Motor Imagery-Based Rehabilitation: Potential Neural Correlates and Clinical Application for Functional Recovery of Motor Deficits after Stroke

C. S. Parallel convolutional neural network and empirical mode decomposition for high accuracy in motor imagery EEG signal classification

In recent years, the utilization of motor imagery (MI) signals derived from electroencephalography (EEG) has shown promising applications in controlling various devices such as wheelchairs, assistive technologies, and driverless vehicles. However, decoding EEG signals poses significant challenges due to their complexity, dynamic nature, and low signal-to-noise ratio (SNR). Traditional EEG pattern recognition algorithms typically involve two key steps: feature extraction and feature classification, both crucial for accurate operation. In this work, we propose a novel method that addresses these challenges by employing empirical mode decomposition (EMD) for feature extraction and a parallel convolutional neural network (PCNN) for feature classification. This approach aims to mitigate non-stationary issues, improve performance speed, and enhance classification accuracy. We validate the effectiveness of our proposed method using datasets from the BCI competition IV, specifically datasets 2a and 2b, which contain motor imagery EEG signals. Our method focuses on identifying two- and four-class motor imagery EEG signal classifications. Additionally, we introduce a transfer learning technique to fine-tune the model for individual subjects, leveraging important features extracted from a group dataset. Our results demonstrate that the proposed EMD-PCNN method outperforms existing approaches in terms of classification accuracy. We conduct both qualitative and quantitative analyses to evaluate our method. Qualitatively, we employ confusion matrices and various performance metrics such as specificity, sensitivity, precision, accuracy, recall, and f1-score. Quantitatively, we compare the classification accuracies of our method with those of existing approaches. Our findings highlight the superiority of the proposed EMD-PCNN method in accurately classifying motor imagery EEG signals. The enhanced performance and robustness of our method underscore its potential for broader applicability in real-world scenarios.

Comparison of Brain Activation Between Different Modes of Motor Acquisition: A Functional Near-Infrared Study

BACKGROUND

Different modes of motor acquisition, including motor execution (ME), motor imagery (MI), action observation (AO), and mirror visual feedback (MVF), are often used when learning new motor behavior and in clinical rehabilitation.

PURPOSE

The aim of this study was to investigate differences in brain activation during different motor acquisition modes among healthy young adults.

METHODS

This cross-sectional study recruited 29 healthy young adults. Participants performed a functional reaching and grasping task under ME, MI, AO, and MVF mode with their right arms at a frequency of 0.5 Hz for 1 min per task. Each task was performed three times in a random order. Brain activation in the supplementary motor area (SMA), premotor cortices (PMC), and primary motor cortices (M1) during tasks was measured using functional near-infrared spectroscopy through 16 source-detector channels.

RESULTS

ME showed significant activation in bilateral PMC, M1, and right SMA, with higher activation in the contralateral M1. MI induced greater activity in the PMC and SMA, particularly in the ipsilateral regions. MVF resulted in significant activation in bilateral PMC, SMA, and M1. AO showed an increasing trend in brain activation, but no significant differences in any channels. Compared to AO, ME and MVF induced significantly greater brain activity in M1.

CONCLUSION

Activation levels under MI and MVF were comparable to that of ME. MI and MVF induced greater activity in the PMC and SMA, and MVF showed significant activity in all brain areas, especially in the bilateral M1. These findings support the application of different motor acquisition strategies according to individual needs. When ME cannot be executed, such as for individuals with hemiparesis or severe impairments of both upper extremities, MI and MVF may be applied, respectively, to drive neuroplastic changes.

Characteristic brain functional activation and connectivity during actual and imaginary right-handed grasp

We used 34-channel functional near infrared spectroscopy to investigate and compare changes in oxyhemoglobin concentration of brain networks in bilateral prefrontal cortex, sensorimotor cortex, and occipital lobe of 22 right-handed healthy adults during executive right-handed grasp (motor execution task) and imagined right-handed grasp (motor imagery task). Then calculated lateral index and functional contribution degree, and measured functional connectivity strength between the regions of interest. In the motor executive block task, there was a significant increase in oxyhemoglobin concentration in regions of interest except for right occipital lobe (P<0.05), while in the motor imagery task, all left regions of interest's oxyhemoglobin concentration increased significantly (P<0.05). Except the prefrontal cortex in motor executive task, the left side of the brain was dominant. Left sensorimotor cortex played a major role in these two tasks, followed by right sensorimotor cortex. Among all functional contribution degree, left sensorimotor cortex, right sensorimotor cortex and left occipital lobe ranked top three during these tasks. In continuous acquisition tasks, functional connectivity on during motor imagery task was stronger than that during motor executive task. Brain functions during two tasks of right-hand grasping movement were partially consistent. However, the excitability of brain during motor imagery was lower, and it was more dependent on the participation of left prefrontal cortex, and its synchronous activity of the whole brain was stronger. The trend of functional contribution degree was basically consistent with oxyhemoglobin concentration and lateral index, and can be used as a novel index to evaluate brain function. [ChiCTR2200063792 (2022-09-16)].

