Scientists identify brain signatures for chronic pain for the first time

Researchers have taken the first steps towards developing new methods for tracking and treating chronic pain, according to a new study in Nature Neuroscience.

For the first time, scientists have identified an area of the brain associated with chronic pain and detected objective markers of chronic pain in individual patients.

By understanding how pain is represented by brain activity, they hope to be able to modify that activity to relieve suffering.

“This is a great example of how tools for measuring brain activity 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 in the US.

“We are hopeful that building from these preliminary findings could lead to effective, non-addictive pain treatments.”

Four patients with chronic neuropathic pain disorders – caused by damage to the nervous system –were surgically implanted with electrodes that measured their brain activity over the course of three to six months.

The study looked at changes in activity in two regions of the brain where pain responses are thought to occur – the anterior cingulate cortex (ACC) and the orbitofrontal cortex (OFC) – as participants reported their current levels of chronic pain.

“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 Prasad Shirvalkar, associate professor of Anaesthesia and Neurological Surgery at the University of California San Francisco, and lead author of the study.

“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?”

Several times a day participants answered questions related to the strength, type of pain, and how their level of pain was making them feel emotionally, and then turned on the implanted device which measured electrical pulses in the brain.

Using machine learning the team was able to use activity in the OFC to predict the participants’ chronic pain severity.

They found that low-frequency signals in the OFC were active when all four participants were experiencing high levels of pain, but the exact combination of frequencies were unique to each participant.

“When you think about it, pain is one of the most fundamental experiences an organism can have,” says Shirvalkar.

“Despite this, there is still so much we don’t understand about how pain works. By developing better tools to study and potentially affect pain responses in the brain, we hope to provide options to people living with chronic pain conditions.”