by Using a brain implant that can record neural signals over several months, my research team and I discovered objective biomarkers of chronic pain severity in four patients with chronic pain during their daily lives.
Pain is one of the most important and basic subjective experiences a person can have. While there is a lot of evidence that pain perception takes place 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 objectively measure its intensity.
Most previous studies on the brain signals responsible for pain were based on laboratory experiments in artificial environments.
Until now, most research on chronic pain has used indirect measures of brain activity, such as functional magnetic resonance imaging or electroencephalography.
Furthermore, although physicians widely recognize that chronic pain is not just an extension of acute pain — like stubbing your toe — it is still unclear how the brain circuits behind acute and chronic pain relate to each other.
Our study was part of a larger clinical trial aimed at developing a new brain stimulation therapy to treat severe chronic pain.
My team surgically implanted electrodes into the brains of four patients with post-stroke pain and phantom limb pain to record neural signals in the orbitofrontal cortex, an area of the brain associated with planning and expectation, and the cingulate cortex, an area associated with emotion.
We asked patients about their pain intensity levels several times a day for up to six months. We then built machine learning models to attempt to match and predict each patient’s self-reported pain intensity scores with snapshots of their brain activity signals.
These brain signals consisted of electrical waves that could be broken down into different frequencies, similar to how a musical chord can be broken down into individual sounds of different pitches.
From these models, we found that low frequencies in the orbitofrontal cortex corresponded to each of the patient’s subjective pain intensities, providing an objective measure of chronic pain.
The greater the change in low-frequency activity that we measure, the more likely the patient is to experience severe pain.
Next, we wanted to compare the relationship between chronic pain and acute pain. We examined how the brain responded to intense, short-term pain caused by applying heat to patients’ bodies.
Based on data from two participants, we found that the anterior cingulate cortex was more involved in processing acute pain than chronic pain.
This experiment provides the first direct evidence that chronic pain involves information processing areas of the brain distinct from those involved in acute pain.
why does it matter
Chronic pain, defined as pain that lasts longer than three months, affects up to 1 in 5 people in the US. In 2019, the incidence of chronic pain was more common than diabetes, high blood pressure or depression.
Neuropathic pain resulting from damage to the nervous system, such as stroke and phantom limb pain, often does not respond to available treatments and can significantly impair physical and emotional function and quality of life.
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Better understanding how to measure brain activity to track pain could 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 are distributed across a wider brain network.
We still don’t know which other brain regions might harbor important pain signals that might more accurately reflect subjective pain. It is also unclear whether the signs we found would apply to patients with other pain conditions.
What is the next
We hope to use these newly discovered neural biomarkers to develop personalized brain stimulation as a way to treat chronic pain disorders. This approach involves embedding signals into custom algorithms that would govern the timing and location of brain stimulation on demand, similar to operating a thermostat.
Prasad Shirvalkar, Associate Professor of Anesthesia, University of California, San Francisco
This article is republished from The Conversation under a Creative Commons license. Read the original article.