Investigating unilateral and bilateral motor imagery control using electrocorticography and fMRI in awake craniotomy

BACKGROUND

The rapid development of neurosurgical techniques, such as awake craniotomy, has increased opportunities to explore the mysteries of the brain. This is crucial for deepening our understanding of motor control and imagination processes, especially in developing brain-computer interface (BCI) technologies and improving neurorehabilitation strategies for neurological disorders.

OBJECTIVE

This study aimed to analyze brain activity patterns in patients undergoing awake craniotomy during actual movements and motor imagery, mainly focusing on the motor control processes of the bilateral limbs.

METHODS

We conducted detailed observations of patients undergoing awake craniotomies. The experimenter requested participants to perform and imagine a series of motor tasks involving their hands and tongues. Brain activity during these tasks was recorded using functional magnetic resonance imaging (fMRI) and intraoperative electrocorticography (ECoG). The study included left and right finger tapping, tongue protrusion, hand clenching, and imagined movements corresponding to these actions.

RESULTS

fMRI revealed significant activation in the brain's motor areas during task performance, mainly involving bilateral brain regions during imagined movement. ECoG data demonstrated a marked desynchronization pattern in the ipsilateral motor cortex during bilateral motor imagination, especially in bilateral coordination tasks. This finding suggests a potential controlling role of the unilateral cerebral cortex in bilateral motor imagination.

CONCLUSION

Our study highlights the unilateral cerebral cortex's significance in controlling bilateral limb motor imagination, offering new insights into future brain network remodeling in patients with hemiplegia. Additionally, these findings provide important insights into understanding motor imagination and its impact on BCI and neurorehabilitation.

Examining the effectiveness of motor imagery combined with non-invasive brain stimulation for upper limb recovery in stroke patients: a systematic review and meta-analysis of randomized clinical trials

BACKGROUND

Transcranial direct current stimulation (tDCS) and repetitive transcranial magnetic stimulation (rTMS) are common non-invasive brain stimulation (NIBS) methods for functional recovery after stroke. Motor imagery (MI) can be used in the rehabilitation of limb motor function after stroke, but its effectiveness remains to be rigorously established. Furthermore, there is a growing interest in the combined application of NIBS with MI, yet the evidence regarding its impact on the recovery of upper limb function after stroke is inconclusive. This meta-analysis aimed to demonstrate whether combining the two is superior to NIBS alone or MI alone to provide a reference for clinical decision-making.

METHODS

PubMed, EMBASE, Cochrane Library, Web of Science, Science Direct, CNKI, WANFANG, and VIP databases were searched for randomized controlled trials on the effects of MI combined NIBS in motor function recovery after stroke until February 2024. The outcomes of interest were associated with body functions or structure (impairment) and activity (functional). The primary outcome was assessed with the Fugl-Meyer assessment of the upper extremity (FMA-UE) for motor function of the upper limbs and the modified Barthel Index (MBI) for the ability to perform daily living activities. For secondary outcomes, functional activity level was measured using wolf motor function test (WMFT) and action research arm test (ARAT), and cortical excitability was assessed using cortical latency of motor evoked potential (MEP-CL) and central motor conduction time (CMCT). The methodological quality of the selected studies was evaluated using the evidence‑based Cochrane Collaboration's tool. A meta-analysis was performed to calculate the mean differences (MD) or the standard mean differences (SMD) and 95% confidence intervals (CI) with random-effect models.

RESULTS

A total of 14 articles, including 886 patients, were reviewed in the meta-analysis. In comparison with MI or NIBS alone, the combined therapy significantly improved the motor function of the upper limbs (MD = 5.43; 95% CI 4.34-6.53; P < 0.00001) and the ability to perform activities of daily living (MD = 11.07; 95% CI 6.33-15.80; P < 0.00001). Subgroup analyses showed an interaction between the stage of stroke, the type of MI, and the type of NIBS with the effect of the combination therapy.

CONCLUSION

The combination of MI and NIBS may be a promising therapeutic approach to enhance upper limb motor function, functional activity, and activities of daily living after stroke.

SYSTEMATIC REGISTRATION

PROSPERO registration CRD42023493073.

Hybrid Functional Near-Infrared Spectroscopy System and Electromyography for Prosthetic Knee Control

The increasing number of individuals with limb loss worldwide highlights the need for advancements in prosthetic knee technology. To improve control and quality of life, integrating brain-computer communication with motor imagery offers a promising solution. This study introduces a hybrid system that combines electromyography (EMG) and functional near-infrared spectroscopy (fNIRS) to address these limitations and enhance the control of knee movements for individuals with above-knee amputations. The study involved an experiment with nine healthy male participants, consisting of two sessions: real execution and imagined execution using motor imagery. The OpenBCI Cyton board collected EMG signals corresponding to the desired movements, while fNIRS monitored brain activity in the prefrontal and motor cortices. The analysis of the simultaneous measurement of the muscular and hemodynamic responses demonstrated that combining these data sources significantly improved the classification accuracy compared to using each dataset alone. The results showed that integrating both the EMG and fNIRS data consistently achieved a higher classification accuracy. More specifically, the Support Vector Machine performed the best during the motor imagery tasks, with an average accuracy of 49.61%, while the Linear Discriminant Analysis excelled in the real execution tasks, achieving an average accuracy of 89.67%. This research validates the feasibility of using a hybrid approach with EMG and fNIRS to enable prosthetic knee control through motor imagery, representing a significant advancement potential in prosthetic technology.

