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A new study published in the American Academy Journal of Neurology aimed to demonstrate the clinical efficacy of brain-computer interface (BCI) training in the treatment of phantom limb pain.

"Previously, phantom limb pain had been treated by mirror therapy which uses a mirror to create an illusion of the phantom hand," study author Takufumi Yanagisawa told us. Yanagisawa is a Professor at the Institute for Advanced Co-creation Studies at Osaka University.

"The mirror therapy has been attributed to strengthening the cortical activities relating to the phantom hand. But recent studies showed some opposing results including our previous study (T. Yanagisawa et al., Nature communications, 2016)."

In his previous study, Yanagisawa found that strengthening the cortical activity relating to the phantom hand actually increases pain. Therefore, they have designed the current study to show that BCI training designed to reduce the cortical activity in fact, reduces phantom limb pain.

"We especially aimed to show that BCI training has significant effects in reducing pain compared to a 'sham' training and that the effect continues even after the trainings," Yanagisawa told us. "We hypothesized that the BCI training would reduce phantom limb pain even a day after the training compared to the sham training."

So far, there are no effective treatments for phantom limb pain. There is no medicine that is effective. In addition, although the mirror therapy is often used for it, it has not been recommended from a meta-analysis of the studies.

A part of this intractable nature comes from the fact that the pain originates in the brain. Previous studies demonstrate that some abnormal cortical activities relating to the phantom hand causes the pain. Therefore, to treat the pain, an effective method should be developed to modulate the cortical activity.

"Because we have been working on the BCI, which decodes the brain information and controls a machine based on the inferred information, we thought that the BCI would be the best way to modulate the abnormal cortical activities to reduce pain," Yanagisawa told us. "Moreover, in our hospital, we applied some surgical treatment for such intractable pain patients. Some of them had less pain after the surgery. But there was someone that had remaining pain. I would like to reduce the pain somehow."

Researchers developed a new BCI using magnetoencepharography (MEG). The MEG records very tiny changes of the magnetic field generated from the human brain. From the signals, researchers can infer the cortical activities precisely. Then, researchers applied AI technology and machine learning to the inferred cortical activities of the motor cortex. The AI inferred the motor information of hand grasping and opening. Based on the inferred information, a virtual phantom hand image was controlled.

"In the study, 12 patients tried to control the virtual phantom hand based on their brain activity by moving their phantom hand," Yanagisawa told us. "Here, for the AI to control the hand image, we used AI to infer the intact hand movements. The AI evaluates how the current cortical activities resembles to the cortical activity during the opening movement of the intact hand. When the cortical activities became similar to that of the opening of the intact hand, the AI sends the open label to make the virtual hand image 'open'. Therefore, the patients were trained to induce the cortical activity of intact hand by moving phantom hand. This inconsistent situation decreased the original phantom hand cortical activities and reduced the pain."

Patients did the BCI training as a randomized cross-over trial. All patients did two BCI training. One did a BCI training for three days and their pain was evaluated. After more than 21 days, the same subject did the random training, in which the virtual hand moved randomly regardless to the brain activity. Another patient did the opposite order. The two conditions were randomized among patients.

"We evaluated how the pain reduced after the BCI trainings of three days," Yanagisawa told us. "The pain was evaluated by visual analogue scale, VAS, which uses 100mm bar to be pointed at the current pain intensity."

Yanagisawa and the team found that BCI training demonstrated significant pain reduction not only during the three days of training but also after the training for five days compared to the sham training.

"The significant pain reduction was just as we expected," Yanagisawa told us. "But the efficacy was more than I expected. The pain reduction was mostly the same as the reduction by the other therapy that took several months. And the reduction was sustained for a week. Therefore, the results strongly suggested that the BCI training once a week will be effective to reduce the pain continuously. That is, the BCI training is clinically feasible."

Researchers concluded that the results were very encouraging to apply the BCI training for clinical practice.

"We are now making a portable easily accessible system of the same effect," Yanagisawa told us. "Because MEG provides very expensive measurements, we are now constructing an EEG system. We are planning another clinical trial to show the clinical efficacy of the EEG system."

Yanagisawa and the team believes that similar BCI training will be applied for other neuropsychiatric disorders. Recent neuroscience revealed that some abnormal brain activities attributes to the neuropsychiatric disorders. Yanagisawa believes BCI will be applied for such disorders to modulate their symptom or to eliminate the cause effectively.