Imagery of Voluntary Movement of Fingers, Toes, and Tongue Activates Corresponding Body-Part-Specific Motor Representations

Time-resolved estimation of strength of motor imagery representation by multivariate EEG decoding

Objective. Multivariate decoding enables access to information encoded in multiple brain activity features with high temporal resolution. However, whether the strength, of which this information is represented in the brain, can be extracted across time within single trials remains largely unexplored.Approach.In this study, we addressed this question by applying a support vector machine (SVM) to extract motor imagery (MI) representations, from electroencephalogram (EEG) data, and by performing time-resolved single-trial analyses of the multivariate decoding. EEG was recorded from a group of healthy participants during MI of opening and closing of the same hand.Main results.Cross-temporal decoding revealed both dynamic and stationary MI-relevant features during the task. Specifically, features representing MI evolved dynamically early in the trial and later stabilized into a stationary network of MI features. Using a hierarchical genetic algorithm for selection of MI-relevant features, we identified primarily contralateral alpha and beta frequency features over the sensorimotor and parieto-occipital cortices as stationary which extended into a bilateral pattern in the later part of the trial. During the stationary encoding of MI, by extracting the SVM prediction scores, we analyzed MI-relevant EEG activity patterns with respect to the temporal dynamics within single trials. We show that the SVM prediction score correlates to the amplitude of univariate MI-relevant features (as documented from an extensive repertoire of previous MI studies) within single trials, strongly suggesting that these are functional variations of MI strength hidden in trial averages.Significance.Our work demonstrates a powerful approach for estimating MI strength continually within single trials, having far-reaching impact for single-trial analyses. In terms of MI neurofeedback for motor rehabilitation, these results set the ground for more refined neurofeedback reflecting the strength of MI that can be provided to patients continually in time.

A Study on the Effect of Mental Practice Using Motor Evoked Potential-Based Neurofeedback

This study aimed to investigate whether the effect of mental practice (motor imagery training) can be enhanced by providing neurofeedback based on transcranial magnetic stimulation (TMS)-induced motor evoked potentials (MEP). Twenty-four healthy, right-handed subjects were enrolled in this study. The subjects were randomly allocated into two groups: a group that was given correct TMS feedback (Real-FB group) and a group that was given randomized false TMS feedback (Sham-FB group). The subjects imagined pushing the switch with just timing, when the target circle overlapped a cross at the center of the computer monitor. In the Real-FB group, feedback was provided to the subjects based on the MEP amplitude measured in the trial immediately preceding motor imagery. In contrast, the subjects of the Sham-FB group were provided with a feedback value that was independent of the MEP amplitude. TMS was applied when the target, moving from right to left, overlapped the cross at the center of the screen, and the MEP amplitude was measured. The MEP was recorded in the right first dorsal interosseous muscle. We evaluated the pre-mental practice and post-mental practice motor performance in both groups. As a result, a significant difference was observed in the percentage change of error values between the Real-FB group and the Sham-FB group. Furthermore, the MEP was significantly different between the groups in the 4th and 5th sets. Therefore, it was suggested that TMS-induced MEP-based neurofeedback might enhance the effect of mental practice.

The Effect of Virtual Reality Technology on the Imagery Skills and Performance of Target-Based Sports Athletes

The aim of this study is the examination of the effect of virtual reality based imagery (VRBI) training programs on the shot performance and imagery skills of athletes and, and to conduct a comparison with Visual Motor Behavior Rehearsal and Video Modeling (VMBR + VM). In the research, mixed research method and sequential explanatory design were used. In the quantitative dimension of the study the semi-experimental model was used, and in the qualitative dimension the case study design was adopted. The research participants were selected from athletes who were involved in our target sports: curling (n = 14), bowling (n = 13), and archery (n = 7). All participants were randomly assigned to VMBR + VM (n = 11), VRBI (n = 12), and Control (n = 11) groups through the "Research Randomizer" program. The quantitative data of the study was: the weekly shot performance scores of the athletes and the data obtained from the "Movement Imagery Questionnaire-Revised." The qualitative data was obtained from the data collected from the semi-structured interview guide, which was developed by researchers and field experts. According to the results obtained from the study, there were statistically significant differences between the groups in terms of shot performance and imagery skills. VRBI training athletes showed more improvement in the 4-week period than the athletes in the VMBR + VM group, in terms of both shot performance and imagery skills. In addition, the VRBI group adapted to the imagery training earlier than the VMBR + VM group. As a result, it was seen that they showed faster development in shot performances. From these findings, it can be said that VRBI program is more efficient in terms of shot performance and imagery skills than VMBR + VM, which is the most used imaging training model.

The changes in spinal reciprocal inhibition during motor imagery in lower extremity

Motor imagery (MI) is known to improve motor function through enhancement of motor cortex activity. Spinal reciprocal inhibition (RI) is modulated by motor cortex activity, and, therefore, MI may change RI. The aim of this study was to examine the changes in RI during MI involving the lower extremity. Spinal RI was measured from the tibialis anterior (TA) to the soleus (SOL). Eleven healthy adults participated in experiment 1. All participants performed the following three conditions, and RI was assessed during each condition: (1) resting condition; (2) MI of ankle dorsiflexion condition (MI-DF); and (3) MI of ankle plantarflexion condition (MI-PF). Twelve healthy adults participated in experiment 2. All participants performed the following two conditions, and RI was assessed before and after MI practice for 10 min: (1) resting condition and (2) MI-DF. The interval between the conditioning and test stimulus (inter-stimulus interval; ISI) was set at 0, 1, 2, or 3 ms and 20 ms. In experiment 1, RI during MI-PF was significantly decreased compared with that during resting with both stimulus intervals. RI during MI-DF showed no significant change compared with that during resting with both ISIs. In experiment 2, the difference between the rest condition and the MI-DF condition after the MI task with ISI of 20 ms was significantly higher than before the MI task. Our findings suggest that real-time changes in RI during MI involving the lower extremity may vary depending on the direction of motion and MI practice.

Multiscale space-time-frequency feature-guided multitask learning CNN for motor imagery EEG classification

OBJECTIVE

Motor imagery (MI) electroencephalography (EEG) classification is regarded as a promising technology for brain--computer interface (BCI) systems, which help people to communicate with the outside world using neural activities. However, decoding human intent accurately is a challenging task because of its small signal-to-noise ratio and non-stationary characteristics. Methods that directly extract features from raw EEG signals ignores key frequency domain information. One of the challenges in MI classification tasks is finding a way to supplement the frequency domain information ignored by the raw EEG signal.

APPROACH

In this study, we fuse different models using their complementary characteristics to develop a multiscale space-time-frequency feature-guided multitask learning convolutional neural network (CNN) architecture. The proposed method consists of four modules: the space-time feature-based representation module, time-frequency feature-based representation module, multimodal fused feature-guided generation module, and classification module. The proposed framework is based on multitask learning. The four modules are trained using three tasks simultaneously and jointly optimised.

