Published papers

© 2018 IEEE. There have been recent advances in brain-computer interfaces for post-stroke rehabilitation. In particular, compact and embedded brain-computer interface systems with neuromuscular electrical stimulation have been developed by industry and academia, and some of them can potentially be used at the bedside. However, limited studies have demonstrated their safety and feasibility for treatment in subacute stroke patients. The aim of this pilot study was to first develop a brain-computer interface system for subacute stroke inpatients that is usable at the bedside and to show the safety and feasibility using a small cohort of inpatients. Four hemiplegic stroke inpatients in the very early phase (7-24 days from stroke onset) participated in this study. The portable brain-computer interface system shows the amplitude of sensorimotor rhythms extracted from scalp electroencephalograms in real time. Patients attempted to extend the wrist on their affected side, and neuromuscular electrical stimulation was applied only when the brain-computer interface system detected significant movement intention-related electroencephalogram changes. Each brain-computer interface training lasted 40 minutes. On average, 120-200 training trials of the wrist extension task were successfully and safely conducted over 3.3 days (range 2-4 days) with the bedside brain-computer interface system. Furthermore, electroencephalogram results showed a new significant event-related desynchronization in the damaged hemisphere after training. These results clearly show the proposed bedside brain-computer interface system's safety and feasibility and also demonstrated electrophysiological plasticity in the damaged hemisphere in subacute patients with post-stroke hemiplegia. Larger clinical studies are needed to identify the brain-computer interface system's clinical efficacy and its effect size in the subacute post-stroke patient population.

© 2018, © 2018 Taylor & Francis Group, LLC. Growing evidence suggests that the gradual transformation of visuomotor association drives a distinct learning process from abrupt transformation in humans. In the current study, we developed a novel omnidirectional visuomotor transformation paradigm to study details of such difference in more realistic environment than conventional experimental systems. Participants were asked to perform a repetitive three-dimensional (3D) arm-reaching task to a target on a front touch panel, wearing a video see-through head-mounted device that displayed a rotating view of surrounding images. In the abrupt condition, the images were rotated by 20°; in the gradual condition, the rotation was increased in a stepwise-manner from 0° to 20°. In both conditions, pointing errors were decreased after adaptation. Further, although the aftereffect of adaptation was not different between conditions, the speed of decay of the aftereffect, which was quantified by an exponential fit, was slower in the gradual condition, suggesting longer-lasting aftereffects for the gradual shift.

BACKGROUND: Physical motor exercise aided by an electroencephalogram (EEG)-based brain-computer interface (BCI) is known to improve motor recovery in patients with stroke. In such a BCI paradigm, event-related desynchronization (ERD) in the alpha and beta bands extracted from EEG recorded over the primary sensorimotor area (SM1) is often used, since ERD has been suggested to be associated with an increase of corticospinal excitability. Recently, we demonstrated a novel online lock-in amplifier (LIA) algorithm to estimate the amplitude modulation of motor-related SM1 ERD. With this algorithm, the delay time, accuracy, and stability to estimate motor-related SM1 ERD were significantly improved compared with the conventional fast Fourier transformation (FFT) algorithm. These technical improvements to extract an ERD trace imply a potential advantage for a better trace of the excitatory status of the SM1 in a BCI context. Therefore, the aim of this study was to assess the precision of LIA-based ERD tracking for estimation of corticospinal excitability using a transcranial magnetic stimulation (TMS) paradigm.METHODS: The motor evoked potentials (MEPs) induced by single-pulse TMS over the primary motor cortex depending on the magnitudes of SM1 ERD (i.e., 35% and 70%) extracted by the online LIA or FFT algorithm were monitored during a motor imagery task of wrist extension in 17 healthy participants. Then, the peak-to-peak amplitudes of MEPs and their variabilities were assessed to investigate the precision of the algorithms.RESULTS: We found greater MEP amplitude evoked by single-pulse TMS triggered by motor imagery-related alpha SM1 ERD than at rest. This enhancement was associated with the magnitude of ERD in both FFT and LIA algorithms. Moreover, we found that the variabilities of peak-to-peak MEP amplitudes at 35% and 70% ERDs calculated by the novel online LIA algorithm were smaller than those extracted using the conventional FFT algorithm.CONCLUSIONS: The present study demonstrated that the calculation of motor imagery-related SM1 ERDs using the novel online LIA algorithm led to a more precise estimation of corticospinal excitability than when the ordinary FFT-based algorithm was used.

