Junichi Ushiba

Effects of neurofeedback training with an electroencephalogram-based brain-computer interface for hand paralysis in patients with chronic stroke: a preliminary case series study.

OBJECTIVE To explore the effectiveness of neurorehabilitative training using an electroencephalogram-based brain- computer interface for hand paralysis following stroke. DESIGN A case series study. SUBJECTS Eight outpatients with chronic stroke demonstrating moderate to severe hemiparesis. METHODS Based on analysis of volitionally decreased amplitudes of sensory motor rhythm during motor imagery involving extending the affected fingers, real-time visual feedback was provided. After successful motor imagery, a mechanical orthosis partially extended the fingers. Brain-computer interface interventions were carried out once or twice a week for a period of 4-7 months, and clinical and neurophysiological examinations pre- and post-intervention were compared. RESULTS New voluntary electromyographic activity was measured in the affected finger extensors in 4 cases who had little or no muscle activity before the training, and the other participants exhibited improvement in finger function. Significantly greater suppression of the sensory motor rhythm over both hemispheres was observed during motor imagery. Transcranial magnetic stimulation showed increased cortical excitability in the damaged hemisphere. Success rates of brain-computer interface training tended to increase as the session progressed in 4 cases. CONCLUSION Brain-computer interface training appears to have yielded some improvement in motor function and brain plasticity. Further controlled research is needed to clarify the role of the brain-computer interface system.

Event-related desynchronization reflects downregulation of intracortical inhibition in human primary motor cortex

There is increasing interest in electroencephalogram (EEG)-based brain-computer interface (BCI) as a tool for rehabilitation of upper limb motor functions in hemiplegic stroke patients. This type of BCI often exploits mu and beta oscillations in EEG recorded over the sensorimotor areas, and their event-related desynchronization (ERD) following motor imagery is believed to represent increased sensorimotor cortex excitability. However, it remains unclear whether the sensorimotor cortex excitability is actually correlated with ERD. Thus we assessed the association of ERD with primary motor cortex (M1) excitability during motor imagery of right wrist movement. M1 excitability was tested by motor evoked potentials (MEPs), short-interval intracortical inhibition (SICI), and intracortical facilitation (ICF) with transcranial magnetic stimulation (TMS). Twenty healthy participants were recruited. The participants performed 7 s of rest followed by 5 s of motor imagery and received online visual feedback of the ERD magnitude of the contralateral hand M1 while performing the motor imagery task. TMS was applied to the right hand M1 when ERD exceeded predetermined thresholds during motor imagery. MEP amplitudes, SICI, and ICF were recorded from the agonist muscle of the imagined hand movement. Results showed that the large ERD during wrist motor imagery was associated with significantly increased MEP amplitudes and reduced SICI but no significant changes in ICF. Thus ERD magnitude during wrist motor imagery represents M1 excitability. This study provides electrophysiological evidence that a motor imagery task involving ERD may induce changes in corticospinal excitability similar to changes accompanying actual movements.

Modulation of mu rhythm desynchronization during motor imagery by transcranial direct current stimulation

BackgroundThe mu event-related desynchronization (ERD) is supposed to reflect motor preparation and appear during motor imagery. The aim of this study is to examine the modulation of ERD with transcranial direct current stimulation (tDCS).MethodsSix healthy subjects were asked to imagine their right hand grasping something after receiving a visual cue. Electroencephalograms (EEGs) were recorded near the left M1. ERD of the mu rhythm (mu ERD) by right hand motor imagery was measured. tDCS (10 min, 1 mA) was used to modulate the cortical excitability of M1. Anodal, cathodal, and sham tDCS were tested in each subject with a randomized sequence on different days. Each condition was separated from the preceding one by more than 1 week in the same subject. Before and after tDCS, mu ERD was assessed. The motor thresholds (MT) of the left M1 were also measured with transcranial magnetic stimulation.ResultsMu ERD significantly increased after anodal stimulation, whereas it significantly decreased after cathodal stimulation. There was a significant correlation between mu ERD and MT.ConclusionsOpposing effects on mu ERD based on the orientation of the stimulation suggest that mu ERD is affected by cortical excitability.

Influence of mirror therapy on human motor cortex.

