings might mean that the brain processes different types of pain in different ways, but more data using a larger cohort would be required to confirm this.

Findings could lead to effective, non-addictive pain treatments

While the small sample number used in the study must be considered, Shirvalkar and team are confident that their work represents an initial step towards “brain biomarkers” of pain, which could be utilized to inform the use of deep brain stimulation (DBS)-based treatment. While such biomarkers have emerged for conditions such as Parkinson’s disease and major depressive disorder, they are lacking for chronic pain.

“This is a great example of how tools for measuring brain activity originating from the BRAIN Initiative have been applied to the significant public health problem of relieving persistent, severe chronic pain,” says Walter Koroshetz, M.D., director of the National Institute of Neurological Disorders and Stroke. “We are hopeful that building from these preliminary findings could lead to effective, non-addictive pain treatments.”

Reference: Shirvalkar P, Prosky J, Chin G, et al. Prediction of chronic pain state using intracranial neural biomarkers. Nat Neuro. May 22, 2023. doi: 10.1038/s41593-023-01338-z

This article is a rework of a press release issued by the NIH/ the National Institute of Neurological Disorders and Stroke. Material has been edited for length and content.