Showing papers on "Motor imagery published in 2014"

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

Abstract: 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. All the 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. Eight patients were received a somatosensory feedback in which the motor-driven orthosis was triggered to extend the paralyzed fingers from 90 to 50 degrees. 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 4 cases and the clinical score of upper limb function in the affected side was also improved in 5 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.

Distinct roles for alpha- and beta-band oscillations during mental simulation of goal-directed actions.

Abstract: Rhythmic neural activity within the alpha (8–12 Hz) and beta (15–25 Hz) frequency bands is modulated during actual and imagined movements. Changes in these rhythms provide a mechanism to select relevant neuronal populations, although the relative contributions of these rhythms remain unclear. Here we use MEG to investigate changes in oscillatory power while healthy human participants imagined grasping a cylinder oriented at different angles. This paradigm allowed us to study the neural signals involved in the simulation of a movement in the absence of signals related to motor execution and sensory reafference. Movement selection demands were manipulated by exploiting the fact that some object orientations evoke consistent grasping movements, whereas others are compatible with both overhand and underhand grasping. By modulating task demands, we show a functional dissociation of the alpha- and beta-band rhythms. As movement selection demands increased, alpha-band oscillatory power increased in the sensorimotor cortex ipsilateral to the arm used for imagery, whereas beta-band power concurrently decreased in the contralateral sensorimotor cortex. The same pattern emerged when motor imagery trials were compared with a control condition, providing converging evidence for the functional dissociation of the two rhythms. These observations call for a re-evaluation of the role of sensorimotor rhythms. We propose that neural oscillations in the alpha-band mediate the allocation of computational resources by disengaging task-irrelevant cortical regions. In contrast, the reduction of neural oscillations in the beta-band is directly related to the disinhibition of neuronal populations involved in the computations of movement parameters.

A direct brain-to-brain interface in humans.

Abstract: We describe the first direct brain-to-brain interface in humans and present results from experiments involving six different subjects. Our non-invasive interface, demonstrated originally in August 2013, combines electroencephalography (EEG) for recording brain signals with transcranial magnetic stimulation (TMS) for delivering information to the brain. We illustrate our method using a visuomotor task in which two humans must cooperate through direct brain-to-brain communication to achieve a desired goal in a computer game. The brain-to-brain interface detects motor imagery in EEG signals recorded from one subject (the “sender”) and transmits this information over the internet to the motor cortex region of a second subject (the “receiver”). This allows the sender to cause a desired motor response in the receiver (a press on a touchpad) via TMS. We quantify the performance of the brain-to-brain interface in terms of the amount of information transmitted as well as the accuracies attained in (1) decoding the sender’s signals, (2) generating a motor response from the receiver upon stimulation, and (3) achieving the overall goal in the cooperative visuomotor task. Our results provide evidence for a rudimentary form of direct information transmission from one human brain to another using non-invasive means.

Mental representation and mental practice: experimental investigation on the functional links between motor memory and motor imagery.

Abstract: Recent research on mental representation of complex action has revealed distinct differences in the structure of representational frameworks between experts and novices. More recently, research on the development of mental representation structure has elicited functional changes in novices' representations as a result of practice. However, research investigating if and how mental practice adds to this adaptation process is lacking. In the present study, we examined the influence of mental practice (i.e., motor imagery rehearsal) on both putting performance and the development of one's representation of the golf putt during early skill acquisition. Novice golfers (N = 52) practiced the task of golf putting under one of four different practice conditions: mental, physical, mental-physical combined, and no practice. Participants were tested prior to and after a practice phase, as well as after a three day retention interval. Mental representation structures of the putt were measured, using the structural dimensional analysis of mental representation. This method provides psychometric data on the distances and groupings of basic action concepts in long-term memory. Additionally, putting accuracy and putting consistency were measured using two-dimensional error scores of each putt. Findings revealed significant performance improvements over the course of practice together with functional adaptations in mental representation structure. Interestingly, after three days of practice, the mental representations of participants who incorporated mental practice into their practice regime displayed representation structures that were more similar to a functional structure than did participants who did not incorporate mental practice. The findings of the present study suggest that mental practice promotes the cognitive adaptation process during motor learning, leading to more elaborate representations than physical practice only.