RESULTS

The proposed method is evaluated using three public challenge datasets. Through quantitative analysis, we demonstrate that our proposed method outperforms most state-of-the-art machine learning and deep learning techniques for EEG classification, thereby demonstrating the robustness and effectiveness of our method. Moreover, the proposed method is employed to realize control of robot based on EEG signal, verifying its feasibility in real-time applications.

SIGNIFICANCE

To the best of our knowledge, a deep CNN architecture that fuses different input cases, which have complementary characteristics, has not been applied to BCI tasks. Because of the interaction of the three tasks in the multitask learning architecture, our method can improve the generalisation and accuracy of subject-dependent and subject-independent methods with limited annotated data.

Parallel Spatial-Temporal Self-Attention CNN-Based Motor Imagery Classification for BCI

Motor imagery (MI) electroencephalography (EEG) classification is an important part of the brain-computer interface (BCI), allowing people with mobility problems to communicate with the outside world via assistive devices. However, EEG decoding is a challenging task because of its complexity, dynamic nature, and low signal-to-noise ratio. Designing an end-to-end framework that fully extracts the high-level features of EEG signals remains a challenge. In this study, we present a parallel spatial–temporal self-attention-based convolutional neural network for four-class MI EEG signal classification. This study is the first to define a new spatial-temporal representation of raw EEG signals that uses the self-attention mechanism to extract distinguishable spatial–temporal features. Specifically, we use the spatial self-attention module to capture the spatial dependencies between the channels of MI EEG signals. This module updates each channel by aggregating features over all channels with a weighted summation, thus improving the classification accuracy and eliminating the artifacts caused by manual channel selection. Furthermore, the temporal self-attention module encodes the global temporal information into features for each sampling time step, so that the high-level temporal features of the MI EEG signals can be extracted in the time domain. Quantitative analysis shows that our method outperforms state-of-the-art methods for intra-subject and inter-subject classification, demonstrating its robustness and effectiveness. In terms of qualitative analysis, we perform a visual inspection of the new spatial–temporal representation estimated from the learned architecture. Finally, the proposed method is employed to realize control of drones based on EEG signal, verifying its feasibility in real-time applications.

Channel Selection for Optimal EEG Measurement in Motor Imagery-Based Brain-Computer Interfaces

A method for selecting electroencephalographic (EEG) signals in motor imagery-based brain-computer interfaces (MI-BCI) is proposed for enhancing the online interoperability and portability of BCI systems, as well as user comfort. The attempt is also to reduce variability and noise of MI-BCI, which could be affected by a large number of EEG channels. The relation between selected channels and MI-BCI performance is therefore analyzed. The proposed method is able to select acquisition channels common to all subjects, while achieving a performance compatible with the use of all the channels. Results are reported with reference to a standard benchmark dataset, the BCI competition IV dataset 2a. They prove that a performance compatible with the best state-of-the-art approaches can be achieved, while adopting a significantly smaller number of channels, both in two and in four tasks classification. In particular, classification accuracy is about 77-83% in binary classification with down to 6 EEG channels, and above 60% for the four-classes case when 10 channels are employed. This gives a contribution in optimizing the EEG measurement while developing non-invasive and wearable MI-based brain-computer interfaces.

Cortical Processing of Multimodal Sensory Learning in Human Neonates

Following birth, infants must immediately process and rapidly adapt to the array of unknown sensory experiences associated with their new ex-utero environment. However, although it is known that unimodal stimuli induce activity in the corresponding primary sensory cortices of the newborn brain, it is unclear how multimodal stimuli are processed and integrated across modalities. The latter is essential for learning and understanding environmental contingencies through encoding relationships between sensory experiences; and ultimately likely subserves development of life-long skills such as speech and language. Here, for the first time, we map the intracerebral processing which underlies auditory-sensorimotor classical conditioning in a group of 13 neonates (median gestational age at birth: 38 weeks + 4 days, range: 32 weeks + 2 days to 41 weeks + 6 days; median postmenstrual age at scan: 40 weeks + 5 days, range: 38 weeks + 3 days to 42 weeks + 1 days) with blood-oxygen-level-dependent (BOLD) functional magnetic resonance imaging (MRI) and magnetic resonance (MR) compatible robotics. We demonstrate that classical conditioning can induce crossmodal changes within putative unimodal sensory cortex even in the absence of its archetypal substrate. Our results also suggest that multimodal learning is associated with network wide activity within the conditioned neural system. These findings suggest that in early life, external multimodal sensory stimulation and integration shapes activity in the developing cortex and may influence its associated functional network architecture.

Evidence for an effector-independent action system from people born without hands

What are the principles of brain organization? In the motor domain, separate pathways were found for reaching and grasping actions performed by the hand. To what extent is this organization specific to the hand or based on abstract action types, regardless of which body part performs them? We tested people born without hands who perform actions with their feet. Activity in frontoparietal association motor areas showed preference for an action type (reaching or grasping), regardless of whether it was performed by the foot in people born without hands or by the hand in typically-developed controls. These findings provide evidence that some association areas are organized based on abstract functions of action types, independent of specific sensorimotor experience and parameters of specific body parts.

Many parts of the visuomotor system guide daily hand actions, like reaching for and grasping objects. Do these regions depend exclusively on the hand as a specific body part whose movement they guide, or are they organized for the reaching task per se, for any body part used as an effector? To address this question, we conducted a neuroimaging study with people born without upper limbs—individuals with dysplasia—who use the feet to act, as they and typically developed controls performed reaching and grasping actions with their dominant effector. Individuals with dysplasia have no prior experience acting with hands, allowing us to control for hand motor imagery when acting with another effector (i.e., foot). Primary sensorimotor cortices showed selectivity for the hand in controls and foot in individuals with dysplasia. Importantly, we found a preference based on action type (reaching/grasping) regardless of the effector used in the association sensorimotor cortex, in the left intraparietal sulcus and dorsal premotor cortex, as well as in the basal ganglia and anterior cerebellum. These areas also showed differential response patterns between action types for both groups. Intermediate areas along a posterior–anterior gradient in the left dorsal premotor cortex gradually transitioned from selectivity based on the body part to selectivity based on the action type. These findings indicate that some visuomotor association areas are organized based on abstract action functions independent of specific sensorimotor parameters, paralleling sensory feature-independence in visual and auditory cortices in people born blind and deaf. Together, they suggest association cortices across action and perception may support specific computations, abstracted from low-level sensorimotor elements.

