Scientists decode brain signals for pain, sparking hope for chronic pain treatments

Researchers have decoded brain signals for pain for the first time
Researchers have decoded brain signals for pain for the first time Copyright Canva
Copyright Canva
By Luke Hurst
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Researchers have identified an area of the brain associated with chronic pain, raising hopes for new treatments.


Researchers have recorded brain signals for pain for the first time, using a machine learning technique that could lead to treatments for the condition.

They recorded pain-related data from inside the brains of individuals who have chronic pain disorders caused by stroke or amputation.

Scientists have long sought to understand how pain is represented by brain activity. With electrodes implanted in the heads of the patients, the researchers could record neural activity over the course of months. Then with machine learning they could predict the pain severity scores from neural activity.

The researchers said the findings, published in Nature Neuroscience, could provide a way forward for developing treatments for chronic pain, which is one of the largest contributors to disability worldwide.

The research was funded by two initiatives - the National Institutes of Health’s (NIH) Brain Research Through Advancing Innovative Neurotechnologies (BRAIN) and the Helping to End Addiction Long-term Initiative.

“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,” Walter Koroshetz, director of the National Institute of Neurological Disorders and Stroke, said in a statement.

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

‘Hope for people living with chronic pain’

Researchers have typically gathered data about chronic pain through patients self-reporting using questionnaires about the intensity and emotional impact of pain.

This study looked directly at changes in brain activity in two brain regions - the anterior cingulate cortex (ACC) and the orbitofrontal cortex (OFC) - where pain responses are thought to occur, while patients self-reported their levels of pain.

Three of the participants had post-stroke pain and one had phantom limb pain, and they all had neuropathic pain.

Neuropathic pain most commonly occurs after injury to the nerves in our bodies, but for the individuals in this study, their pain was thought to originate from the brain itself. This kind of pain does not respond well to current treatments and can be debilitating for people living with it.

They were surgically implanted with electrodes targeting their ACC and OFC. A number of times each day the participants answered questions about their pain, and initiated a brain recording which provided a snapshot of the activity in the two brain areas. Machine learning analysis was then used to predict the participants’ chronic pain state.

There is still so much we don’t understand about how pain works
Prasad Shirvalkar
Associate professor of anaesthesia and neurological surgery at the University of California

“When you think about it, pain is one of the most fundamental experiences an organism can have,” said Prasad Shirvalkar, associate professor of anaesthesia and neurological surgery at the University of California, San Francisco, and lead author of this study.

“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.”

This study represents an initial step towards uncovering the patterns of brain activity that cause our perception of pain. The researchers believe identifying this pain signature will enable the development of new therapies that can alter brain activity to relieve suffering due to chronic pain.

Further studies involving more participants will be needed to determine whether different pain conditions share the same activity recorded in this study, or how they differ among people with different conditions.

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