Experts bodies, experts minds: How physical and mental training shape the brain

Abstract: Skill learning is the improvement in perceptual, cognitive, or motor performance following practice. Expert performance levels can be achieved with well-organized knowledge, using sophisticated and specific mental representations and cognitive processing, applying automatic sequences quickly and efficiently, being able to deal with large amounts of information, and many other challenging task demands and situations that otherwise paralyze the performance of novices. The neural reorganizations that occur with expertise reflect the optimization of the neurocognitive resources to deal with the complex computational load needed to achieve peak performance. As such, capitalizing on neuronal plasticity, brain modifications take place over time-practice and during the consolidation process. One major challenge is to investigate the neural substrates and cognitive mechanisms engaged in expertise, and to define “expertise” from its neural and cognitive underpinnings. Recent insights showed that many brain structures are recruited during task performance, but only activity in regions related to domain-specific knowledge distinguishes experts from novices. The present review focuses on three expertise domains placed across a motor to mental gradient of skill learning: sequential motor skill, mental simulation of the movement (motor imagery), and meditation as a paradigmatic example of “pure” mental training. We first describe results on each specific domain from the initial skill acquisition to the achieving of expert performance, including recent results on the corresponding underlying neural mechanisms. We then discuss differences and similarities between these domains with the aim to identify the highlights of the neurocognitive processes underpinning expertise, and conclude with suggestions for future research.

The Neural Basis of Age-Related Changes in Motor Imagery of Gait: An fMRI Study

Abstract: BACKGROUND: Aging is often associated with modifications of gait. Recent studies have revealed a strong relationship between gait and executive functions in healthy and pathological aging. We hypothesized that modification of gait due to aging may be related to changes in frontal lobe function. METHODS: Fourteen younger (27.0±3.6 years) and 14 older healthy adults (66.0±3.5 years) performed a motor imagery task of gait as well as a matched visual imagery task. Task difficulty was modulated to investigate differential activation for precise control of gait. Task performance was assessed by recording motor imagery latencies, eye movements, and electromyography during functional magnetic resonance imaging scanning. RESULTS: Our results showed that both healthy older and young adults recruited a network of brain regions comprising the bilateral supplementary motor cortex and primary motor cortex, right prefrontal cortex, and cerebellum, during motor imagery of gait. We observed an age-related increase in brain activity in the right supplementary motor area (BA6), the right orbitofrontal cortex (BA11), and the left dorsolateral frontal cortex (BA10). Activity in the left hippocampus was significantly modulated by task difficulty in the elderly participants. Executive functioning correlated with magnitude of increases in right primary motor cortex (BA4) during the motor imagery task. CONCLUSIONS: Besides demonstrating a general overlap in brain regions recruited in young and older participants, this study shows age-related changes in cerebral activation during mental imagery of gait. Our results underscore the importance of executive function (dorsolateral frontal cortex) and spatial navigation or memory function (hippocampus) in gait control in elderly individuals. Language: en

Impact of neurologic deficits on motor imagery: a systematic review of clinical evaluations.

Abstract: Motor imagery (MI, the mental representation of an action without engaging in its actual execution) is a therapeutically relevant technique to promote motor recovery after neurologic disorders. MI shares common neural and psychological bases with physical practice. Interestingly, both acute and progressive neurologic disorders impact brain motor networks, hence potentially eliciting changes in MI capacities. How experimental neuroscientists and medical practitioners should assess and take into account these changes in order to design fruitful interventions is largely unresolved. Understanding how the psychometric, behavioral and neurophysiological correlates of MI are impacted by neurologic disorders is required. To address this brain-behavior issue, we conducted a systematic review of MI data in stroke, Parkinson’s disease, spinal cord injury, and amputee participants. MI evaluation methods are presented. Redundant MI profiles, primarily based on psychometric and behavioral evaluations, emerged in each clinical population. When present, changes in the psychometric and behavioral correlates of MI were highly congruent with the corresponding motor impairments. Neurophysiological recordings yielded specific changes in cerebral activations during MI, which mirrored structural and functional reorganizations due to neuroplasticity. In this view, MI capacities may not be deteriorated per se by neurologic diseases resulting in chronic motor incapacities, but adjusted to the current state of the motor system. Literature-driven orientations for future clinical research are provided.

Classification of four-class motor imagery employing single-channel electroencephalography.

