Induced sensorimotor brain plasticity controls pain in phantom limb patients

The cause of pain in a phantom limb after partial or complete deafferentation is an important problem. A popular but increasingly controversial theory is that it results from maladaptive reorganization of the sensorimotor cortex, suggesting that experimental induction of further reorganization should affect the pain, especially if it results in functional restoration. Here we use a brain–machine interface (BMI) based on real-time magnetoencephalography signals to reconstruct affected hand movements with a robotic hand. BMI training induces significant plasticity in the sensorimotor cortex, manifested as improved discriminability of movement information and enhanced prosthetic control. Contrary to our expectation that functional restoration would reduce pain, the BMI training with the phantom hand intensifies the pain. In contrast, BMI training designed to dissociate the prosthetic and phantom hands actually reduces pain. These results reveal a functional relevance between sensorimotor cortical plasticity and pain, and may provide a novel treatment with BMI neurofeedback.

of ANOVA of the z-scored cortical currents between the two movements were color-coded on the normalized brain surface (the side of the real hand is shown on the left, n = 10). (c) The accuracy of classifying the two movements of the real hands was evaluated using two different features for pre-and post-trainings. The averaged accuracies are shown with a 95% confidence interval (error bar) for each feature (n = 10). The accuracies were not statistically different between pre-and post-trainings for each hemisphere (p > 0.05 for each, uncorrected, n = 10, Student paired t-test).
Gray: the accuracy using the estimated cortical currents on the sensorimotor cortex contralateral to the intact hand; red: that using the estimated cortical currents on the sensorimotor cortex ipsilateral to the intact hand. The z-scored cortical currents during grasping or opening of the phantom hand were averaged at each vertex for the 10 patients and color-coded on the normalized brain surfaces for pre-BMI (upper panel) and post-BMI (middle panel). Each box corresponds to each experiment (a, phantom hand decoder; b, random decoder; c, real hand decoder). The t-value of the paired Student t-test between the z-scored cortical currents of post-BMI and pre-BMI was color-coded on the normalized brain surface (lower panel). (d-f) The F-values of two-way ANOVA for the factor of pre vs. post (two movements × pre-and post-BMI) were color-coded on the normalized brain surface for each training. The Pearson's correlation coefficient between the Δcurrents and the ΔVAS at each vertex was color-coded on the normalized brain for grasping and opening (n = 30).

Supplementary Tables
Supplementary Table 1 Pt 2 Phantom I feel I became able to control the prosthetic hand. I felt tired.
Random I could not move the prosthetic hand well.
Real I became better able to control the prosthetic hand in the later part of the training.
However, the arm sometimes moved when I did not intend to move the arm. I thought that controlling my breath improved the accuracy of controlling the prosthetic hand. I breathed in during grasping and out during opening.
Pt 3 Phantom I felt I became better able to control the prosthetic hand. I was tired.
Random I could not control the prosthetic hand well. The prosthetic hand did not move as I intended.
Real It was difficult for me to control the prosthetic hand for a grasping posture. But it was rather easy to control it for an opening posture. I felt I could learn to control the prosthetic hand.
Pt 4 Phantom I could control the prosthetic hand for opening at almost the same timing when I intended to open my phantom hand. However, it was difficult to control the hand for grasping. My feeling of numbness in the phantom hand increased after the training. Also, I felt something like muscle aches in my phantom hand. The pain seems to be concentrated on the tip of the phantom hand after the training. Usually, the pain was distributed uniformly from the elbow to hand. However, after the training, the pain was increased in the hand and decreased around the elbow.
Random I could not control the prosthetic hand well. The prosthetic hand did not move according to the intended timing.
Real I could not master the techniques to control the prosthetic hand. I could easily control it for grasping, but opening was difficult. The prosthetic hand opened at a time when I did not intend it to open. Also, I could not sustain the opening posture.
Pt 5 Phantom It was difficult to control. I felt a little improvement in control after the training, although it was difficult to control both grasping and opening.
Random I could control the prosthetic hand for grasping, but it was difficult to control it for opening.
Real I could control the prosthetic hand for grasping, but it was difficult to control it for opening. The pain improved slightly, perhaps because I concentrated on the task.
Pt 6 Phantom I felt I could control the prosthetic hand better than the previous case (Random). The prosthetic hand moved at the intended time.

Random
The prosthetic hand opened at an unintended time. I could not maintain grasping with the prosthetic hand. I felt that controlling it was difficult, because I have not thought about moving my phantom hand for a long time.

Real
It was difficult to control the prosthetic hand, although I tried various ways to move my phantom hand. During the middle of the training, I felt that I could control the prosthetic hand. But at the end of the training, the prosthetic hand seemed to move against my intentions.
Pt 7 Phantom I could control the prosthetic hand better than I expected. The accuracy for controlling the hand improved in the later part of the training. I felt strong pain attacks several times during the training.

Random
It was difficult to control the prosthetic hand. Opening of the prosthetic hand was controlled by imagining hand postures of coded signs during a basketball game. I did not feel a significant change in pain, although I felt a small increase in pain after the training.

Real
The prosthetic hand was successfully grasped by imaging a grasping posture of the right phantom hand with my eyes closed. Opening the prosthetic hand was difficult. The accuracy for controlling the prosthetic hand improved in the later part of the training.

Random
The prosthetic hand did not move according to my intention. The pain did not change much.

Real
Controlling the prosthetic hand was difficult. I did not feel any changes throughout the training.
Pt 9 Phantom Controlling the prosthetic hand was difficult. I think I learned to perform grasping, although opening the prosthetic hand was difficult. I felt that my pain increased during the training, although it decreased after the training.
Random I could control the prosthetic hand for a grasping posture with almost 100% accuracy.
Opening was more difficult. The prosthetic hand opened when I did not intend it to move.
My pain increased a little.
Real I learned to control the prosthetic hand well compared to the previous experiment [random]. I could sometimes open the prosthetic hand when I intended. Opening was still difficult compared to grasping.
Pt 10 Phantom Controlling the prosthetic hand was difficult. I could not improve my ability to control the prosthetic hand. I felt that my pain was unchanged.

Random
Controlling the prosthetic hand was difficult. I think I was able to improve my ability to control the prosthetic hand a little in the later part of the training. My pain was unchanged.

Real
Controlling the prosthetic hand was difficult. I developed no change in my ability to control the prosthetic hand. My pain was unchanged.