Upregulating excitability of corticospinal pathways in stroke patients using TMS neurofeedback; A pilot study

Upper limb weakness following a stroke affects 80% of survivors and is a key factor in preventing their return to independence. State-of-the art approaches to rehabilitation often require that the patient can generate some activity in the paretic limb, which is not possible for many patients in the early period following stroke. Approaches that enable more patients to engage with upper limb therapy earlier are urgently needed. Motor imagery has shown promise as a potential means to maintain activity in the brain's motor network, when the patient is incapable of generating functional movement. However, as imagery is a hidden mental process, it is impossible for individuals to gauge what impact this is having upon their neural activity. Here we used a novel brain-computer interface (BCI) approach allowing patients to gain an insight into the effect of motor imagery on their brain-muscle pathways, in real-time. Seven patients 2-26 weeks post stroke were provided with neurofeedback (NF) of their corticospinal excitability measured by the size of motor evoked potentials (MEP) in response to transcranial magnetic stimulation (TMS). The aim was to train patients to use motor imagery to increase the size of MEPs, using the BCI with a computer game displaying neurofeedback. Patients training finger muscles learned to elevate MEP amplitudes above their resting baseline values for the first dorsal interosseous (FDI) and abductor digiti minimi (ADM) muscles. By day 3 for ADM and day 4 for FDI, MEP amplitudes were sustained above baseline in all three NF blocks. Here we have described the first clinical implementation of TMS NF in a population of sub-acute stroke patients. The results show that in the context of severe upper limb paralysis, patients are capable of using neurofeedback to elevate corticospinal excitability in the affected muscles. This may provide a new training modality for early intervention following stroke.

"I Dreamed of My Hands and Arms Moving Again": A Case Series Investigating the Effect of Immersive Virtual Reality on Phantom Limb Pain Alleviation

Phantom limb pain (PLP) is a type of chronic pain that follows limb amputation, brachial plexus avulsion injury, or spinal cord injury. Treating PLP is a well-known challenge. Currently, virtual reality (VR) interventions are attracting increasing attention because they show promising analgesic effects. However, most previous studies of VR interventions were conducted with a limited number of patients in a single trial. Few studies explored questions such as how multiple VR sessions might affect pain over time, or if a patient's ability to move their phantom limb may affect their PLP. Here we recruited five PLP patients to practice two motor tasks for multiple VR sessions over 6 weeks. In VR, patients “inhabit” a virtual body or avatar, and the movements of their intact limbs are mirrored in the avatar, providing them with the illusion that their limbs respond as if they were both intact and functional. We found that repetitive exposure to our VR intervention led to reduced pain and improvements in anxiety, depression, and a sense of embodiment of the virtual body. Importantly, we also found that their ability to move their phantom limbs improved as quantified by shortened motor imagery time with the impaired limb. Although the limited sample size prevents us from performing a correlational analysis, our findings suggest that providing PLP patients with sensorimotor experience for the impaired limb in VR appears to offer long-term benefits for patients and that these benefits may be related to changes in their control of the phantom limbs' movement.

Motor-Imagery Classification Using Riemannian Geometry with Median Absolute Deviation

Motor imagery (MI) from human brain signals can diagnose or aid specific physical activities for rehabilitation, recreation, device control, and technology assistance. It is a dynamic state in learning and practicing movement tracking when a person mentally imitates physical activity. Recently, it has been determined that a brain–computer interface (BCI) can support this kind of neurological rehabilitation or mental practice of action. In this context, MI data have been captured via non-invasive electroencephalogram (EEGs), and EEG-based BCIs are expected to become clinically and recreationally ground-breaking technology. However, determining a set of efficient and relevant features for the classification step was a challenge. In this paper, we specifically focus on feature extraction, feature selection, and classification strategies based on MI-EEG data. In an MI-based BCI domain, covariance metrics can play important roles in extracting discriminatory features from EEG datasets. To explore efficient and discriminatory features for the enhancement of MI classification, we introduced a median absolute deviation (MAD) strategy that calculates the average sample covariance matrices (SCMs) to select optimal accurate reference metrics in a tangent space mapping (TSM)-based MI-EEG. Furthermore, all data from SCM were projected using TSM according to the reference matrix that represents the featured vector. To increase performance, we reduced the dimensions and selected an optimum number of features using principal component analysis (PCA) along with an analysis of variance (ANOVA) that could classify MI tasks. Then, the selected features were used to develop linear discriminant analysis (LDA) training for classification. The benchmark datasets were considered for the evaluation and the results show that it provides better accuracy than more sophisticated methods.

Role of kinaesthetic motor imagery in mirror-induced visual illusion as intervention in post-stroke rehabilitation

Mirror-induced visual illusion obtained through mirror therapy is widely used to facilitate motor recovery after stroke. Activation of primary motor cortex (M1) ipsilateral to the moving limb has been reported during mirror-induced visual illusion. However, the mechanism through which the mirror illusion elicits motor execution processes without movements observed in the mirrored limb remains unclear. This study aims to review evidence based on brain imaging studies for testing the hypothesis that neural processes associated with kinaesthetic motor imagery are attributed to ipsilateral M1 activation. Four electronic databases were searched. Studies on functional brain imaging, investigating the instant effects of mirror-induced visual illusion among stroke survivors and healthy participants were included. Thirty-five studies engaging 78 stroke survivors and 396 healthy participants were reviewed. Results of functional brain scans (n = 20) indicated that half of the studies (n = 10, 50%) reported significant changes in the activation of ipsilateral M1, which mediates motor preparation and execution. Other common neural substrates included primary somatosensory cortex (45%, kinaesthesia), precuneus (40%, image generation and self-processing operations) and cerebellum (20%, motor control). Similar patterns of ipsilateral M1 activations were observed in the two groups. These neural substrates mediated the generation, maintenance, and manipulation of motor-related images, which were the key processes in kinaesthetic motor imagery. Relationships in terms of shared neural substrates and mental processes between mirror-induced visual illusion and kinaesthetic motor imagery generate new evidence on the role of the latter in mirror therapy. Future studies should investigate the imagery processes in illusion training for post-stroke patients.

Audiomotor interaction induced by mental imagery

Mental imagery can induce audiovisual integration, but whether it can induce interactions in other modalities remains uncertain. It has been demonstrated that audiomotor interaction can be generated following training, but whether such audiomotor interaction can be induced by auditory imagery training remains unknown. The present study aims at determining whether auditory mental imagery could induce a multimodal association with postural control. We examined static postural control in the presence of a frequency-modulated sound in three groups of participants, prior to and following a short period of training designed to create an association between auditory mental imagery of sounds and postural swaying. Results suggest that mental imagery impacted performance, as a significant decrease in postural control was observed in the experimental group following mental imagery training. Results of the control groups confirmed that the effect of mental imagery was not due to response bias, but to a significant multimodal interaction following training. These findings are in accordance with previous studies suggesting that mental imagery stimuli can interact with perceptual stimuli of a different sensory modality and lead to multisensory integration. The results also confirm that audiomotor interaction can be generated a mental imagery training. However, the full extent of mental imagery influence on multimodal interaction remains to be determined.