Abstract: With advances in brain-computer interface (BCI) research, a portable few- or single-channel BCI system has become necessary. Most recent BCI studies have demonstrated that the common spatial pattern (CSP) algorithm is a powerful tool in extracting features for multiple-class motor imagery. However, since the CSP algorithm requires multi-channel information, it is not suitable for a few- or single-channel system. In this study, we applied a short-time Fourier transform to decompose a single-channel electroencephalography signal into the time-frequency domain and construct multi-channel information. Using the reconstructed data, the CSP was combined with a support vector machine to obtain high classification accuracies from channels of both the sensorimotor and forehead areas. These results suggest that motor imagery can be detected with a single channel not only from the traditional sensorimotor area but also from the forehead area.

The influence of individual motor imagery ability on cerebral recruitment during gait imagery.

Abstract: r r Abstract: Motor imagery (MI) is often used in combination with neuroimaging techniques to study the cog- nitive control of gait. However, imagery ability (IA) varies widely across individuals, potentially influencing the pattern of cerebral recruitment during MI. The aim of the current study was to investigate this effect of IA on the neural correlates of gait control using functional magnetic resonance imaging (fMRI). Twenty healthy young subjects were subdivided into a good and bad imagers group, on the basis of their perform- ance on two mental chronometry tests. For the whole group, MI activated a bilateral network of areas highly consistent with previous studies, encompassing primary motor cortex (BA 4), supplementary motor area, and other frontal and parietal areas, anterior insula, and cerebellum. Compared to bad imagers, good imagers showed higher activation in the right BA 4, left prefrontal cortex (BA 10), right thalamus, and bilat- eral cerebellum. Good imagers thus appear better able to recruit motor areas during MI, but also activate a prefrontal executive area (BA 10), which integrates information from the body and the environment and participates in higher-order gait control. These differences were found even though the two groups did not differ in other imagery abilities according to a standard questionnaire for vividness of motor and visual im- agery. Future studies on MI should take into account these effects, and control for IA when comparing dif- ferent populations, using appropriate measures. A better understanding of the neural mechanisms that underlie MI ability is crucial to accurately evaluate locomotor skills in clinical measures and neurorehabilita- tion techniques. Hum Brain Mapp 00:000-000, 2012. V C 2012 Wiley-Periodicals, Inc.

Training the Motor Cortex by Observing the Actions of Others During Immobilization

Abstract: Limb immobilization and nonuse are well-known causes of corticomotor depression. While physical training can drive the recovery from nonuse-dependent corticomotor effects, it remains unclear if it is possible to gain access to motor cortex in alternative ways, such as through motor imagery (MI) or action observation (AO). Transcranial magnetic stimulation was used to study the excitability of the hand left motor cortex in normal subjects immediately before and after 10 h of right arm immobilization. During immobilization, subjects were requested either to imagine to act with their constrained limb or to observe hand actions performed by other individuals. A third group of control subjects watched a nature documentary presented on a computer screen. Hand corticomotor maps and recruitment curves reliably showed that AO, but not MI, prevented the corticomotor depression induced by immobilization. Our results demonstrate the existence of a visuomotor mechanism in humans that links AO and execution which is able to effect cortical plasticity in a beneficial way. This facilitation was not related to the action simulation, because it was not induced by explicit MI.

Modulation of event-related desynchronization during kinematic and kinetic hand movements

Abstract: Event-related desynchronization/synchronization (ERD/ERS) is a relative power decrease/increase of electroencephalogram (EEG) in a specific frequency band during physical motor execution and mental motor imagery, thus it is widely used for the brain-computer interface (BCI) purpose. However what the ERD really reflects and its frequency band specific role have not been agreed and are under investigation. Understanding the underlying mechanism which causes a significant ERD would be crucial to improve the reliability of the ERD-based BCI. We systematically investigated the relationship between conditions of actual repetitive hand movements and resulting ERD. Eleven healthy young participants were asked to close/open their right hand repetitively at three different speeds (Hold, 1/3 Hz, and 1 Hz) and four distinct motor loads (0, 2, 10, and 15 kgf). In each condition, participants repeated 20 experimental trials, each of which consisted of rest (8–10 s), preparation (1 s) and task (6 s) periods. Under the Hold condition, participants were instructed to keep clenching their hand (i.e., isometric contraction) during the task period. Throughout the experiment, EEG signals were recorded from left and right motor areas for offline data analysis. We obtained time courses of EEG power spectrum to discuss the modulation of mu and beta-ERD/ERS due to the task conditions. We confirmed salient mu-ERD (8–13 Hz) and slightly weak beta-ERD (14–30 Hz) on both hemispheres during repetitive hand grasping movements. According to a 3 × 4 ANOVA (speed × motor load), both mu and beta-ERD during the task period were significantly weakened under the Hold condition, whereas no significant difference in the kinetics levels and interaction effect was observed. This study investigates the effect of changes in kinematics and kinetics on resulting ERD during repetitive hand grasping movements. The experimental results suggest that the strength of ERD may reflect the time differentiation of hand postures in motor planning process or the variation of proprioception resulting from hand movements, rather than the motor command generated in the down stream, which recruits a group of motor neurons.