This article investigates whether or not mirror therapy alters the neural mechanisms in human motor cortex. Six healthy volunteers participated. The study investigated the effects of three main factors of mirror therapy (observation of hand movements in a mirror, motor imagery of an assumed affected hand, and assistance in exercising the assumed affected hand) on excitability changes in the human motor cortex to clarify the contribution of each factor. The increase in motor-evoked potential (MEP) amplitudes during motor imagery tended to be larger with a mirror than without one. Moreover, MEP amplitudes increased greatly when movements were assisted. Watching the movement of one hand in a mirror makes it easier to move the other hand in the same way. Moreover, the increase in MEP amplitudes is related to the synergic effects of afferent information and motor imagery.

Muscle dependency of corticomuscular coherence in upper and lower limb muscles and training-related alterations in ballet dancers and weightlifters.

It has been well documented that the 15- to 35-Hz oscillatory activity of the sensorimotor cortex shows coherence with the muscle activity during weak to moderate steady contraction. To investigate the muscle dependency of the corticomuscular coherence and its training-related alterations, we quantified the coherence between electroencephalogram (EEG) from the sensorimotor cortex and rectified electromyogram (EMG) from five upper limb (first dorsal interosseous, flexor carpi radialis, extensor carpi radialis, biceps brachii, triceps brachii) and four lower limb muscles (soleus, tibialis anterior, biceps femoris, rectus femoris), while maintaining a constant force level at 30% of maximal voluntary contraction of each muscle, in 24 untrained, 12 skill-trained (ballet dancers), and 10 strength-trained (weightlifters) individuals. Data from untrained subjects demonstrated the muscle dependency of corticomuscular coherence. The magnitude of the EEG-EMG coherence was significantly greater in the distally located lower limb muscles, such as the soleus and tibialis anterior, than in the upper or other lower limb muscles in untrained subjects (P < 0.05). These results imply that oscillatory coupling between the sensorimotor cortex and spinal motoneurons during steady contraction differs among muscles, according to the functional role of each muscle. In addition, the ballet dancers and weightlifters showed smaller EEG-EMG coherences than the untrained subjects, especially in the lower limb muscles (P < 0.05). These results indicate that oscillatory interaction between the sensorimotor cortex and spinal motoneurons can be changed by long-term specialized use of the muscles and that this neural adaptation may lead to finer control of muscle force during steady contraction.

Brain-computer interface with somatosensory feedback improves functional recovery from severe hemiplegia due to chronic stroke.

Recent studies have shown that scalp electroencephalogram (EEG) based brain-computer interface (BCI) has a great potential for motor rehabilitation in stroke patients with severe hemiplegia. However, key elements in BCI architecture for functional recovery has yet to be clear. We in this study focused on the type of feedback to the patients, which is given contingently to their motor-related EEG in a BCI context. The efficacy of visual and somatosensory feedbacks was compared by a two-group study with the chronic stroke patients who are suffering with severe motor hemiplegia. Twelve patients were asked an attempt of finger opening in the affected side repeatedly, and the event-related desynchronization (ERD) in EEG of alpha and beta rhythms was monitored over bilateral parietal regions. Six patients were received a simple visual feedback in which the hand open/grasp picture on screen was animated at eye level, following significant ERD. Six patients were received a somatosensory feedback in which the motor-driven orthosis was triggered to extend the paralyzed fingers from 90 to 50°. All the participants received 1-h BCI treatment with 12–20 training days. After the training period, while no changes in clinical scores and electromyographic (EMG) activity were observed in visual feedback group after training, voluntary EMG activity was newly observed in the affected finger extensors in four cases and the clinical score of upper limb function in the affected side was also improved in three participants in somatosensory feedback group. Although the present study was conducted with a limited number of patients, these results imply that BCI training with somatosensory feedback could be more effective for rehabilitation than with visual feedback. This pilot trial positively encouraged further clinical BCI research using a controlled design.

Efficacy of brain-computer interface-driven neuromuscular electrical stimulation for chronic paresis after stroke.