Mu rhythm separation from the mix with alpha rhythm: Principal component analyses and factor topography

BACKGROUND

EEG mu rhythm suppression is assessed in experiments on the execution, observation and imagination of movements. It is utilised for studying of actions, language, empathy in healthy individuals and preservation of sensorimotor system functions in patients with schizophrenia and autism spectrum disorders. While EEG alpha and mu rhythms are recorded in the same frequency range (8-13 Hz), their specification becomes a serious issue. THE NEW METHOD: is based on the spatial and functional characteristics of the mu wave, which are: (1) the mu rhythm is located over the sensorimotor cortex; (2) it desynchronises during movement processing and does not respond on the eyes opening. In EEG recordings, we analysed the mu rhythm under conditions with eyes opened and eyes closed (baseline), and during a motor imagery task with eyes closed. EEG recordings were processed by principal component analysis (PCA).

RESULTS

The analysis of EEG data with the proposed approach revealed the maximum spectral power of mu rhythm localised in the sensorimotor areas. During motor imagery, mu rhythm was suppressed more in frontal and central sites than in occipital sites, whereas alpha rhythm was suppressed more in parietal and occipital sites. Mu rhythm desynchronization in sensorimotor sites during motor imagery was greater than alpha rhythm desynchronization. The proposed method enabled EEG mu rhythm separation from its mix with alpha rhythm.

CONCLUSIONS

EEG mu rhythm separation with the proposed method satisfies its classical definition.

The Beneficial Influence of Combining Motor Imagery and Coach’s Feedback on Soccer Pass Accuracy in Intermediate Players

This study compared the effects of motor imagery, feedback, and feedback+imagery interventions on soccer pass performance in non-elite players (intermediate, regional level). Participants were randomly divided into Control, Feedback, Imagery, and Feedback+Imagery groups, within a pre- post- intervention design. The intervention lasted 7 weeks, and the task consisted of passing the ball to a target 20-meters away. In each intervention session, the participants performed 3 blocks of four physical trials. The participants of the Feedback and Feedback+Imagery groups received expert feedback, given by the coach, after each block and then, all the participants realized a mental task (countdown or motor imagery). Results showed that the Feedback+Imagery group had the greatest pre- to post-test improvement compared to the other groups, and highlight the beneficial effect of combining verbal feedback and motor imagery to improve soccer passing accuracy. It is suggested to coaches or physical education teachers to adapt their training by incorporating feedback and imagery.

Motor imagery enhances corticospinal transmission mediated by cervical premotoneurons in humans

Imaging movement has positive effects on the reacquisition of motor functions after damage to the central nervous system. This study shows that motor imagery facilitates oligosynaptic corticospinal excitation that is mediated via cervical premotoneurons, which may be important for motor recovery in monkeys and humans. Current findings highlight how this imagery might be a beneficial tool for movement disorders through effects on premotoneuron circuitry.

Effect of Adding Motor Imagery to Task Specific Training on Facilitation of Sit to Stand in Hemiparetic Patients

Background: Motor imagery training is a cognitive process in which an internal representation of a movement is activated in working memory. The movement is mentally rehearsed, without any physical activity. Task-specific training emphasizes the repetitive practice of skilled movement to enhance functional abilities in hemiparesis. Objectives: To investigate whether task specific training preceded by motor imagery or task specific training alone was more effective for facilitating sit to stand in patients with stroke. Methods: Thirty male patients with stroke were selected from the Cairo University Outpatient Clinic; the median age of participants was 54.5 ± 3.51 years and they were divided equally into two groups. Patients in study group A (n = 15) received motor imagery training for 15 minutes followed by task specific training for 45 minutes, as well as a selected physical therapy program 3 times per week for 6 weeks. The control group B (n = 15) received task specific training for 45 minutes, as well as a selected physical therapy program 3 times per week for 6 weeks. The Fugl-Meyer section of the lower extremity (FMA-LE), Timed up and go test (TUG), and Biodex Balance system were assessed before and after treatment. Results: The results were highly significant for all variables including FMA-LE, TUG and Biodex Balance system in favor of the study group, post treatment. (P = 0.0004, P = 0.0001 and P = 0.0001, respectively). Conclusions: Motor imagery training results in greater improvement in sit to stand ability when used in conjunction with task specific training, rather than task specific training alone.

Mental Practice Using Motor Imagery in Dysphagia Rehabilitation: A Survey of Practicing Speech-Language Pathologists

Mental practice (MP) using motor imagery is recognized as an effective clinical tool in rehabilitative medicine for improving motor performance. Preliminary data using MP in dysphagia rehabilitation are promising, though nothing is known about the current landscape among speech-language pathologists (SLPs) relating to MP implementation. This nationwide study surveys practicing SLPs about knowledge and practice patterns of using MP to gain a better understanding of the current knowledge, as well as perceived benefits and challenges in using MP. Descriptive data are reported and open-ended questions analyzed for emerging themes using inductive coding. Over half of the participants were familiar or somewhat familiar with motor imagery in the context of dysphagia rehabilitation, though only 16% of those SLPs reported using MP with a patient. Nearly 75% of respondents expressed interest in learning more about MP. Emerging themes include factors SLPs perceive to limit patient engagement, evidence-based practice concerns, and therapeutic environmental factors. More research on MP and access to training for clinicians is needed in the area of dysphagia rehabilitation to address acknowledged interest in MP.

The use of functional magnetic resonance imaging techniques in the evaluation of patients with disorders of consciousness: a case report

Purpose

The management of patients with disorders of consciousness (DOC) constitutes a challenge for clinicians.

Case report

We present the case of a 66-year-old man who developed coma with subsequent DOC after a severe traumatic brain injury. Behavioural assessment constitutes the gold standard in the evaluation of patients with DOC. In the case presented herein the neuropsychological findings were ambiguous, and the patient underwent functional magnetic resonance imaging (fMRI) to determine whether he was in a vegetative state or minimally conscious state. Three paradigms: passive, active, and resting state fMRI were used to study the brain activity in our patient.

Conclusions

fMRI provided reliable evidence of preserved minimal consciousness. The neuroimaging techniques used in our patient were vital for his further treatment.

Effects of Motor Imagery and Action Observation on Lumbo-pelvic Motor Control, Trunk Muscles Strength and Level of Perceived Fatigue: A Randomized Controlled Trial

Purpose: The aim of the study was to evaluate the effects of motor imagery (MI) and action observation (AO) combined with a motor control exercises program for the lumbopelvic region. Method: Forty-five asymptomatic individuals were randomized into three groups: MI (n = 15), AO (n = 15) or control group (CG) (n = 15). The outcome measures included lumbopelvic motor control measured with a stabilizer pressure biofeedback, trunk muscle strength using a dynamometer and the perceived fatigue using a visual analogue scale. Participants were assessed at pre-intervention, at first week of intervention (mid) and post-intervention. Results: Regarding lumbopelvic motor control, we observed significant within-group differences between pre- and the mid and post-intervention assessment in AO group (p < .001, d > 0.80). MI and CG groups showed significant differences between pre- and post-intervention assessment (p < .05, d > 0.80). Regarding the direct comparison in the ΔMid-Pre differences between groups, only the AO group was superior to the CG with a large effect size (d > 0.80). Regarding trunk muscle strength, significant within-group differences between pre- and post-intervention assessments were observed in AO (p < .001, d = -1.25) and MI (p < .05, d = -1.00) groups. In relation to the perceived fatigue, statistically significant within-group differences were found in all groups (p < .05, d > 0.60). Conclusion: AO training caused faster changes in lumbopelvic motor control compared with the CG group. The AO strategy could be used as a guideline for teaching lumbopelvic motor control exercises.