Evaluation of various mental task combinations for near-infrared spectroscopy-based brain-computer interfaces

Abstract: A number of recent studies have demonstrated that near-infrared spectroscopy (NIRS) is a promising neuroimaging modality for brain-computer interfaces (BCIs). So far, most NIRS-based BCI studies have focused on enhancing the accuracy of the classification of different mental tasks. In the present study, we evaluated the performances of a variety of mental task combinations in order to determine the mental task pairs that are best suited for customized NIRS-based BCIs. To this end, we recorded event-related hemodynamic responses while seven participants performed eight different mental tasks. Classification accuracies were then estimated for all possible pairs of the eight mental tasks ( 8 C 2 ¼ 28). Based on this analysis, mental task combinations with rel- atively high classification accuracies frequently included the following three mental tasks: "mental multiplication," "mental rotation," and "right-hand motor imagery." Specifically, mental task combinations consisting of two of these three mental tasks showed the highest mean classification accuracies. It is expected that our results will be a useful reference to reduce the time needed for preliminary tests when discovering individual-specific mental task combinations. © 2014 Society of Photo-Optical Instrumentation Engineers (SPIE) (DOI: 10.1117/1.JBO.19.7.077005)

Neurophysiological substrates of stroke patients with motor imagery-based brain-computer interface training

Abstract: We investigated the efficacy of motor imagery-based Brain Computer Interface (MI-based BCI) training for eight stroke patients with severe upper extremity paralysis using longitudinal clinical assessments. The results were compared with those of a control group (n = 7) that only received FES (Functional Electrical Stimulation) treatment besides conventional therapies. During rehabilitation training, changes in the motor function of the upper extremity and in the neurophysiologic electroencephalographic (EEG) were observed for two groups. After 8 weeks of training, a significant improvement in the motor function of the upper extremity for the BCI group was confirmed (p < 0.05 for ARAT), simultaneously with the activation of bilateral cerebral hemispheres. Additionally, event-related desynchronization (ERD) of the affected sensorimotor cortexes (SMCs) was significantly enhanced when compared to the pretraining course, which was only observed in the BCI group (p < 0.05). Furthermore, the activation of affect...

Combining Motor Imagery With Selective Sensation Toward a Hybrid-Modality BCI

Abstract: A hybrid modality brain-computer interface (BCI) is proposed in this paper, which combines motor imagery with selective sensation to enhance the discrimination between left and right mental tasks, e.g., the classification between left/ right stimulation sensation and right/ left motor imagery. In this paradigm, wearable vibrotactile rings are used to stimulate both the skin on both wrists. Subjects are required to perform the mental tasks according to the randomly presented cues (i.e., left hand motor imagery, right hand motor imagery, left stimulation sensation or right stimulation sensation). Two-way ANOVA statistical analysis showed a significant group effect (F (2,20) = 7.17, p = 0.0045), and the Benferroni-corrected multiple comparison test (with α = 0.05) showed that the hybrid modality group is 11.13% higher on average than the motor imagery group, and 10.45% higher than the selective sensation group. The hybrid modality experiment exhibits potentially wider spread usage within ten subjects crossed 70% accuracy, followed by four subjects in motor imagery and five subjects in selective sensation. Six subjects showed statistically significant improvement ( Benferroni-corrected) in hybrid modality in comparison with both motor imagery and selective sensation. Furthermore, among subjects having difficulties in both motor imagery and selective sensation, the hybrid modality improves their performance to 90% accuracy. The proposed hybrid modality BCI has demonstrated clear benefits for those poorly performing BCI users. Not only does the requirement of motor and sensory anticipation in this hybrid modality provide basic function of BCI for communication and control, it also has the potential for enhancing the rehabilitation during motor recovery.

