Details of a Researcher - Ushiba, Junichi

Papers - Ushiba, Junichi

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Depth Sensor-Based Assessment of Reachable Work Space for Visualizing and Quantifying Paretic Upper Extremity Motor Function in People with Stroke

Kohei Okuyama, Michiyuki Kawakami, Shohei Tsuchimoto, Miho Ogura, Kohsuke Okada, Katsuhiro Mizuno, Junichi Ushiba, Meigen Liu

Research paper (scientific journal), Joint Work, Accepted

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Sensorimotor Connectivity after Motor Exercise with Neurofeedback in Post-Stroke Patients with Hemiplegia

Tsuchimoto S., Shindo K., Hotta F., Hanakawa T., Liu M., Ushiba J.

Neuroscience (Neuroscience) 416 109 - 125 2019.09

Research paper (scientific journal), Joint Work, Accepted, ISSN 03064522

© 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.

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Fast Electrophysiological Mapping of Rat Cortical Motor Representation on a Time Scale of Minutes during Skin Stimulation

Kosugi A., Castagnola E., Carli S., Ricci D., Fadiga L., Taoka M., Iriki A., Ushiba J.

Neuroscience (Neuroscience) 414 245 - 254 2019.08

Research paper (scientific journal), Joint Work, Accepted, ISSN 03064522

© 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.

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Two-stage regression of high-density scalp electroencephalograms visualizes force regulation signaling during muscle contraction

Hayashi M., Tsuchimoto S., Mizuguchi N., Miyatake M., Kasuga S., Ushiba J.

Journal of Neural Engineering (Journal of Neural Engineering) 16 ( 5 ) 2019.08

Research paper (scientific journal), Joint Work, Accepted, ISSN 17412560

© 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.

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Development of Rehabilitation System with Brain-Computer Interface for Subacute Stroke Patients

Hashimoto Y., Kakui T., Ushiba J., Liu M., Kamada K., Ota T.

Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018 (Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018) 51 - 56 2019.01

Research paper (international conference proceedings), Joint Work, ISSN 9781538666500

© 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.

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Evaluating the Effectiveness and Safety of the Electroencephalogram-Based Brain-Machine Interface Rehabilitation System for Patients With Severe Hemiparetic Stroke: Protocol for a Randomized Controlled Trial (BEST-BRAIN Trial)

Katsuhiro Mizuno, Takayuki Abe, Junichi Ushiba, Michiyuki Kawakami, Tomomi Ohwa, Kazuto Hagimura, Miho Ogura, Kohei Okuyama, Toshiyuki Fujiwara, Meigen Liu

JMIR Research Protocols 7 ( 12 ) e12339 2018.12

Research paper (scientific journal), Joint Work, Accepted

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Precise estimation of human corticospinal excitability associated with the levels of motor imagery-related EEG desynchronization extracted by a locked-in amplifier algorithm

Kensho Takahashi, Kenji Kato, Nobuaki Mizuguchi, Junichi Ushiba

Journal of NeuroEngineering and Rehabilitation (Journal of neuroengineering and rehabilitation) 15 ( 93 ) 2018.11

Research paper (scientific journal), Joint Work, Accepted

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.

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Prolonged Aftereffect of Visuomotor Adaptation to Gradually Distorted Reality Displayed on a See-Through Head-Mounted Device

Shoko Kasuga, Ryota Mori, Shunichi Kasahara, Junichi Rekimoto, Junichi Ushiba

International Journal of Human-Computer Interaction (International Journal of Human-Computer Interaction) 35 ( 15 ) 1345 - 1351 2018.10

Research paper (scientific journal), Joint Work, Accepted, ISSN 10447318

© 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.

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Muscle-selective disinhibition of corticomotor representations using a motor imagery-based brain-computer interface.

Mitsuaki Takemi, Tsuyoshi Maeda, Yoshihisa Masakado, Hartwig Roman Siebner, Junichi Ushiba

NeuroImage (NeuroImage) 183 597 - 605 2018.08

Research paper (scientific journal), Joint Work, Accepted, ISSN 10538119

© 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.

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Calcium transient dynamics of neural ensembles in the primary motor cortex of naturally behaving monkeys

Takahiro Kondo, Risa Saito, Masaki Otaka, Kimika Yoshino-Saito, Akihiro Yamanaka, Tetsuo Yamamori, Akiya Watakabe, Hiroaki Mizukami, Mark J. Schnitzer, Kenji F. Tanaka, Junichi Ushiba(*), Hideyuki Okano(*) *: Double corresponding author.

Cell Reports (Cell Reports) 24 ( 8 ) 2191 - 2195 2018.08

Research paper (scientific journal), Joint Work, Accepted

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Brain-computer interfaces for stroke rehabilitation: summary of the 2016 BCI Meeting in Asilomar

Guger C., Millán J., Mattia D., Ushiba J., Soekadar S., Prabhakaran V., Mrachacz-Kersting N., Kamada K., Allison B.