The Effect of Expertise on Kinesthetic Motor Imagery of Complex Actions

The ability to mentally simulate an action by recalling the body sensations relative to the real execution is referred to as kinesthetic motor imagery (MI). Frontal and parietal motor-related brain regions are generally engaged during MI. The present study aimed to investigate the time course and neural correlates of complex action imagery and possible effects of expertise on the underlying action representation processes. Professional ballet dancers and controls were presented with effortful and effortless ballet steps and instructed to mentally reproduce each movement during EEG recording. Time-locked MI was associated with an Anterior Negativity (AN) component (400-550 ms) that was larger in dancers relative to controls. The AN was differentially modulated by the motor content (effort) as a function of ballet expertise. It was more negative in response to effortful (than effortless) movements in control participants only. This effect also had a frontal distribution in controls and a centro-parietal distribution in dancers, as shown by the topographic maps of the scalp voltage. The source reconstruction (swLORETA) of the recorded potentials in the AN time-window showed enhanced engagement of prefrontal regions in controls (BA 10/47) relative to dancers, and occipitotemporal (BA 20) and bilateral sensorimotor areas in dancers (BA6/40) compared with controls. This evidence seems to suggest that kinesthetic MI of complex action relied on visuomotor simulation processes in participants with acquired dance expertise. Simultaneously, increased cognitive demands occurred in participants lacking in motor knowledge with the specific action. Hence, professional dance training may lead to refined action representation processes.

Brain-computer interfaces and virtual reality for neurorehabilitation

Brain-computer interfaces (BCIs) and virtual reality (VR) are two technologic advances that are changing our way of interacting with the world. BCIs can be used to influence and can serve as a control mechanism in navigation tasks, communication, or other assistive functions. VR can create ad hoc interactive scenarios that involve all our senses, stimulate the brain in a multisensory fashion, and increase the motivation and fun with game-like environments. VR and motion tracking enable natural human-computer interaction at cognitive and physical levels. This includes both brain and body in the design of meaningful VR experiences; these cases in which participants feel naturally present could help augment the benefits of BCIs for assistive and neurorehabilitation applications for the relearning of motor and cognitive skills. VR technology is now available at the consumer level thanks to the proliferation of affordable head-mounted displays (HMDs). Merging both technologies into simplified, practical devices may help democratize these technologies.

G-Causality Brain Connectivity Differences of Finger Movements between Motor Execution and Motor Imagery

Motor imagery is one of the classical paradigms which have been used in brain-computer interface and motor function recovery. Finger movement-based motor execution is a complex biomechanical architecture and a crucial task for establishing most complicated and natural activities in daily life. Some patients may suffer from alternating hemiplegia after brain stroke and lose their ability of motor execution. Fortunately, the ability of motor imagery might be preserved independently and worked as a backdoor for motor function recovery. The efficacy of motor imagery for achieving significant recovery for the motor cortex after brain stroke is still an open question. In this study, we designed a new paradigm to investigate the neural mechanism of thirty finger movements in two scenarios: motor execution and motor imagery. Eleven healthy participants performed or imagined thirty hand gestures twice based on left and right finger movements. The electroencephalogram (EEG) signal for each subject during sixty trials left and right finger motor execution and imagery were recorded during our proposed experimental paradigm. The Granger causality (G-causality) analysis method was employed to analyze the brain connectivity and its strength between contralateral premotor, motor, and sensorimotor areas. Highest numbers for G-causality trials of 37 ± 7.3, 35.5 ± 8.8, 36.3 ± 10.3, and 39.2 ± 9.0 and lowest Granger causality coefficients of 9.1 ± 3.2, 10.9 ± 3.7, 13.2 ± 0.6, and 13.4 ± 0.6 were achieved from the premotor to motor area during execution/imagination tasks of right and left finger movements, respectively. These results provided a new insight into motor execution and motor imagery based on hand gestures, which might be useful to build a new biomarker of finger motor recovery for partially or even completely plegic patients. Furthermore, a significant difference of the G-causality trial number was observed during left finger execution/imagery and right finger imagery, but it was not observed during the right finger execution phase. Significant difference of the G-causality coefficient was observed during left finger execution and imagery, but it was not observed during right finger execution and imagery phases. These results suggested that different MI-based brain motor function recovery strategies should be taken for right-hand and left-hand patients after brain stroke.

Activity in the dorsal ACC causes deterioration of sequential motor performance due to anxiety

Performance anxiety can profoundly affect motor performance, even in experts such as professional athletes and musicians. Previously, the neural mechanisms underlying anxiety-induced performance deterioration have predominantly been investigated for individual one-shot actions. Sports and music, however, are characterized by action sequences, where many individual actions are assembled to develop a performance. Here, utilizing a novel differential sequential motor learning paradigm, we first show that performance at the junctions between pre-learnt action sequences is particularly prone to anxiety. Next, utilizing functional magnetic resonance imaging (fMRI), we reveal that performance deterioration at the junctions is parametrically correlated with activity in the dorsal anterior cingulate cortex (dACC). Finally, we show that 1 Hz repetitive transcranial magnetic stimulation of the dACC attenuates the performance deterioration at the junctions. These results demonstrate causality between dACC activity and impairment of sequential motor performance due to anxiety, and suggest new intervention techniques against the deterioration.

Dissociation between cortical and spinal excitability of the antagonist muscle during combined motor imagery and action observation

Inhibitory neural control of antagonist muscle is one of the fundamental neural mechanism of coordinated human limb movement. Previous studies have revealed that motor execution (ME) and motor imagery (MI) share many common neural substrates; however, whether inhibitory neural activity occurs during MI remains unknown. In addition, recent studies have demonstrated that a combined MI and action observation (MI + AO) produces strong neurophysiological changes compared with MI or AO alone. Therefore, we investigated inhibitory changes in cortical and spinal excitability of the antagonist muscle during MI + AO and ME. Single-pulse transcranial magnetic stimulation (TMS) experiments revealed that corticospinal excitability of the antagonist muscle was decreased during MI + AO. Conversely, F-wave experiments showed that F-wave persistence of the antagonist muscle increased. Paired-pulse TMS experiment also demonstrated that short-interval intracortical inhibition (SICI) did not contribute to this inhibition. Therefore, cortical mediated inhibition, except for SICI, may be related to this inhibition. Conversely, such clear inhibition of the antagonist muscle was not observed during ME, presumably owing to the effects of muscle contraction to decelerate the movements and/or sensory input accompanying the joint movements. These findings provide important insights into the neurophysiological differences between MI + AO and ME.