OBJECTIVE Brain computer interface technology is of great interest to researchers as a potential therapeutic measure for people with severe neurological disorders. The aim of this study was to examine the efficacy of brain computer interface, by comparing conventional neuromuscular electrical stimulation and brain computer interface-driven neuromuscular electrical stimulation, using an A-B-A-B withdrawal single-subject design. METHODS A 38-year-old male with severe hemiplegia due to a putaminal haemorrhage participated in this study. The design involved 2 epochs. In epoch A, the patient attempted to open his fingers during the application of neuromuscular electrical stimulation, irrespective of his actual brain activity. In epoch B, neuromuscular electrical stimulation was applied only when a significant motor-related cortical potential was observed in the electroencephalogram. RESULTS The subject initially showed diffuse functional magnetic resonance imaging activation and small electro-encephalogram responses while attempting finger movement. Epoch A was associated with few neurological or clinical signs of improvement. Epoch B, with a brain computer interface, was associated with marked lateralization of electroencephalogram (EEG) and blood oxygenation level dependent responses. Voluntary electromyogram (EMG) activity, with significant EEG-EMG coherence, was also prompted. Clinical improvement in upper-extremity function and muscle tone was observed. CONCLUSION These results indicate that self-directed training with a brain computer interface may induce activity- dependent cortical plasticity and promote functional recovery. This preliminary clinical investigation encourages further research using a controlled design.

Daily training with realistic visual feedback improves reproducibility of event-related desynchronisation following hand motor imagery

OBJECTIVE Few brain-computer interface (BCI) studies have addressed learning mechanisms by exposure to visual feedback that elicits scalp electroencephalogram. We examined the effect of realistic visual feedback of hand movement associated with sensorimotor rhythm. METHODS Thirty-two healthy participants performed in five daily training in which they were shown motor imagery of their dominant hand. Participants were randomly assigned to 1 of 4 experimental groups receiving different types of visual feedback on event-related desynchronisation (ERD) derived over the contralateral sensorimotor cortex: no feedback as a control, bar feedback with changing bar length, anatomically incongruent feedback in which the hand open/grasp picture on screen was animated at eye level, and anatomically congruent feedback in which the same hand open/grasp picture was animated on the screen overlaying the participants hand. RESULTS Daily training with all types of visual feedback induced more robust ERD than the no feedback condition (p < 0.05). The anatomically congruent feedback produced the highest reproducibility of ERD with the smallest inter-trial variance (p < 0.05). CONCLUSION Realistic feedback training is a suitable method to acquire the skill to control a BCI system. SIGNIFICANCE This finding highlights the possibility of improvement of reproducibility of ERD and can help to use BCI techniques.

Change in brain activity through virtual reality-based brain-machine communication in a chronic tetraplegic subject with muscular dystrophy

BackgroundFor severely paralyzed people, a brain-computer interface (BCI) provides a way of re-establishing communication. Although subjects with muscular dystrophy (MD) appear to be potential BCI users, the actual long-term effects of BCI use on brain activities in MD subjects have yet to be clarified. To investigate these effects, we followed BCI use by a chronic tetraplegic subject with MD over 5 months. The topographic changes in an electroencephalogram (EEG) after long-term use of the virtual reality (VR)-based BCI were also assessed. Our originally developed BCI system was used to classify an EEG recorded over the sensorimotor cortex in real time and estimate the users motor intention (MI) in 3 different limb movements: feet, left hand, and right hand. An avatar in the internet-based VR was controlled in accordance with the results of the EEG classification by the BCI. The subject was trained to control his avatar via the BCI by strolling in the VR for 1 hour a day and then continued the same training twice a month at his home.ResultsAfter the training, the error rate of the EEG classification decreased from 40% to 28%. The subject successfully walked around in the VR using only his MI and chatted with other users through a voice-chat function embedded in the internet-based VR. With this improvement in BCI control, event-related desynchronization (ERD) following MI was significantly enhanced (p < 0.01) for feet MI (from -29% to -55%), left-hand MI (from -23% to -42%), and right-hand MI (from -22% to -51%).ConclusionsThese results show that our subject with severe MD was able to learn to control his EEG signal and communicate with other users through use of VR navigation and suggest that an internet-based VR has the potential to provide paralyzed people with the opportunity for easy communication.

On-Demand Control System for Deep Brain Stimulation for Treatment of Intention Tremor

Intention tremor becomes evident only when patients intend to move their body and is characterized by dysmetria. We have developed an on‐demand control system that triggers the switching on/off of deep brain stimulation (DBS) instantly for the control of intention tremor.