Cardiac cycle modulates alpha and beta suppression during motor imagery

Previous interoception research has demonstrated that sensory processing is reduced during cardiac systole, an effect associated with diminished cortical excitability, possibly due to heightened baroreceptor activity. This study aims to determine how phases of the cardiac cycle-systole and diastole-modulate neural sensorimotor activity during motor imagery (MI) and motor execution (ME). We hypothesised that MI performance, indexed by enhanced suppression of contralateral sensorimotor alpha (8-13 Hz) and beta (14-30 Hz) activity, would be modulated by the cardiac phases, with improved performance during diastole due to enhanced sensory processing of movement cues. Additionally, we investigated whether movement cues during systole or diastole enhance muscle activity. To test these hypotheses, 29 participants were instructed to perform or imagine thumb abductions, while we recorded their electroencephalography, electrocardiogram, and electromyogram (EMG) activity. We show that imaginary movements instructed during diastole lead to more pronounced suppression of alpha and beta activity in contralateral sensorimotor cortices, with no significant cardiac timing effects observed during ME as confirmed by circular statistics. Additionally, diastole was associated with significantly increased EMG on the side of actual and, to a lesser degree, imagined movements. Our study identifies optimal cardiac phases for MI performance, suggesting potential pathways to enhance MI-based assistive technologies.

Interactive Virtual Ankle Movement Controlled by Wrist sEMG Improves Motor Imagery: An Exploratory Study

Virtual reality (VR) techniques can significantly enhance motor imagery training by creating a strong illusion of action for central sensory stimulation. In this article, we establish a precedent by using surface electromyography (sEMG) of contralateral wrist movement to trigger virtual ankle movement through an improved data-driven approach with a continuous sEMG signal for fast and accurate intention recognition. Our developed VR interactive system can provide feedback training for stroke patients in the early stages, even if there is no active ankle movement. Our objectives are to evaluate: 1) the effects of VR immersion mode on body illusion, kinesthetic illusion, and motor imagery performance in stroke patients; 2) the effects of motivation and attention when utilizing wrist sEMG as a trigger signal for virtual ankle motion; 3) the acute effects on motor function in stroke patients. Through a series of well-designed experiments, we have found that, compared to the 2D condition, VR significantly increases the degree of kinesthetic illusion and body ownership of the patients, and improves their motor imagery performance and motor memory. When compared to conditions without feedback, using contralateral wrist sEMG signals as trigger signals for virtual ankle movement enhances patients' sustained attention and motivation during repetitive tasks. Furthermore, the combination of VR and feedback has an acute impact on motor function. Our exploratory study suggests that the sEMG-based immersive virtual interactive feedback provides an effective option for active rehabilitation training for severe hemiplegia patients in the early stages, with great potential for clinical application.

Transcranial direct current stimulation for upper extremity motor dysfunction in poststroke patients: A systematic review and meta-analysis

OBJECTIVE

To evaluate the efficacy and safety of transcranial direct current stimulation in poststroke patients with upper extremity motor dysfunction using a systematic review and meta-analysis.

DATA SOURCES

We searched the Web of Science, Cochrane Library, EMBASE, and PubMed for randomized controlled trials investigating the effects of both active and sham stimulation up until January 27, 2024.

REVIEW METHODS

Efficacy, including the upper extremity Fugl-Meyer Assessment, Action Research Arm Test, Barthel Index, and safety, were assessed. The risk of bias was assessed using the Cochrane Risk of Bias 2 tool and the Physiotherapy Evidence Database Scale. Meta-analysis was performed using the RevMan 5.4 software.

RESULTS

Forty-four studies with 1555 participants were included. Transcranial direct current stimulation proved effective in improving upper extremity motor function (standardized mean difference = 0.22, 95% confidence interval: 0.12-0.32, P < 0.001) and Barthel Index (mean difference = 4.65, 95% confidence interval: 2.82-6.49, P < 0.001). Subgroup analysis revealed the highest transcranial direct current stimulation efficacy in patients with subacute stroke. Both anodal and cathodal stimulation were effective against upper extremity motor dysfunction. C3/C4 was the most effective stimulus target. Optimal stimulation parameters included stimulus current densities <0.057 mA/cm2 for 20-30 min and <30 sessions. Adverse effects and dropouts during follow-up showed that transcranial direct current stimulation is safe and feasible.

CONCLUSIONS

Our findings suggest that both anodal and cathodal stimulation were significantly effective in subacute stroke patients, particularly when preceding other treatments and when C3/C4 is targeted.

