Machine learning classifiers for psychiatric disorders using resting-state functional magnetic resonance imaging (rs-fMRI) have recently attracted attention as a method for directly examining relationships between neural circuits and psychiatric disorders. To develop accurate and generalizable classifiers, we compiled a large-scale, multi-site, multi-disorder neuroimaging database. The database comprises resting-state fMRI and structural images of the brain from 993 patients and 1,421 healthy individuals, as well as demographic information such as age, sex, and clinical rating scales. To harmonize the multi-site data, nine healthy participants (“traveling subjects”) visited the sites from which the above datasets were obtained and underwent neuroimaging with 12 scanners. All participants consented to having their data shared and analyzed at multiple medical and research institutions participating in the project, and 706 patients and 1,122 healthy individuals consented to having their data disclosed. Finally, we have published four datasets: 1) the SRPBS Multi-disorder Connectivity Dataset 2), the SRPBS Multi-disorder MRI Dataset (restricted), 3) the SRPBS Multi-disorder MRI Dataset (unrestricted), and 4) the SRPBS Traveling Subject MRI Dataset.

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.

We conducted a multicenter, randomized, patient- and assessor-blinded, sham-controlled trial to investigate the efficacy of repetitive transcranial magnetic stimulation (rTMS) of the primary motor cortex (M1) in patients with neuropathic pain (NP). Patients were randomly assigned to receive 5 daily sessions of active or sham rTMS of M1 corresponding to the part of the body experiencing the worst pain (500 pulses per session at 5 Hz). Responders were invited to enroll in an open-label continuous trial involving 4 weekly sessions of active rTMS. The primary outcome was a mean decrease in a visual analogue scale of pain intensity (scaled 0-100 mm) measured daily during the daily sessions in an intention-to-treat population. Secondary outcomes were other pain scores, quality-of-life measures, and depression score. One hundred forty-four patients were assigned to the active or sham stimulation groups. The primary outcome, mean visual analogue scale decreases, was not significantly different (P = 0.58) between the active stimulation group (mean, 8.0) and the sham group (9.2) during the daily sessions. The secondary outcomes were not significantly different between 2 groups. The patients enrolled in the continuous weekly rTMS achieved more pain relief in the active stimulation group compared with the sham (P < 0.01). No serious adverse events were observed. Five daily sessions of rTMS with stimulus conditions used in this trial were ineffective in short-term pain relief in the whole study population with various NP. Long-term administration to the responders should be investigated for the clinical use of rTMS on NP in the future trials.

OBJECTIVE: Electrical motor cortex stimulation can relieve neuropathic pain (NP), but its use requires patients to undergo an invasive procedure. Repetitive transcranial magnetic stimulation (rTMS) of the primary motor cortex (M1) using a figure-8 coil can relieve NP noninvasively, but its ability to relieve lower limb pain is still limited. Deep rTMS using an H-coil can effectively stimulate deep brain regions and has been widely used for the treatment of various neurological diseases; however, there have been no clinical studies comparing the effectiveness of figure-8 coils and H-coils. This study assessed the clinical effectiveness of 5 once-daily stimulations with H-coils and figure-8 coils in patients with NP.METHODS: This randomized, double-blind, 3-way crossover trial examined 18 patients with NP who sequentially received 3 types of stimulations in the M1 for 5 consecutive days; each 5-day stimulation period was followed by a 17-day follow-up period before crossing over to the next type of stimulation. During each rTMS session, patients received a 5-Hz rTMS to the M1 region corresponding to the painful lower limb. The visual analog scale (VAS) and the Japanese version of the short-form McGill Pain Questionnaire 2 (SF-MPQ2-J) were used to measure pain intensity. The primary outcome was VAS score reduction immediately after and 1 hour after intervention.RESULTS: Both the VAS and SF-MPQ2-J showed significant pain improvement immediately after deep rTMS with an H-coil as compared with the sham group (p < 0.001 and p = 0.049, respectively). However, neither outcome measure showed significant pain improvement when using a figure-8 coil. The VAS also showed significant pain improvement 1 hour after deep rTMS with an H-coil (p = 0.004) but not 1 hour after rTMS using a figure-8 coil. None of the patients exhibited any serious adverse events.CONCLUSIONS: The current findings suggest that the use of deep rTMS with an H-coil in the lower limb region of the M1 in patients with NP was tolerable and could provide significant short-term pain relief.Clinical trial registration no.: UMIN000010536 (http://www.umin.ac.jp/ctr/)

Neuroprosthetic arms might potentially restore motor functions for severely paralysed patients. Invasive measurements of cortical currents using electrocorticography have been widely used for neuroprosthetic control. Moreover, magnetoencephalography (MEG) exhibits characteristic brain signals similar to those of invasively measured signals. However, it remains unclear whether non-invasively measured signals convey enough motor information to control a neuroprosthetic hand, especially for severely paralysed patients whose sensorimotor cortex might be reorganized. We tested an MEG-based neuroprosthetic system to evaluate the accuracy of using cortical currents in the sensorimotor cortex of severely paralysed patients to control a prosthetic hand. The patients attempted to grasp with or open their paralysed hand while the slow components of MEG signals (slow movement fields; SMFs) were recorded. Even without actual movements, the SMFs of all patients indicated characteristic spatiotemporal patterns similar to actual movements, and the SMFs were successfully used to control a neuroprosthetic hand in a closed-loop condition. These results demonstrate that the slow components of MEG signals carry sufficient information to classify movement types. Successful control by paralysed patients suggests the feasibility of using an MEG-based neuroprosthetic hand to predict a patient’s ability to control an invasive neuroprosthesis via the same signal sources as the non-invasive method.