Is Motor-Imagery Brain-Computer Interface Feasible in Stroke Rehabilitation?

Abstract: In the past 3 decades, interest has increased in brain-computer interface (BCI) technology as a tool for assisting, augmenting, and rehabilitating sensorimotor functions in clinical populations Initially designed as an assistive device for partial or total body impairments, BCI systems have since been explored as a possible adjuvant therapy in the rehabilitation of patients who have had a stroke In particular, BCI systems incorporating a robotic manipulanda to passively manipulate affected limbs have been studied These systems can use a range of invasive (ie, intracranial implanted electrodes) or noninvasive neurophysiologic recording techniques (ie, electroencephalography [EEG], near-infrared spectroscopy, and magnetoencephalography) to establish communication links between the brain and the BCI system Trials are most commonly performed on EEG-based BCI in comparison with the other techniques because of its high temporal resolution, relatively low setup costs, portability, and noninvasive nature EEG-based BCI detects event-related desynchronization/synchronization in sensorimotor oscillatory rhythms associated with motor imagery (MI), which in turn drives the BCI Previous evidence suggests that the process of MI preferentially activates sensorimotor regions similar to actual task performance and that repeated practice of MI can induce plasticity changes in the brain It is therefore postulated that the combination of MI and BCI may augment rehabilitation gains in patients who have had a stroke by activating corticomotor networks via MI and providing sensory feedback from the affected limb using end-effector robots In this review we examine the current literature surrounding the feasibility of EEG-based MI-BCI systems in stroke rehabilitation We also discuss the limitations of using EEG-based MI-BCI in patients who have had a stroke and suggest possible solutions to overcome these limitations

Motor imagery, P300 and error-related EEG-based robot arm movement control for rehabilitation purpose.

Abstract: The paper proposes a novel approach toward EEG-driven position control of a robot arm by utilizing motor imagery, P300 and error-related potentials (ErRP) to align the robot arm with desired target position. In the proposed scheme, the users generate motor imagery signals to control the motion of the robot arm. The P300 waveforms are detected when the user intends to stop the motion of the robot on reaching the goal position. The error potentials are employed as feedback response by the user. On detection of error the control system performs the necessary corrections on the robot arm. Here, an AdaBoost-Support Vector Machine (SVM) classifier is used to decode the 4-class motor imagery and an SVM is used to decode the presence of P300 and ErRP waveforms. The average steady-state error, peak overshoot and settling time obtained for our proposed approach is 0.045, 2.8 % and 44 s, respectively, and the average rate of reaching the target is 95 %. The results obtained for the proposed control scheme make it suitable for designs of prosthetics in rehabilitative applications.

Mental representation and motor imagery training.

Abstract: Research in sports, dance and rehabilitation has shown that basic action concepts (BACs) are fundamental building blocks of mental action representations. BACs are based on chunked body postures related to common functions for realizing action goals. In this paper, we outline issues in research methodology and an experimental method, the structural dimensional analysis of mental representation (SDA-M), to assess action-relevant representational structures that reflect the organization of BACs. The SDA-M reveals a strong relationship between cognitive representation and performance if complex actions are performed. We show how the SDA-M can improve motor imagery training and how it contributes to our understanding of coaching processes. The SDA-M capitalizes on the objective measurement of individual mental movement representations before training and the integration of these results into the motor imagery training. Such motor imagery training based on mental representations (MTMR) has been applied successfully in professional sports such as golf, volleyball, gymnastics, windsurfing, and recently in the rehabilitation of patients who have suffered a stroke.

Motor Imagery for Severely Motor-Impaired Patients: Evidence for Brain-Computer Interfacing as Superior Control Solution