The Effects of Immersion and Visuo-Tactile Stimulation on Motor Imagery in Stroke Patients are Related to the Sense of Ownership

Visual guided motor imagery (MI) is commonly used in stroke rehabilitation, eliciting event-related desynchronization (ERD) in EEG. Previous studies found that immersion level and visuo-tactile stimulation could modulate ERD during visual guided MI, and both of two factors could also improve sense of ownership (SOO) over target limb (or body). Additionally, the relationship was also reported between the performance of MI and SOO. This study aims to investigate whether immersion and visuo-tactile stimulation affect visual guided MI through the SOO over virtual body in stroke patients. Nineteen stroke patients were recruited. The experiment included two phases (i.e., SOO induction and visual guided MI with SOO) that was manipulated across four conditions in a within-subject design: 2×2 , i.e., immersion (VR, 2D monitor display) × multisensory stimulation (visuo-tactile stimulation, observation without tactile stimulation). Results found peaks ERD amplitude during MI were significantly higher in stronger SOO conditions than weaker SOO conditions. Interestingly, the ERD during visual guided MI under the condition of vision only in VR and visuo-tactile stimulation in 2D monitor are similar, which indicates that SOO may be an important factor behind this phenomenon (due to the similar SOO between these two conditions). A moderate correlation was also found between SOO scores and peaks ERD amplitude during MI. This study discussed the possible factor underlying the effects of immersion and multisensory stimulation on visual guided MI in post-stroke patients, identifying the effect of SOO in this process, and could be referred in future studies for coming up with better MI paradigms for stroke rehabilitation.

Classification of EEG Signals Based on Sparrow Search Algorithm-Deep Belief Network for Brain-Computer Interface

In brain-computer interface (BCI) systems, challenges are presented by the recognition of motor imagery (MI) brain signals. Established recognition approaches have achieved favorable performance from patterns like SSVEP, AEP, and P300, whereas the classification methods for MI need to be improved. Hence, seeking a classification method that exhibits high accuracy and robustness for application in MI-BCI systems is essential. In this study, the Sparrow search algorithm (SSA)-optimized Deep Belief Network (DBN), called SSA-DBN, is designed to recognize the EEG features extracted by the Empirical Mode Decomposition (EMD). The performance of the DBN is enhanced by the optimized hyper-parameters obtained through the SSA. Our method's efficacy was tested on three datasets: two public and one private. Results indicate a relatively high accuracy rate, outperforming three baseline methods. Specifically, on the private dataset, our approach achieved an accuracy of 87.83%, marking a significant 10.38% improvement over the standard DBN algorithm. For the BCI IV 2a dataset, we recorded an accuracy of 86.14%, surpassing the DBN algorithm by 9.33%. In the SMR-BCI dataset, our method attained a classification accuracy of 87.21%, which is 5.57% higher than that of the conventional DBN algorithm. This study demonstrates enhanced classification capabilities in MI-BCI, potentially contributing to advancements in the field of BCI.

Rehabilitation Training after Spinal Cord Injury Affects Brain Structure and Function: From Mechanisms to Methods

Spinal cord injury (SCI) is a serious neurological insult that disrupts the ascending and descending neural pathways between the peripheral nerves and the brain, leading to not only functional deficits in the injured area and below the level of the lesion but also morphological, structural, and functional reorganization of the brain. These changes introduce new challenges and uncertainties into the treatment of SCI. Rehabilitation training, a clinical intervention designed to promote functional recovery after spinal cord and brain injuries, has been reported to promote activation and functional reorganization of the cerebral cortex through multiple physiological mechanisms. In this review, we evaluate the potential mechanisms of exercise that affect the brain structure and function, as well as the rehabilitation training process for the brain after SCI. Additionally, we compare and discuss the principles, effects, and future directions of several rehabilitation training methods that facilitate cerebral cortex activation and recovery after SCI. Understanding the regulatory role of rehabilitation training at the supraspinal center is of great significance for clinicians to develop SCI treatment strategies and optimize rehabilitation plans.

Effects of visual-electrotactile stimulation feedback on brain functional connectivity during motor imagery practice

The use of neurofeedback is an important aspect of effective motor rehabilitation as it offers real-time sensory information to promote neuroplasticity. However, there is still limited knowledge about how the brain's functional networks reorganize in response to such feedback. To address this gap, this study investigates the reorganization of the brain network during motor imagery tasks when subject to visual stimulation or visual-electrotactile stimulation feedback. This study can provide healthcare professionals with a deeper understanding of the changes in the brain network and help develop successful treatment approaches for brain-computer interface-based motor rehabilitation applications. We examine individual edges, nodes, and the entire network, and use the minimum spanning tree algorithm to construct a brain network representation using a functional connectivity matrix. Furthermore, graph analysis is used to detect significant features in the brain network that might arise in response to the feedback. Additionally, we investigate the power distribution of brain activation patterns using power spectral analysis and evaluate the motor imagery performance based on the classification accuracy. The results showed that the visual and visual-electrotactile stimulation feedback induced subject-specific changes in brain activation patterns and network reorganization in the [Formula: see text] band. Thus, the visual-electrotactile stimulation feedback significantly improved the integration of information flow between brain regions associated with motor-related commands and higher-level cognitive functions, while reducing cognitive workload in the sensory areas of the brain and promoting positive emotions. Despite these promising results, neither neurofeedback modality resulted in a significant improvement in classification accuracy, compared with the absence of feedback. These findings indicate that multimodal neurofeedback can modulate imagery-mediated rehabilitation by enhancing motor-cognitive communication and reducing cognitive effort. In future interventions, incorporating this technique to ease cognitive demands for participants could be crucial for maintaining their motivation to engage in rehabilitation.

