Scientists and clinicians at the University of California, San Francisco are studying chronic pain and developing new ways it may be treated. In a recent paper published in natural neuroscienceDr. Prasad Silvalkar and his team of doctors and researchers studied how types of chronic pain are represented in recordings of brain activity.
A neurologist and pain specialist at the UCSF Center for Pain Management, Mr. Silvalker studies and treats central pain syndrome, a type of chronic pain caused by dysfunction within the central nervous system. Treatment of this condition is difficult because it may not arise from external causes or damaged parts of the body. Further complicating the problem is the lack of specific knowledge about how different types of acute and chronic pain manifest themselves in the nervous system. “Things don’t happen in areas of the brain, but in coordinated distributed circuits of cells,” says Silvalker, referring to how pain is expressed in patterns of neural activity. “Certain brain regions may contribute to certain types of information processing, but by themselves cannot accomplish certain tasks.”
One treatment for chronic neuropathic pain, such as central pain syndrome, is to use deep brain stimulation (DBS) to manipulate the neural activity that causes painful sensations. DBS is also used to treat other neurological conditions such as Parkinson’s disease and more severe depression. However, in chronic pain, it is difficult to know exactly where to place DBS electrodes so that stimulation of the electrodes can effectively block brain activity that causes pain.
To better understand how central pain arises from brain function, this study examined neural activity recorded from four patients with central pain syndrome. Three experienced chronic pain during recovery from stroke and one experienced phantom limb pain after stroke. – Knee amputation of the right leg – and correlated neural activity with a questionnaire and a pain score of 0 to 10 reported by each patient. The researchers recorded data from intracranial electrodes placed in the patient’s orbitofrontal cortex (OFC) and anterior cingulate cortex (ACC), two brain regions previously associated with pain sensations.
Each patient underwent surgery and had a neural recording and stimulation platform implanted in the brain. The device is portable and allows each patient to go about their daily activities and record data representing their daily experience with central pain. Patients were prompted by a phone app to periodically record their current pain level and to record EEG data (electrocortical and local field potentials) from the neural implant for 30 seconds.
Shirvalkar and his collaborators used machine learning to associate features of neural activity with pain levels reported by each patient immediately before each brain recording. These features represent the relative presence of different frequencies in neural recordings collected from separate locations in the ACC and OFC and are robustly correlated with high and low pain states for each subject. It turns out. However, the pattern of these associations—which frequencies had the greatest power in which brain locations—varied considerably from patient to patient.
Patient-drawn diagram showing pain locations and pain intensity for four study participants. Green indicates mild pain and red indicates severe pain.University of California, San Francisco
Despite the observed differences in chronic pain-related brain activity between patients, researchers found some commonalities between them. Specifically, Shirvalkar and his team found that in all patients, low-frequency power, especially his 1–4 hertz delta waves, was increased in the lower region of his OFC. These regions were also located on the opposite side of the body or the contralateral side of the brain where the patient felt pain. “Although the top 10 features of the models that were good at predicting pain for individual patients differed, the main pattern that emerged was, which was surprising, the contralateral he I did,” he says Shirvalkar. “All of these patients had pain in only one part of their body, and this gave us an opportunity. What is it?”
Kate Nicholson, founder and executive director of the National Center for Pain Advocacy, said the research could lead to pain quantification and treatment for people suffering from central pain disorders and other conditions that cause chronic pain. says. “The search for objective measures of pain phenotypes is the holy grail. Together with subjective reporting, this will help healthcare professionals treat pain,” says Nicholson. “This study he only had four people, and it’s a very specific type of neuropathic pain, but what they found is certainly interesting. It’s very exciting, but We are still in the first stage.”
Going forward, Shirvalkar plans to incorporate his findings into better stimulation treatments for chronic pain. “This study just scratches the surface,” says Silvalker. “In the future, we may have stimulators that change the frequency and location of stimulation. It’s a moving target. We know what we’re doing and we’re trying to integrate them into a common model.”
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