NIH-funded study shows preliminary results that could lead to new pain treatments. In a pioneering study, scientists have used machine learning tools to record and analyze brain data from chronic pain patients, identifying a specific brain region and biomarkers linked to chronic pain. The researc
, represent a first step towards developing novel methods for tracking and treating chronic pain.
Chronic pain is one of the largest contributors to disability worldwide. Neuropathic pain is caused by damage to the nervous system itself. It most commonly occurs due to injury to the nerves in our bodies, but for the individuals in this study, their pain is 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.
Traditionally, researchers gather data about chronic pain through self-reports from those living with the condition. Examples of this type of data include questionnaires about pain intensity and emotional impact of pain. This study however, also looked directly at changes in brain activity in two regions where pain responses are thought to occur—the anterior cingulate cortex and the orbitofrontal cortex —as participants reported their current levels of chronic pain.
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.
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