Neuroimaging prognostic factors for treatment response to motor imagery training after stroke

The efficacy of motor imagery training for motor recovery is well acknowledged, but with substantial inter-individual variability in stroke patients. To help optimize motor imagery training therapy plans and screen suitable patients, this study aimed to explore neuroimaging biomarkers explaining variability in treatment response. Thirty-nine stroke patients were randomized to a motor imagery training group (n = 22, received a combination of conventional rehabilitation therapy and motor imagery training) and a control group (n = 17, received conventional rehabilitation therapy and health education) for 4 weeks of interventions. Their demography and clinical information, brain lesion from structural MRI, spontaneous brain activity and connectivity from rest fMRI, and sensorimotor brain activation from passive motor task fMRI were acquired to identify prognostic factors. We found that the variability of outcomes from sole conventional rehabilitation therapy could be explained by the reserved sensorimotor neural function, whereas the variability of outcomes from motor imagery training + conventional rehabilitation therapy was related to the spontaneous activity in the ipsilesional inferior parietal lobule and the local connectivity in the contralesional supplementary motor area. The results suggest that additional motor imagery training treatment is also efficient for severe patients with damaged sensorimotor neural function, but might be more effective for patients with impaired motor planning and reserved motor imagery.

Evidence of neuroplasticity with brain-computer interface in a randomized trial for post-stroke rehabilitation: a graph-theoretic study of subnetwork analysis

Background

Brain-computer interface (BCI) has been widely used for functional recovery after stroke. Understanding the brain mechanisms following BCI intervention to optimize BCI strategies is crucial for the benefit of stroke patients.

Methods

Forty-six patients with upper limb motor dysfunction after stroke were recruited and randomly divided into the control group or the BCI group. The primary outcome was measured by the assessment of Fugl-Meyer Assessment of Upper Extremity (FMA-UE). Meanwhile, we performed resting-state functional magnetic resonance imaging (rs-fMRI) in all patients, followed by independent component analysis (ICA) to identify functionally connected brain networks. Finally, we assessed the topological efficiency of both groups using graph-theoretic analysis in these brain subnetworks.

Results

The FMA-UE score of the BCI group was significantly higher than that of the control group after treatment (p = 0.035). From the network topology analysis, we first identified seven subnetworks from the rs-fMRI data. In the following analysis of subnetwork properties, small-world properties including γ (p = 0.035) and σ (p = 0.031) within the visual network (VN) decreased in the BCI group. For the analysis of the dorsal attention network (DAN), significant differences were found in assortativity (p = 0.045) between the groups. Additionally, the improvement in FMA-UE was positively correlated with the assortativity of the dorsal attention network (R = 0.498, p = 0.011).

Conclusion

Brain-computer interface can promote the recovery of upper limbs after stroke by regulating VN and DAN. The correlation trend of weak intensity proves that functional recovery in stroke patients is likely to be related to the brain's visuospatial processing ability, which can be used to optimize BCI strategies.

Clinical Trial Registration

The trial is registered in the Chinese Clinical Trial Registry, number ChiCTR2000034848. Registered 21 July 2020.

Classification of Motor Imagery EEG Signals Based on Data Augmentation and Convolutional Neural Networks

In brain-computer interface (BCI) systems, motor imagery electroencephalography (MI-EEG) signals are commonly used to detect participant intent. Many factors, including low signal-to-noise ratios and few high-quality samples, make MI classification difficult. In order for BCI systems to function, MI-EEG signals must be studied. In pattern recognition and other fields, deep learning approaches have recently been successfully applied. In contrast, few effective deep learning algorithms have been applied to BCI systems, especially MI-based systems. In this paper, we address these problems from two aspects based on the characteristics of EEG signals: first, we proposed a combined time-frequency domain data enhancement method. This method guarantees that the size of the training data is effectively increased while maintaining the intrinsic composition of the data. Second, our design consists of a parallel CNN that takes both raw EEG images and images transformed through continuous wavelet transform (CWT) as inputs. We conducted classification experiments on a public data set to verify the effectiveness of the algorithm. According to experimental results based on the BCI Competition IV Dataset2a, the average classification accuracy is 97.61%. A comparison of the proposed algorithm with other algorithms shows that it performs better in classification. The algorithm can be used to improve the classification performance of MI-based BCIs and BCI systems created for people with disabilities.

A Method for Using Video Presentation to Increase Cortical Region Activity during Motor Imagery Tasks in Stroke Patients

Previous studies have reported that stroke patients have difficulty recalling the motor imagery (MI) of a task, also known as MI vividness. Research on combining MI with action observation is gaining importance as a method to improve MI vividness. We enrolled 10 right-handed stroke patients and compared MI vividness and cortical activity under different presentation methods (no inverted image, inverted image of another individual’s hand, and an inverted image of the patient’s nonparalyzed hand) using near-infrared spectroscopy. Images of the nonparalyzed upper limb were inverted to make the paralyzed upper limb appear as if it were moving. Three tasks (non inverted image, AO + MI (other hand), AO + MI (own hand)) were randomly performed on 10 stroke patients. MI vividness was significantly higher when the inverted image of the nonparalyzed upper limb was presented compared to the other conditions (p < 0.01). The activity of the cortical regions was also significantly enhanced (p < 0.01). Our study highlights the potential application of inverted images of a stroke patient’s own nonparalyzed hand in mental practice to promote the motor recovery of stroke patients. This technique achieved higher levels of MI vividness and cortical activity when performing motor tasks.