EEG Signals Feature Extraction Based on DWT and EMD Combined with Approximate Entropy

The classification recognition rate of motor imagery is a key factor to improve the performance of brain-computer interface (BCI). Thus, we propose a feature extraction method based on discrete wavelet transform (DWT), empirical mode decomposition (EMD), and approximate entropy. Firstly, the electroencephalogram (EEG) signal is decomposed into a series of narrow band signals with DWT, then the sub-band signal is decomposed with EMD to get a set of stationary time series, which are called intrinsic mode functions (IMFs). Secondly, the appropriate IMFs for signal reconstruction are selected. Thus, the approximate entropy of the reconstructed signal can be obtained as the corresponding feature vector. Finally, support vector machine (SVM) is used to perform the classification. The proposed method solves the problem of wide frequency band coverage during EMD and further improves the classification accuracy of EEG signal motion imaging.

Remote effects on corticospinal excitability during motor execution and motor imagery

We investigated the remote effect on corticospinal excitability of resting left and right hand muscles during motor execution and motor imagery when performing left or right foot plantar flexion. Fifteen right-handed subjects performed two conditions with three tasks: Condition (Motor Execution (ME) vs. Motor Imagery (MI)): Task (Control, Ipsilateral, and Contralateral). From the left and right first dorsal interosseous, motor evoked potentials (MEPs) elicited by a single-pulse transcranial magnetic stimulation (TMS) to the left or right primary motor cortices (M1) were recorded under all six trials. MEP amplitudes were significantly larger under the ME than MI condition, irrespective of hands and tasks. MEP amplitudes were also the largest during the Contralateral tasks, irrespective of the condition and hands. The correlation analysis showed that MEP amplitudes were significantly correlated between ME and MI conditions with both left and right hands. Our results indicate that the magnitude of the remote effect on corticospinal excitability of hand muscles differs between motor execution and motor imagery, and between ipsi- and contralateral limbs, when performing foot plantar flexion.

Motor planning with and without motor imagery in children with Developmental Coordination Disorder

Children with Developmental Coordination Disorder (DCD) demonstrate inefficient motor planning ability with a tendency to opt for non-optimal planning strategies. Motor imagery can provide an insight to this planning inefficiency, as it may be a strategy for improving motor planning and thereby motor performance for those with DCD. In this study, we investigated the prevalence of end-state-comfort (ESC) and the minimal rotation strategy using a grip selection task in children with DCD with and without motor imagery instructions. Boys with (n = 14) and without DCD (n = 18) aged 7-12 years completed one, two and three colour sequences of a grip selection (octagon) task. Two conditions were examined; a Motor Planning (MP) condition requiring only the performance of the task and a Motor Imagery and Planning (MIP) condition, which included an instruction to imagine performing the movement before execution. For the MP condition, children with DCD ended fewer trials in ESC for the one (p = 0.001) and two colour (p = 0.002) sequences and used a minimal rotation strategy more often than those without DCD. For the MIP condition, the DCD group significantly increased their use of the ESC strategy for the one colour sequences (p = 0.014) while those without DCD improved for the two colour (p = 0.008) sequences. ESC level of the DCD group on the MIP condition was similar to those without DCD at baseline for all colour sequences. Motor imagery shows potential as a strategy for improving motor planning in children with DCD. Implications and limitations are discussed.

Visual and kinesthetic modes affect motor imagery classification in untrained subjects

The understanding of neurophysiological mechanisms responsible for motor imagery (MI) is essential for the development of brain-computer interfaces (BCI) and bioprosthetics. Our magnetoencephalographic (MEG) experiments with voluntary participants confirm the existence of two types of motor imagery, kinesthetic imagery (KI) and visual imagery (VI), distinguished by activation and inhibition of different brain areas in motor-related α- and β-frequency regions. Although the brain activity corresponding to MI is usually observed in specially trained subjects or athletes, we show that it is also possible to identify particular features of MI in untrained subjects. Similar to real movement, KI implies muscular sensation when performing an imaginary moving action that leads to event-related desynchronization (ERD) of motor-associated brain rhythms. By contrast, VI refers to visualization of the corresponding action that results in event-related synchronization (ERS) of α- and β-wave activity. A notable difference between KI and VI groups occurs in the frontal brain area. In particular, the analysis of evoked responses shows that in all KI subjects the activity in the frontal cortex is suppressed during MI, while in the VI subjects the frontal cortex is always active. The accuracy in classification of left-arm and right-arm MI using artificial intelligence is similar for KI and VI. Since untrained subjects usually demonstrate the VI imagery mode, the possibility to increase the accuracy for VI is in demand for BCIs. The application of artificial neural networks allows us to classify MI in raising right and left arms with average accuracy of 70% for both KI and VI using appropriate filtration of input signals. The same average accuracy is achieved by optimizing MEG channels and reducing their number to only 13.

Developmental Changes in Task-Induced Brain Deactivation in Humans Revealed by a Motor Task

Performing tasks activates relevant brain regions in adults while deactivating task-irrelevant regions. Here, using a well-controlled motor task, we explored how deactivation is shaped during typical human development and whether deactivation is related to task performance. Healthy right-handed children (8-11 years), adolescents (12-15 years), and young adults (20-24 years; 20 per group) underwent functional magnetic resonance imaging with their eyes closed while performing a repetitive button-press task with their right index finger in synchronization with a 1-Hz sound. Deactivation in the ipsilateral sensorimotor cortex (SM1), bilateral visual and auditory (cross-modal) areas, and bilateral default mode network (DMN) progressed with development. Specifically, ipsilateral SM1 and lateral occipital deactivation progressed prominently between childhood and adolescence, while medial occipital (including primary visual) and DMN deactivation progressed from adolescence to adulthood. In adults, greater cross-modal deactivation in the bilateral primary visual cortices was associated with higher button-press timing accuracy relative to the sound. The region-specific deactivation progression in a developmental period may underlie the gradual promotion of sensorimotor function segregation required in the task. Task-induced deactivation might have physiological significance regarding suppressed activity in task-irrelevant regions. Furthermore, cross-modal deactivation develops to benefit some aspects of task performance in adults.

Subjective vividness of motor imagery has a neural signature in human premotor and parietal cortex

Motor imagery (MI) is the process in which subjects imagine executing a body movement with a strong kinesthetic component from a first-person perspective. The individual capacity to elicit such mental images is not universal but varies within and between subjects. Neuroimaging studies have shown that these inter-as well as intra-individual differences in imagery quality mediate the amplitude of neural activity during MI on a group level. However, these analyses were not sensitive to forms of representation that may not map onto a simple modulation of overall amplitude. Therefore, the present study asked how far the subjective impression of motor imagery vividness is reflected by a spatial neural code, and how patterns of neural activation in different motor regions relate to specific imagery impressions. During fMRI scanning, 20 volunteers imagined three different types of right-hand actions. After each imagery trial, subjects were asked to evaluate the perceived vividness of their imagery. A correlation analysis compared the rating differences and neural dissimilarity values of the rating groups separately for each region of interest. Results showed a significant positive correlation in the left vPMC and right IPL, indicating that these regions particularly reflect perceived imagery vividness in that similar rated trials evoke more similar neural patterns. A decoding analysis revealed that the vividness of the motor image related systematically to the action specificity of neural activation patterns in left vPMC and right SPL. Imagined actions accompanied by higher vividness ratings were significantly more distinguishable within these areas. Altogether, results showed that spatial patterns of neural activity within the human motor cortices reflect the individual vividness of imagined actions. Hence, the findings reveal a link between the subjective impression of motor imagery vividness and objective physiological markers.

