Scientists can now measure the intensity of chronic pain using your brain signals

Pain is one of the most important and fundamental subjective experiences a person can have. While there is a lot of evidence that the perception of pain occurs in the brain, there is also a large knowledge gap about where and how pain signals are processed in the brain. Although pain is universal, there is no way to measure its intensity.

Most of the previous studies on the brain signals responsible for pain were reliable laboratory experiments in an artificial environment. To date, most research on chronic pain has used indirect measures of brain activity such as functional magnetic resonance imaging or electroencephalography. Furthermore, although doctors widely recognize that chronic pain is not simply an extension of acute pain – like stubbing your toe – it remains unknown how these Brain circuits behind acute and chronic pain are related to each other.

Our study is part of a larger clinical trials which aims to develop a new brain stimulation therapy to treat severe chronic pain. My team surgically implanted electrodes in the brain of four patients with post-stroke pain and phantom limb pain to record their neural signals orbitofrontal cortexa part of the brain involved in planning and anticipation, and cingulate cortexa place associated with emotion.

We asked patients about their level of pain severity several times a day for up to six months. We developed machine learning models to try to match and predict each patient’s self-reported pain intensity scores with snapshots of their brain activity signals. These brain signals consist of electrical waves that can decay into different frequencies, similar to how a musical chords can be broken into individual sounds of different pitches. From these models, we see that low frequency in the orbitofrontal cortex corresponds to each of the subjective pain intensities of the patients, which provides an objective measure of chronic pain. The greater the shift in low-frequency activity we measure, the more likely the patient is experiencing severe pain.

Next, we want to compare the relationship between chronic pain and acute pain. We investigated how the brain responds to brief, intense pain caused by the application of body heat to patients. Based on data from two participants, we found that the anterior cingulate cortex was more involved in acute pain processing than chronic pain. This experiment provides the first direct evidence that chronic pain involves information processing in areas of the brain that are different from those involved in acute pain.

Why is this important?

Chronic pain, defined as pain that lasts more than three months, affects up to 1 in 5 people in the US In 2019, the incidence of chronic pain is more common than diabetes, high blood pressure or depression.

Neuropathic pain resulting from damage to the nervous system, such as stroke and phantom limb disease, often does not respond to available treatments and can impair physical and emotional function and quality of life. A better understanding of how brain activity is measured to track pain may improve the diagnosis of chronic pain conditions and help develop new treatments such as deep brain stimulation.

What is not yet known

Although our study provides a proof of concept that signals from specific brain regions can serve as an objective measure of chronic pain, it is more likely that pain signals distributed in a wide network of the brain.

We do not yet know what other brain regions may contain important pain signals that may more accurately reflect subjective pain. It is also unclear whether the signals we found apply to patients with other pain conditions.

What’s next

We hope to use these newly discovered neural biomarkers to develop personal brain stimulation as a means of treating chronic diseases. This method involves incorporating signals into tailored algorithms that will manage the timing and location of brain stimulation on demand, similar to how a thermostat works.

Prasad ShirwalkarAssociate Professor of Anesthesia, University of California, San Francisco

This article was reprinted from The Conversation under Creative Commons license. Read the original article.

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