Brain Function and Upper Limb Deficit in Stroke With Motor Execution and Imagery: A Cross-Sectional Functional Magnetic Resonance Imaging Study

Background

Motor imagery training might be helpful in stroke rehabilitation. This study explored if a specific modulation of movement-related regions is related to motor imagery (MI) ability.

Methods

Twenty-three patients with subcortical stroke and 21 age-matched controls were recruited. They were subjectively screened using the Kinesthetic and Visual Imagery Questionnaire (KVIQ). They then underwent functional magnetic resonance imaging (fMRI) while performing three repetitions of different motor tasks (motor execution and MI). Two separate runs were acquired [motor execution tasks (ME and rest) and motor imagery (MI and rest)] in a block design. For the different tasks, analyses of cerebral activation and the correlation of motor/imagery task-related activity and KVIQ scores were performed.

Results

During unaffected hand (UH) active grasp movement, we observed decreased activations in the contralateral precentral gyrus (PreCG), contralateral postcentral gyrus (PoCG) [p &lt; 0.05, family wise error (FWE) corrected] and a positive correlation with the ability of FMA-UE (PreCG: r = 0.46, p = 0.028; PoCG: r = 0.44, p = 0.040). During active grasp of the affected hand (AH), decreased activation in the contralateral PoCG was observed (p &lt; 0.05, FWE corrected). MI of the UH induced significant activations of the contralateral superior frontal gyrus, opercular region of the inferior frontal gyrus, and ipsilateral ACC and deactivation in the ipsilateral supplementary motor area (p &lt; 0.05, AlphaSim correction). Ipsilateral anterior cingulate cortex (ACC) activity negatively correlated with MI ability (r = =–0.49, p = 0.022). Moreover, we found significant activation of the contralesional middle frontal gyrus (MFG) during MI of the AH.

Conclusion

Our results proved the dominant effects of MI dysfunction that exist in stroke during the processing of motor execution. In the motor execution task, the enhancement of the contralateral PreCG and PoCG contributed to reversing the motor dysfunction, while in the MI task, inhibition of the contralateral ACC can increase the impaired KVIQ ability. The bimodal balance recovery model can explain our results well. Recognizing neural mechanisms is critical to helping us formulate precise strategies when intervening with electrical or magnetic stimulation.

Emerging Limb Rehabilitation Therapy After Post-stroke Motor Recovery

Stroke, including hemorrhagic and ischemic stroke, refers to the blood supply disorder in the local brain tissue for various reasons (aneurysm, occlusion, etc.). It leads to regional brain circulation imbalance, neurological complications, limb motor dysfunction, aphasia, and depression. As the second-leading cause of death worldwide, stroke poses a significant threat to human life characterized by high mortality, disability, and recurrence. Therefore, the clinician has to care about the symptoms of stroke patients in the acute stage and formulate an effective postoperative rehabilitation plan to facilitate the recovery in patients. We summarize a novel application and update of the rehabilitation therapy in limb motor rehabilitation of stroke patients to provide a potential future stroke rehabilitation strategy.

The brain state of motor imagery is reflected in the causal information of functional near-infrared spectroscopy

BACKGROUND

Brain-computer interface (BCI) is a promising neurorehabilitation strategy for ameliorating post-stroke function disorders. Physiological changes in the brain, such as functional near-infrared spectroscopy (fNIRS) dedicated to exploring cerebral circulatory responses during neurological rehabilitation tasks, are essential for gaining insights into neurorehabilitation mechanisms. However, the relationship between the neurovascular responses in different brain regions under rehabilitation tasks remains unknown.

OBJECTIVE

The present study explores the fNIRS interactions between brain regions under different motor imagery (MI) tasks, emphasizing functional characteristics of brain network patterns and BCI motor task classification.

METHODS

Granger causality analysis (GCA) is carried out for oxyhemoglobin data from 29 study participants in left- and right-hand MI tasks.

RESULTS

According to research findings, homozygous and heterozygous states in the two brain connectivity modes reveal one and nine channel pairs, respectively, with significantly different (P < 0.05) GC values under the left- and right-hand MI tasks in the population. With reference to the total 10 channel pairs of causality differences between the two brain working states, a support vector machine is used to classify the two tasks with an overall accuracy of 83% for five-fold cross-validation.

CONCLUSION

As demonstrated in the present study, fNIRS offers causality patterns in different brain states of MIBCI motor tasks. The research findings show that fNIRS causality can be used to assess different states of the brain, providing theoretical support for its application to neurorehabilitation assessment protocols to ultimately improve patients' quality of life.Video Abstract: http://links.lww.com/WNR/A653.

Motor imagery and gait control in Parkinson's disease: techniques and new perspectives in neurorehabilitation

INTRODUCTION

Motor imagery (MI), defined as the ability to mentally represent an action without actual movement, has been used to improve motor function in athletes and, more recently, in neurological disorders such as Parkinson's disease (PD). Several studies have investigated the neural correlates of motor imagery, which change also depending on the action imagined.

AREAS COVERED

This review focuses on locomotion, which is a crucial activity in everyday life and is often impaired by neurological conditions. After a general discussion on the neural correlates of motor imagery and locomotion, we review the evidence highlighting the abnormalities in gait control and gait imagery in PD patients. Next, new perspectives and techniques for PD patients' rehabilitation are discussed, namely Brain Computer Interfaces (BCIs), neurofeedback, and virtual reality (VR).