Negative BOLD responses during hand and foot movements: An fMRI study

The present study employed functional magnetic resonance imaging (fMRI) to examine the characteristics of negative blood oxygen level-dependent (Negative BOLD) signals during motor execution. Subjects repeated extension and flexion of one of the following: the right hand, left hand, right ankle, or left ankle. Negative BOLD responses during hand movements were observed in the ipsilateral hemisphere of the hand primary sensorimotor area (SMI), medial frontal gyrus (MeFG), middle frontal gyrus (MFG), and superior frontal gyrus (SFG). Negative BOLD responses during foot movements were also noted in the bilateral hand SMI, MeFG, MFG, SFG, inferior frontal gyrus, middle temporal gyrus, parahippocampal gyrus, anterior cingulate cortex, cingulate gyrus (CG), fusiform gyrus, and precuneus. A conjunction analysis showed that portions of the MeFG and CG involving similar regions to those of the default mode network were commonly deactivated during voluntary movements of the right/left hand or foot. The present results suggest that three mechanisms are involved in the Negative BOLD responses observed during voluntary movements: (1) transcallosal inhibition from the contralateral to ipsilateral hemisphere in the SMI, (2) the deactivated neural network with several brain regions, and (3) the default mode network in the MeFG and CG.

Comparison of brain activity between motor imagery and mental rotation of the hand tasks: a functional magnetic resonance imaging study

Motor imagery (MI) has been considered effective in learning and practicing movements in many fields. However, when evaluating the effectiveness of this technique, the examiner has no way of assessing the participant’s motor imagery process. As an alternative, we have been exploring a mental body-part rotation task, in which the examiner can estimate the participant’s motivation and ability to sustain attention through the scored results. In this study, we aimed to investigate the possible application of a mental rotation (MRot) task and used fMRI to compare the brain activity during the MRot task with that during an MI task in healthy volunteers. Increased blood oxygenation level-dependent signals were observed bilaterally in the premotor areas and supplementary motor area during performance of both MI and MRot tasks. Our findings suggest that MRot could be an alternative to MI.

The Effect of Body-Related Stimuli on Mental Rotation in Children, Young and Elderly Adults

This study aimed to explore the development of mental rotation ability throughout life by comparing different kinds of stimuli. Thirty-six children (6-9 years-old), 30 young (20-28 years-old) and 30 elderly people (60-82 years-old) performed mental rotation tasks with abstract (i.e. two-dimensional lines) and concrete stimuli (i.e. hands, human/animal faces). The results showed that overall young people outperformed children and elderly people, while children were less accurate than the elderly. However, the effect of age was shaped by the kinds of stimuli: (a) young people were more accurate than children and elderly people particularly with abstract stimuli; (b) elderly people improved their performance with images depicting faces; (c) children performed better with body-related stimuli than animal faces. Finally, performance was more difficult when stimuli were rotated by 180°, especially for younger and older females. We may conclude that the effects of age are modulated by the characteristics of the stimuli with a specific difficulty for abstract stimuli and a facilitation for concrete stimuli. As an innovative aspect, during childhood there appeared a specific facilitation for body-related stimuli, not just for concrete ones. These findings are interpreted according to embodied models of cognitive development and the effects of ageing on the brain.

Mental imagery in psychiatry: conceptual & clinical implications

Mental imagery refers to the experience of perception in the absence of external sensory input. Deficits in the ability to generate mental imagery or to distinguish it from actual sensory perception are linked to neurocognitive conditions such as dementia and schizophrenia, respectively. However, the importance of mental imagery to psychiatry extends beyond neurocognitive impairment. Mental imagery has a stronger link to emotion than verbal-linguistic cognition, serving to maintain and amplify emotional states, with downstream impacts on motivation and behavior. As a result, anomalies in the occurrence of emotion-laden mental imagery has transdiagnostic significance for emotion, motivation, and behavioral dysfunction across mental disorders. This review aims to demonstrate the conceptual and clinical significance of mental imagery in psychiatry through examples of mood and anxiety disorders, self-harm and suicidality, and addiction. We contend that focusing on mental imagery assessment in research and clinical practice can increase our understanding of the cognitive basis of psychopathology in mental disorders, with the potential to drive the development of algorithms to aid treatment decision-making and inform transdiagnostic treatment innovation.

Spinal plasticity with motor imagery practice

KEY POINTS

While a consensus has now been reached on the effect of motor imagery (MI) - the mental simulation of an action - on motor cortical areas, less is known about its impact on spinal structures. The current study, using H-reflex conditioning paradigms, examined the effect of a 20 min MI practice on several spinal mechanisms of the plantar flexor muscles. We observed modulations of spinal presynaptic circuitry while imagining, which was even more pronounced following an acute session of MI practice. We suggested that the small cortical output generated during MI may reach specific spinal circuits and that repeating MI may increase the sensitivity of the spinal cord to its effects. The short-term plasticity induced by MI practice may include spinal network modulation in addition to cortical reorganization.

ABSTRACT

Kinesthetic motor imagery (MI) is the mental simulation of a movement with its sensory consequences but without its concomitant execution. While the effect of MI practice on cortical areas is well known, its influence on spinal circuitry remains unclear. Here, we assessed plastic changes in spinal structures following an acute MI practice. Thirteen young healthy participants accomplished two experimental sessions: a 20 min MI training consisting of four blocks of 25 imagined maximal isometric plantar flexions, and a 20 min rest (control session). The level of spinal presynaptic inhibition was assessed by conditioning the triceps surae spinal H-reflex with two methods: (i) the stimulation of the common peroneal nerve that induced D1 presynaptic inhibition (H_PSI response), and (ii) the stimulation of the femoral nerve that induced heteronymous Ia facilitation (H_FAC response). We then compared the effects of MI on unconditioned (H_TEST ) and conditioned (H_PSI and H_FAC ) responses before, immediately after and 10 min after the 20 min session. After resting for 20 min, no changes were observed on the recorded parameters. After MI practice, the amplitude of rest H_TEST was unchanged, while H_PSI and H_FAC significantly increased, showing a reduction of presynaptic inhibition with no impact on the afferent-motoneuronal synapse. The current results revealed the acute effect of MI practice on baseline spinal presynaptic inhibition, increasing the sensitivity of the spinal circuitry to MI. These findings will help in understanding the mechanisms of neural plasticity following chronic practice.