Brain-Computer Interfaces (Brain-Computer Interfaces) 5 ( 2-3 ) 41 - 57 2018.07

ISSN 2326263X

© 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.

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Subjective vividness of kinesthetic motor imagery is associated with the similarity in magnitude of sensorimotor event-related desynchronization between motor execution and motor imagery

Hisato Toriyama, Junichi Ushiba, Junichi Ushiyama

Frontiers in Human Neuroscience 12 (Frontiers in Human Neuroscience) 295 (10 pages) 2018.07

Research paper (scientific journal), Joint Work, Accepted

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Structural gray matter changes in the hippocampus and the primary motor cortex on an-hour-to-one-day scale can predict arm-reaching performance improvement

Midori Kodama, Takashi Ono, Fumio Yamashita, Hiroki Ebata, Meigen Liu, Shoko Kasuga, Junichi Ushiba.

Frontiers in Human Neuroscience 12 (Frontiers in Human Neuroscience) 209 (11 pages) 2018.06

Research paper (scientific journal), Joint Work, Accepted

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Resting-state pallidal-cortical oscillatory couplings in patients with predominant phasic and tonic dystonia

Fusako Yokochi, Kenji Kato, Hirokazu Iwamuro, Tsutomu Kamiyama, Katsuo Kimura, Akihiro Yugeta, Ryoichi Okiyama, makoto Taniguchi, Satoko Kumada, Junichi Ushiba

Frontiers in Neurology 9 (Frontiers in Neurology) 375 (12 pages) ( MAY ) 2018.05

Research paper (scientific journal), Joint Work, Accepted

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Change in reciprocal inhibition of the forearm with motor imagery among patients with chronic stroke.

Michiyuki Kawakami, Kohei Okuyama, Yoko Takahashi, Miho Hiramoto, Atsuko Nishimura, Junichi Ushiba, Toshiyuki Fujiwara and Meigen Liu

Neural Plasticity (Neural Plasticity) 2018 394636 (9 pages) 2018.04

Research paper (scientific journal), Joint Work, Accepted, ISSN 20905904

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Brain-computer interfaces for post-stroke motor rehabilitation: a meta-analysis

Maria A. Cervera, Surjo R. Soekadar, Junichi Ushiba, José del R. Millán, Meigen Liu, Niels Bibaumer, Gangadhar Garipelli

Annals of Clinical and Translational Neurology (Annals of Clinical and Translational Neurology) 5 ( 5 ) 651 - 663 2018.03

Research paper (scientific journal), Joint Work, Accepted

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Accurate motor mapping in awake common marmosets using micro-electrocorticographical stimulation and stochastic threshold estimation.

Akito Kosugi, Mitsuaki Takemi, Banty Tia, Elisa Castagnola, Alberto Ansaldo, Kenta Sato, Friedmann Awiszus, Kazuhiko Seki, Davide Ricci, Luciano Fadiga, Atsushi Iriki, Junichi Ushiba.

Journal of Neural Engineering (Journal of Neural Engineering) 15 ( 3 ) 036019 2018.03

Research paper (scientific journal), Joint Work, Accepted, ISSN 17412560

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Acquisition of a mental strategy to control a virtual tail via brain-computer interface.

Ayaka Fujisawa, Shoko Kasuga, Takaharu Suzuki, Junichi Ushiba.

Cognitive Neuroscience (Cognitive Neuroscience) 26 ( 1 ) 1 - 14 2018.01

Research paper (scientific journal), Joint Work, Accepted, ISSN 17588928

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Feasibility of task-specific brain-machine interface training for upper extremity paralysis in patients with chronic hemiparetic stroke

Atsuko Nishimoto, Michiyuki Kawakami, Toshiyuki Fujiwara, Miho Hiramoto, Kaoru Honaga , Kaoru Abe, Katsuhiro Mizuno, Junichi Ushiba, Meigen Liu.

Journal of Rehabilitation Medicine (Journal of Rehabilitation Medicine) 50 ( 1 ) 52 - 58 2018.01

Research paper (scientific journal), Joint Work, Accepted, ISSN 16501977

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Online detection of amplitude modulation of motor-related EEG desynchronization using a lock-in amplifier: Comparison with a fast Fourier transform, a continuous wavelet transform, and an autoregressive algorithm.

Kenji Kato, Kensho Takahashi, Nobuaki Mizuguchi, Junichi Ushiba.

Journal of Neuroscience Methods (Journal of Neuroscience Methods) 293 289 - 298 2018.01

Research paper (scientific journal), Joint Work, Accepted, ISSN 01650270

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