EXPERT OPINION

Despite the few studies, the literature review supports the potential beneficial effects of motor imagery interventions in PD focused on locomotion. The development of new technologies could empower the administration of training based on motor imagery locomotor tasks, and their application could lead to new rehabilitation protocols aimed at improving walking ability in patients with PD.

Motor imagery practice and feedback effects on functional connectivity

- Objective: the use of motor imagery (MI) in motor rehabilitation protocols has been increasingly investigated as a potential technique for enhancing traditional treatments, yielding better clinical outcomes. However, since MI performance can be challenging, practice is usually required. This demands appropriate training, actively engaging the MI-related brain areas, consequently enabling the user to properly benefit from it. The role of feedback is central for MI practice. Yet, assessing which underlying neural changes are feedback-specific or purely due to MI practice is still a challenging effort, mainly due to the difficulty in isolating their contributions. In this work, we aimed to assess functional connectivity (FC) changes following MI practice that are either extrinsic or specific to feedback.

APPROACH

to achieve this, we investigated FC, using graph theory, in electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data, during MI performance and at resting-state (rs), respectively. Thirty healthy subjects were divided into three groups, receiving no feedback (control), "false" feedback (sham) or actual neurofeedback (active). Participants underwent 12 to 13 hands-MI EEG sessions and pre- and post-MI training fMRI exams.

MAIN RESULTS

following MI practice, control participants presented significant increases in degree and in eigenvector centrality for occipital nodes at rs-fMRI scans, whereas sham-feedback produced similar effects, but to a lesser extent. Therefore, MI practice, by itself, seems to stimulate visual information processing mechanisms that become apparent during basal brain activity. Additionally, only the active group displayed decreases in inter-subject FC patterns, both during MI performance and at rs-fMRI.

SIGNIFICANCE

hence, actual neurofeedback impacted FC by disrupting common inter-subject patterns, suggesting that subject-specific neural plasticity mechanisms become important. Future studies should consider this when designing experimental NFBT protocols and analyses.

A method for using video presentation to increase the vividness and activity of cortical regions during motor imagery tasks

In recent years, mental practice (MP) using laterally inverted video of a subject's non-paralyzed upper limb to improve the vividness of presented motor imagery (MI) has been shown to be effective for improving the function of a paralyzed upper limb. However, no studies have yet assessed the activity of cortical regions engaged during MI task performance using inverse video presentations and neurophysiological indicators. This study sought to investigate changes in MI vividness and hemodynamic changes in the cerebral cortex during MI performance under the following three conditions in near-infrared spectroscopy: MI-only without inverse video presentation (MI-only), MI with action observation (AO) of an inverse video presentation of another person's hand (AO + MI (other hand)), and MI with AO of an inverse video presentation of a participant's own hand (AO + MI (own hand)). Participants included 66 healthy right-handed adults (41 men and 25 women; mean age: 26.3 ± 4.3 years). There were 23 patients in the MI-only group (mean age: 26.4 ± 4.1 years), 20 in the AO + MI (other hand) group (mean age: 25.9 ± 5.0 years), and 23 in the AO + MI (own hand) group (mean age: 26.9 ± 4.1 years). The MI task involved transferring 1 cm × 1 cm blocks from one plate to another, once per second, using chopsticks held in the non-dominant hand. Based on a visual analog scale (VAS), MI vividness was significantly higher in the AO + MI (own hand) group than in the MI-only group and the AO + MI (other hand) group. A main effect of condition was revealed in terms of MI vividness, as well as regions of interest (ROIs) in certain brain areas associated with motor processing. The data suggest that inverse video presentation of a person's own hand enhances the MI vividness and increases the activity of motor-related cortical areas during MI. This study was approved by the Institutional Ethics Committee of Nagasaki University Graduate School of Biomedical and Health Sciences (approval No. 18121303) on January 18, 2019.

Mirror therapy in upper limb motor recovery and activities of daily living, and its neural correlates in stroke individuals: A systematic review and meta-analysis

Available literature indicates that 30-66% of stroke survivors present persistent upper limb impairment. Considering the importance of upper limb function for activities of daily living, it is necessary to investigate neurorehabilitation therapies that could improve the upper limb function. Among stroke complementary therapies, mirror therapy has shown promising results. Thus, the aim of this systematic review and meta-analyses was to review and synthesize clinical evidence on the use of mirror therapy on motor recovery of the upper limb and activities of daily living, and its neural correlates in stroke patients. The literature search was carried out in PubMed, ISI Web of Science, and Scopus databases. Twenty-nine studies met all the inclusion criteria. Two meta-analyses were conducted to compare mirror therapy with sham therapy on two general measures, upper limb assessment and activities of daily living. Results suggest that mirror therapy was better than sham therapy, mainly in the subacute phase, but the meta-analyses were nonsignificant. In addition, mirror therapy and cortical reorganization showed potential neural correlates, such as the primary motor cortex, precuneus, and posterior cingulate cortex.