© 2019 IOP Publishing Ltd. Objective. A critical feature for the maintenance of precise skeletal muscle force production by the human brain is its ability to configure motor function activity dynamically and adaptively in response to visual and somatosensory information. Existing studies have concluded that not only the sensorimotor area but also distributed cortical areas act cooperatively in the generation of motor commands for voluntary force production to the desired level. However, less attention has been paid to such physiological mechanisms in conventional brain-computer interface (BCI) design and implementation. We proposed a new, physiologically inspired two-stage decoding method to see its contribution on accuracy improvement of BCI. Approach. We performed whole-head high-density scalp electroencephalographic (EEG) recording during a right finger force-matching task at three strength levels (20%, 40%, and 60% maximal voluntary contraction following a resting state). A two-stage regression approach was employed that decodes muscle contraction level from EEG signals in the multi-level force-matching task and translates them into: (1) presence/absence of muscle contraction as a first stage; and (2) muscle contraction level as a second stage. Dimensionality reduction of the EEG signals, using principal component analysis, avoided multicollinearity during multiple regression, and data-driven stepwise multiple regression identified EEG components that were involved in the multi-level force-matching task. Main results. An alternatively tuned two-stage regressor accurately decoded muscle contraction level with online processing rather than the conventional decoders, and identified EEG components that were related to voluntary force production. Relaxation/contraction state-dependent EEG components were localized dominantly in the contralateral parieto-temporal regions, whereas multi-level force regulation-dependent EEG components came from the fronto-parietal regions. Significance. Our findings identify respective cortical signalings during relaxation/contraction and multi-level force regulation using a sensor-based approach with EEG. Simulation-based assessment of the current physiologically inspired decoding technique proved improved accuracy in online BCI control.

© 2019 Elsevier Ltd Impaired finger motor function in post-stroke hemiplegia is a debilitating condition with no evidence-based or accessible treatments. Here, we evaluated the neurophysiological effectiveness of direct brain control of robotic exoskeleton that provides movement support contingent with brain activity. To elucidate the mechanisms underlying the neurofeedback intervention, we assessed resting-state functional connectivity with functional magnetic resonance imaging (rsfcMRI) between the ipsilesional sensory and motor cortices before and after a single 1-h intervention. Eighteen stroke patients were randomly assigned to crossover interventions in a double-blind and sham-controlled design. One patient dropped out midway through the study, and 17 patients were included in this analysis. Interventions involved motor imagery, robotic assistance, and neuromuscular electrical stimulation administered to a paretic finger. The neurofeedback intervention delivered stimulations contingent on desynchronized ipsilesional electroencephalographic (EEG) oscillations during imagined movement, and the control intervention delivered sensorimotor stimulations that were independent of EEG oscillations. There was a significant time × intervention interaction in rsfcMRI in the ipsilesional sensorimotor cortex. Post-hoc analysis showed a larger gain in increased functional connectivity during the neurofeedback intervention. Although the neurofeedback intervention delivered fewer total sensorimotor stimulations compared to the sham-control, rsfcMRI in the ipsilesional sensorimotor cortices was increased during the neurofeedback intervention compared to the sham-control. Higher coactivation of the sensory and motor cortices during neurofeedback intervention enhanced rsfcMRI in the ipsilesional sensorimotor cortices. This study showed neurophysiological evidence that EEG-contingent neurofeedback is a promising strategy to induce intrinsic ipsilesional sensorimotor reorganization, supporting the importance of integrating closed-loop sensorimotor processing at a neurophysiological level.

© 2019 Elsevier Ltd The topographic map of motor cortical representation, called the motor map, is not invariant, but can be altered by motor learning, neurological injury, and functional recovery from injury. Although much attention has been paid to short-term changes of the motor map, robust measures have not been established. The existing mapping methods are time-consuming, and the obtained maps are confounded by time preference. The purpose of this study was to examine the dynamics of the motor map on a timescale of minutes during transient somatosensory input by a fast motor mapping technique. We applied 32-channel micro-electrocorticographic electrode arrays to the rat sensorimotor cortex for cortical stimulation, and the topographic profile of motor thresholds in forelimb muscle was identified by fast motor mapping. Sequential motor maps were obtained every few minutes before, during, and just after skin stimulation to the dorsal forearm using a wool buff. During skin stimulation, the motor map expanded and the center of gravity of the map was shifted caudally. The expansion of the map persisted for at least a few minutes after the end of skin stimulation. Although the motor threshold of the hotspot was not changed, the area in which it was decreased appeared caudally to the hotspot, which may be in the somatosensory cortex. The present study demonstrated rapid enlargement of the forelimb motor map in the order of a few minutes induced by skin stimulation. This helps to understand the spatial dynamism of motor cortical representation that is modulated rapidly by somatosensory input.