Abstract: Brain-Computer Interfaces (BCIs) strive to decode brain signals into control commands for severely handicapped people with no means of muscular control. These potential users of noninvasive BCIs display a large range of physical and mental conditions. Prior studies have shown the general applicability of BCI with patients, with the conflict of either using many training sessions or studying only moderately restricted patients. We present a BCI system designed to establish external control for severely motor-impaired patients within a very short time. Within only six experimental sessions, three out of four patients were able to gain significant control over the BCI, which was based on motor imagery or attempted execution. For the most affected patient, we found evidence that the BCI could outperform the best assistive technology (AT) of the patient in terms of control accuracy, reaction time and information transfer rate. We credit this success to the applied user-centered design approach and to a highly flexible technical setup. State-of-the art machine learning methods allowed the exploitation and combination of multiple relevant features contained in the EEG, which rapidly enabled the patients to gain substantial BCI control. Thus, we could show the feasibility of a flexible and tailorable BCI application in severely disabled users. This can be considered a significant success for two reasons: Firstly, the results were obtained within a short period of time, matching the tight clinical requirements. Secondly, the participating patients showed, compared to most other studies, very severe communication deficits. They were dependent on everyday use of AT and two patients were in a locked-in state. For the most affected patient a reliable communication was rarely possible with existing AT.

Multiple tasks and neuroimaging modalities increase the likelihood of detecting covert awareness in patients with disorders of consciousness

Abstract: Minimal or inconsistent behavioural responses to command make it challenging to accurately diagnose the level of awareness of a patient with a Disorder of Consciousness (DOC). By identifying markers of mental imagery being covertly performed to command, functional neuroimaging (fMRI, EEG) has shown that some of these patients are aware despite their lack of behavioural responsiveness. We report the findings of behavioural, fMRI, and EEG approaches to detecting command-following in a group of patients with DOC. From an initial sample of 14 patients, complete data across all tasks was obtained in six cases. Behavioural evaluations were performed with the Coma Recovery Scale - Revised. Both fMRI and EEG evaluations involved the completion of previously validated mental imagery tasks - i.e., motor imagery (EEG and fMRI) and spatial navigation imagery (fMRI). One patient exhibited statistically significant evidence of motor imagery in both the fMRI and EEG tasks, despite being unable to follow commands behaviourally. Two behaviourally non-responsive patients produced appropriate activation during the spatial navigation fMRI task. However, neither of these patients successfully completed the motor imagery tasks, likely due to specific motor area damage in at least one of these cases. A further patient demonstrated command following only in the EEG motor imagery task, and two patients did not demonstrate command following in any of the behavioural, EEG, or fMRI assessments. Due to the heterogeneity of aetiology and pathology in this group, DOC patients vary in terms of their suitability for some forms of neuroimaging, the preservation of specific neural structures, and the cognitive resources that may be available to them. Assessments of a range of cognitive abilities supported by spatially-distinct brain regions and indexed by multiple neural signatures are therefore required in order to accurately characterise a patient’s level of residual cognition and awareness.

Meta-analysis on the effect of mental imagery on motor recovery of the hemiplegic upper extremity function

Abstract: Background/aim Studies have shown that mental imagery can enhance relearning and generalisation of function after stroke. The aim of this meta-analysis was to evaluate evidence on the effects of mental imagery on motor recovery of the hemiplegic upper extremities after stroke. Methods A comprehensive data base search of the literature up to December 2012 was performed using PubMed, EBSCO host (Academic Search Premier, CINAHL and Educational Resource Information Center), PsycINFO, Medline, and ISI Web of Knowledge (Science Citation Index and Social Sciences Citation Index). Randomised clinical trials or controlled clinical trials that included mental imagery for improving upper extremity motor function for stroke patients were located. Relevant articles were critically reviewed and methodological quality was evaluated using the PEDro Scale, and study results synthesised. Results Five randomised clinical trials and one controlled clinical trial met the inclusion criteria. Five of the six studies yielded positive findings in favour of mental imagery. Quantitative analysis showed a significant difference in the Action Research Arm Test (overall effect: Z = 6.75; P << 0.001). Conclusion Review of the literature revealed a trend in support of the use of motor imagery for upper extremity motor rehabilitation after stroke. Mental imagery could be a viable intervention for stroke patients given its benefits of being safe, cost-effective and rendering multiple and unlimited practice opportunities. It is recommended that researchers incorporate imaging techniques into clinical studies so that the mechanism whereby mental imagery mediates motor recovery or neural adaptation for people with stroke can be better understood.