Frequency Specific Cortical Dynamics During Motor Imagery Are Influenced by Prior Physical Activity

Motor imagery is often used inducing changes in electroencephalographic (EEG) signals for imagery-based brain-computer interfacing (BCI). A BCI is a device translating brain signals into control signals providing severely motor-impaired persons with an additional, non-muscular channel for communication and control. In the last years, there is increasing interest using BCIs also for healthy people in terms of enhancement or gaming. Most studies focusing on improving signal processing feature extraction and classification methods, but the performance of a BCI can also be improved by optimizing the user's control strategies, e.g., using more vivid and engaging mental tasks for control. We used multichannel EEG to investigate neural correlates of a sports imagery task (playing tennis) compared to a simple motor imagery task (squeezing a ball). To enhance the vividness of both tasks participants performed a short physical exercise between two imagery sessions. EEG was recorded from 60 closely spaced electrodes placed over frontal, central, and parietal areas of 30 healthy volunteers divided in two groups. Whereas Group 1 (EG) performed a physical exercise between the two imagery sessions, Group 2 (CG) watched a landscape movie without physical activity. Spatiotemporal event-related desynchronization (ERD) and event-related synchronization (ERS) patterns during motor imagery (MI) tasks were evaluated. The results of the EG showed significant stronger ERD patterns in the alpha frequency band (8-13 Hz) during MI of tennis after training. Our results are in evidence with previous findings that MI in combination with motor execution has beneficial effects. We conclude that sports MI combined with an interactive game environment could be a future promising task in motor learning and rehabilitation improving motor functions in late therapy processes or support neuroplasticity.

Influence of mirror therapy and motor imagery on intermanual transfer effects in upper-limb prosthesis training of healthy participants: A randomized pre-posttest study

The effect that a motor skill trained on one side can lead to improvement in the untrained side is called intermanual transfer. Intermanual transfer can help enhance upper limb prosthetic training. To determine the influence of mirror therapy and motor imagery on intermanual transfer in upper limb prosthesis training, a pseudo-randomized clinical trial, single blinded, with a pre-posttest design was used. Forty-seven able-bodied, right-handed participants were pseudo-randomly assigned to two training groups and one control group. One training group undertook an intermanual transfer training program, using an upper-limb prosthetic simulator with added mirror therapy and motor imagery. The second training group completed only the intermanual transfer training program. The control group completed a sham training: a dummy training without using the prosthesis simulator. The program lasted five consecutive days. To determine the improvement in skill, a test was administered before, immediately after, and six days after the training program. Training used the "unaffected" arm; tests were performed with the "affected" arm, resembling the amputated limb. Movement time, the time from the beginning of the movement until completion of the task; hand opening, the duration of the maximum prosthetic hand opening; and grip-force control, the deviation from the required force during a tracking task. No intermanual transfer effects were found: neither the intermanual transfer training program, nor the additional mirror therapy and motor imagery affected prosthesis skills. A limitation of the study was that the training program was applied to able-bodied subjects instead of patients with an amputation. Contrary to previous studies, no intermanual transfer effects were found. Additional mirror therapy and motor imagery did not ameliorate intermanual transfer effects.

Effect of the combination of motor imagery and electrical stimulation on upper extremity motor function in patients with chronic stroke: preliminary results

Background

The combination of motor imagery (MI) and afferent input with electrical stimulation (ES) enhances the excitability of the corticospinal tract compared with motor imagery alone or electrical stimulation alone. However, its therapeutic effect is unknown in patients with hemiparetic stroke. We performed a preliminary examination of the therapeutic effects of MI + ES on upper extremity (UE) motor function in patients with chronic stroke.

Methods

A total of 10 patients with chronic stroke demonstrating severe hemiparesis participated. The imagined task was extension of the affected finger. Peripheral nerve electrical stimulation was applied to the radial nerve at the spiral groove. MI + ES intervention was conducted for 10 days. UE motor function as assessed with the Fugl-Meyer assessment UE motor score (FMA-UE), the amount of the affected UE use in daily life as assessed with a Motor Activity Log (MAL-AOU), and the degree of hypertonia in flexor muscles as assessed with the Modified Ashworth Scale (MAS) were evaluated before and after intervention. To assess the change in spinal neural circuits, reciprocal inhibition between forearm extensor and flexor muscles with the H reflex conditioning-test paradigm at interstimulus intervals (ISIs) of 0, 20, and 100 ms were measured before and after intervention.

Results

UE motor function, the amount of the affected UE use, and muscle hypertonia in flexor muscles were significantly improved after MI + ES intervention (FMA-UE: p < 0.01, MAL-AOU: p < 0.01, MAS: p = 0.02). Neurophysiologically, the intervention induced restoration of reciprocal inhibition from the forearm extensor to the flexor muscles (ISI at 0 ms: p = 0.03, ISI at 20 ms: p = 0.03, ISI at 100 ms: p = 0.01).

Conclusion

MI + ES intervention was effective for improving UE motor function in patients with severe paralysis.

Combining Movement-Related Cortical Potentials and Event-Related Desynchronization to Study Movement Preparation and Execution

This study applied a comprehensive electroencephalography (EEG) analysis for movement-related cortical potentials (MRCPs) and event-related desynchronization (ERD) in order to understand movement-related brain activity changes during movement preparation and execution stage of unilateral wrist extension. Thirty-four healthy subjects completed two event-related potential tests in the same sequence. Unilateral wrist extension was involved in both tests as the movement task. Instruction Response Movement (IRM) was a brisk movement response task with visual “go” signal, while Cued Instruction Response Movement (CIRM) added a visual cue contenting the direction information to create a prolonged motor preparation stage. Recorded EEG data were segmented and averaged to show time domain changes and then transformed into time-frequency mapping to show the time-frequency changes. All components were calculated and compared among C3, Cz, and C4 locations. The motor potential appeared bilaterally in both tests' movement execution stages, and Cz had the largest peak value among the investigated locations (p < 0.01). In CIRM, a contingent negative variation (CNV) component presented bilaterally during the movement preparation stage with the largest amplitude at Cz. ERD of the mu rhythm (mu ERD) presented bilateral sensorimotor cortices during movement execution stages in both tests and was the smallest at Cz among the investigated locations. In the movement preparation stage of CIRM, mu ERD presented mainly in the contralateral sensory motor cortex area (C3 and C4 for right and left wrist movements, respectively) and showed significant differences between different locations. EEG changes in the time and time-frequency domains showed different topographical features. Movement execution was controlled bilaterally, while movement preparation was controlled mainly by contralateral sensorimotor cortices. Mu ERD was found to have stronger contra-lateralization features in the movement preparation stage and might be a better indicator for detecting movement intentions. This information could be helpful and might provide comprehensive information for studying movement disorders (such as those in post-stroke hemiplegic patients) or for facilitating the development of neuro-rehabilitation engineering technology such as brain computer interface.