© 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group. Brain-computer interfaces (BCIs) based on motor imagery have been gaining attention as tools to facilitate recovery from movement disorders resulting from stroke or other causes. These BCIs can detect imagined movements that are typically required within conventional rehabilitation therapy. This information about the timing, intensity, and location of imagined movements can help assess compliance and control feedback mechanisms such as functional electrical stimulation (FES) and virtual avatars. Here, we review work from eight groups that each presented recent results with BCI-based rehabilitation at a workshop during the 6th International Brain-Computer Interface Meeting. We also present major directions and challenges for future research.

無麻酔・自由行動下でのコモン・マーモセット一次運動野皮質ニューロン活動を、蛍光カルシウムプローブと光ファイバー顕微鏡を用いて100個単位で観察することに成功し、運動中だけでなく運動前や運動後の神経活動パターンも上肢運動方向を符号化していることを明らかにした。

脳卒中片麻痺上肢に対するブレイン・マシン・インターフェース訓練に関するランダム比較試験（9件）をメタアナリシスした結果、比較対象群に対して有意に治療効果が高いことを明らかにした。

© 2018 Bridging between brain activity and machine control, brain-computer interface (BCI) can be employed to activate distributed neural circuits implicated in a specific aspect of motor control. Using a motor imagery-based BCI paradigm, we previously found a disinhibition within the primary motor cortex contralateral to the imagined movement, as evidenced by event-related desynchronization (ERD) of oscillatory cortical activity. Yet it is unclear whether this BCI approach does selectively facilitate corticomotor representations targeted by the imagery. To address this question, we used brain state-dependent transcranial magnetic stimulation while participants performed kinesthetic motor imagery of wrist movements with their right hand and received online visual feedback of the ERD. Single and paired-pulse magnetic stimulation were given to the left primary motor cortex at a low or high level of ERD to assess intracortical excitability. While intracortical facilitation showed no modulation by ERD, short-latency intracortical inhibition was reduced the higher the ERD. Intracortical disinhibition was only found in the agonist muscle targeted by motor imagery at high ERD level, but not in the antagonist muscle. Single pulse motor-evoked potential was also increased the higher the ERD. However, at high ERD level, this facilitatory effect on overall corticospinal excitability was not selective to the agonist muscle. Analogous results were found in two independent experiments, in which participants either performed kinesthetic motor imagery of wrist extension or flexion. Our results showed that motor imagery-based BCI can selectively disinhibit the corticomotor output to the agonist muscle, enabling effector-specific training in patients with motor paralysis.

上肢運動想起時に体性感覚運動野近傍の頭皮脳波で観察される事象関連脱同期現象は、被験者の運動内観の鮮明さに相関することを明らかにした。

視野左右鏡像反転環境下での上肢到達運動を5日間にわたって継続し、磁気共鳴画像法による脳構造撮像をおこなった結果、初回訓練後に一次運動野と海馬の灰白質信号が変化した被験者では5日後の運動パフォーマンスが高かったことを明らかにした。

ジストニア患者における淡蒼球-大脳皮質間の機能結合を解析したところ、特定周波数の結合強度によってジストニアサブタイプを分類することが可能であることを認めた。

慢性期脳卒中片麻痺患者の麻痺側上肢運動企図時に、拮抗筋との間に形成されている脊髄内相反抑制神経回路が増強すること、皮質損傷例よりも皮質下構造損傷例のほうがその効果が著明であること、10日間にわたる継続的なブレイン・マシン・インターフェース訓練によってその効果が更に増強することを報告した。

運動皮質へのパルス電流刺激強度と誘発筋電図振幅の小標本分布から運動閾値を推定するアルゴリズムを利用して、非麻酔下コモン・マーモセットでの高速運動地図作成法を確立した。

コンピュータ・グラフィックスで生成された尻尾様オブジェクトを頭皮脳波変化で動作させるブレイン・マシン・インターフェースを構築し、適応過程におけるユーザーの内観変化を分析した。

ブレイン・マシン・インターフェースで利用されている頭皮脳波成分は、ロックインアンプ機構によって低遅延・高精密に実時間検出できることを示した。

臨床運用性を担保したブレイン・マシン・インターフェース（BMI）訓練が脳卒中重度片麻痺上肢の手指機能の改善をもたらすことと、BMIの正動率が運動機能スケールの改善に送還することを臨床研究により明らかにした。