Combined EEG-fNIRS Decoding of Motor Attempt and Imagery for Brain Switch Control: An Offline Study in Patients With Tetraplegia

Abstract: Combining electrophysiological and hemodynamic features is a novel approach for improving current performance of brain switches based on sensorimotor rhythms (SMR). This study was conducted with a dual purpose: to test the feasibility of using a combined electroencephalogram/functional near-infrared spectroscopy (EEG-fNIRS) SMR-based brain switch in patients with tetraplegia, and to examine the performance difference between motor imagery and motor attempt for this user group. A general improvement was found when using both EEG and fNIRS features for classification as compared to using the single-modality EEG classifier, with average classification rates of 79% for attempted movement and 70% for imagined movement. For the control group, rates of 87% and 79% were obtained, respectively, where the “attempted movement” condition was replaced with “actual movement.” A combined EEG-fNIRS system might be especially beneficial for users who lack sufficient control of current EEG-based brain switches. The average classification performance in the patient group for attempted movement was significantly higher than for imagined movement using the EEG-only as well as the combined classifier, arguing for the case of a paradigm shift in current brain switch research.

Augmented Complex Common Spatial Patterns for Classification of Noncircular EEG From Motor Imagery Tasks

Abstract: A novel augmented complex-valued common spatial pattern (CSP) algorithm is introduced in order to cater for general complex signals with noncircular probability distributions. This is a typical case in multichannel electroencephalogram (EEG), due to the power difference or correlation between the data channels, yet current methods only cater for a very restrictive class of circular data. The proposed complex-valued CSP algorithms account for the generality of complex noncircular data, by virtue of the use of augmented complex statistics and the strong-uncorrelating transform (SUT). Depending on the degree of power difference of complex signals, the analysis and simulations show that the SUT based algorithm maximizes the inter-class difference between two motor imagery tasks. Simulations on both synthetic noncircular sources and motor imagery experiments using real-world EEG support the approach.

Effect of biased feedback on motor imagery learning in BCI-teleoperation system.

Abstract: Feedback design is an important issue in motor imagery BCI systems. Regardless, to date it has not been reported how feedback presentation can optimize co-adaptation between a human brain and such systems. This paper assesses the effect of realistic visual feedback on users’ BC performance and motor imagery skills. We previously developed a tele-operation system for a pair of humanlike robotic hands and showed that BCI control of such hands along with first-person perspective visual feedback of movements can arouse a sense of embodiment in the operators. In the first stage of this study, we found that the intensity of this ownership illusion was associated with feedback presentation and subjects’ performance during BCI motion control. In the second stage, we probed the effect of positive and negative feedback bias on subjects’ BCI performance and motor imagery skills. Although the subject specific classifier, which was set up at the beginning of experiment, detected no significant change in the subjects’ online performance, evaluation of brain activity patterns revealed that subjects’ self-regulation of motor imagery features improved due to a positive bias of feedback and a possible occurrence of ownership illusion. Our findings suggest that in general training protocols for BCIs, manipulation of feedback can play an important role in the optimization of subjects’ motor imagery skills.

Motor imagery during action observation modulates automatic imitation effects in rhythmical actions.

Abstract: We have previously shown that passively observing a task-irrelevant rhythmical action can bias the cycle time of a subsequently executed rhythmical action. Here we use the same paradigm to investigate the impact of different forms of motor imagery (MI) during action observation (AO) on this automatic imitation (AI) effect. Participants saw a picture of the instructed action followed by a rhythmical distractor movie, wherein cycle time was subtly manipulated across trials. They then executed the instructed rhythmical action. When participants imagined performing the instructed action in synchrony with the distractor action (AO + MI), a strong imitation bias was found that was significantly greater than in our previous study. The bias was pronounced equally for compatible and incompatible trials, wherein observed and imagined actions were different in type (e.g., face washing vs. painting) or plane of movement, or both. In contrast, no imitation bias was observed when MI conflicted with AO. In Experiment 2, motor execution synchronized with AO produced a stronger imitation bias compared to AO + MI, showing an advantage in synchronization for overt execution over MI. Furthermore, the bias was stronger when participants synchronized the instructed action with the distractor movie, compared to when they synchronized the distractor action with the distractor movie. Although we still observed a significant bias in the latter condition, this finding indicates a degree of specificity in AI effects for the identity of the synchronized action. Overall, our data show that MI can substantially modulate the effects of AO on subsequent execution, wherein: (1) combined AO + MI can enhance AI effects relative to passive AO; (2) observed and imagined actions can be flexibly coordinated across different action types and planes; and (3) conflicting AO + MI can abolish AI effects. Therefore, combined AO + MI instructions should be considered in motor training and rehabilitation.