App-based data collection, mental imagery, and naming performance in adults with aphasia

BACKGROUND AND PURPOSE

Naming impairments are often found in aphasia. Combining mHealth technology with mental imagery may offer new insights into novel approaches to naming interventions in persons with aphasia. The aims of this study are to (1) explore whether mental imagery can improve performance during a naming task in adults with aphasia; and, (2) demonstrate the use of app-based data collection for research in aphasia rehabilitation through utilization of an app designed specifically for this study.

MATERIALS AND METHODS

A single subject non-concurrent multiple baseline design across participants was utilized. Four participants with anomic and conduction aphasia were included. Each participant's percentage of naming accuracy was measured before the initiating intervention to establish a baseline level of performance.

RESULTS

Per overlap metrics, two of the participants demonstrated a strong effect in improving naming from baseline to intervention on items using the app. Two participants showed no effect in naming accuracy from the imagery intervention.

CONCLUSION

Some participants showed improvement in naming items following an imagery script, suggesting that this complementary health practice should continue to be explored. Additionally, this study demonstrates the successful use of app-based data collection.

Comparison of cerebral activation between motor execution and motor imagery of self-feeding activity

Motor imagery is defined as an act wherein an individual contemplates a mental action of motor execution without apparent action. Mental practice executed by repetitive motor imagery can improve motor performance without simultaneous sensory input or overt output. We aimed to investigate cerebral hemodynamics during motor imagery and motor execution of a self-feeding activity using chopsticks. This study included 21 healthy right-handed volunteers. The self-feeding activity task comprised either motor imagery or motor execution of eating sliced cucumber pickles with chopsticks to examine eight regions of interest: pre-supplementary motor area, supplementary motor area, bilateral prefrontal cortex, premotor area, and sensorimotor cortex. The mean oxyhemoglobin levels were detected using near-infrared spectroscopy to reflect cerebral activation. The mean oxyhemoglobin levels during motor execution were significantly higher in the left sensorimotor cortex than in the supplementary motor area and the left premotor area. Moreover, significantly higher oxyhemoglobin levels were detected in the supplementary motor area and the left premotor area during motor imagery, compared to motor execution. Supplementary motor area and premotor area had important roles in the motor imagery of self-feeding activity. Moreover, the activation levels of the supplementary motor area and the premotor area during motor execution and motor imagery are likely affected by intentional cognitive processes. Levels of cerebral activation differed in some areas during motor execution and motor imagery of a self-feeding activity. This study was approved by the Ethical Review Committee of Nagasaki University (approval No. 18110801) on December 10, 2018.

Applications of Functional Magnetic Resonance Imaging in Determining the Pathophysiological Mechanisms and Rehabilitation of Spatial Neglect

Functional magnetic resonance imaging (fMRI) is a neuroimaging tool which has been applied extensively to explore the pathophysiological mechanisms of neurological disorders. Spatial neglect is considered to be the failure to attend or respond to stimuli on the side of the space or body opposite a cerebral lesion. In this review, we summarize and analyze fMRI studies focused specifically on spatial neglect. Evidence from fMRI studies have highlighted the role of dorsal and ventral attention networks in the pathophysiological mechanisms of spatial neglect, and also support the concept of interhemispheric rivalry as an explanatory model. fMRI studies have shown that several rehabilitation methods can induce activity changes in brain regions implicated in the control of spatial attention. Future investigations with large study cohorts and appropriate subgroup analyses should be conducted to confirm the possibility that fMRI might offer an objective standard for predicting spatial neglect and tracking the response of brain activity to clinical treatment, as well as provide biomarkers to guide rehabilitation for patients with SN.

A BCI System Based on Motor Imagery for Assisting People with Motor Deficiencies in the Limbs

Motor deficiencies constitute a significant problem affecting millions of people worldwide. Such people suffer from a debility in daily functioning, which may lead to decreased and incoherence in daily routines and deteriorate their quality of life (QoL). Thus, there is an essential need for assistive systems to help those people achieve their daily actions and enhance their overall QoL. This study proposes a novel brain–computer interface (BCI) system for assisting people with limb motor disabilities in performing their daily life activities by using their brain signals to control assistive devices. The extraction of useful features is vital for an efficient BCI system. Therefore, the proposed system consists of a hybrid feature set that feeds into three machine-learning (ML) classifiers to classify motor Imagery (MI) tasks. This hybrid feature selection (FS) system is practical, real-time, and an efficient BCI with low computation cost. We investigate different combinations of channels to select the combination that has the highest impact on performance. The results indicate that the highest achieved accuracies using a support vector machine (SVM) classifier are 93.46% and 86.0% for the BCI competition III–IVa dataset and the autocalibration and recurrent adaptation dataset, respectively. These datasets are used to test the performance of the proposed BCI. Also, we verify the effectiveness of the proposed BCI by comparing its performance with recent studies. We show that the proposed system is accurate and efficient. Future work can apply the proposed system to individuals with limb motor disabilities to assist them and test their capability to improve their QoL. Moreover, the forthcoming work can examine the system’s performance in controlling assistive devices such as wheelchairs or artificial limbs.

Home-based motor imagery intervention improves functional performance following total knee arthroplasty in the short term: a randomized controlled trial

BACKGROUND

Motor imagery (MI) is effective in improving motor performance in the healthy asymptomatic adult population. However, its possible effects among older orthopaedic patients are still poorly investigated. Therefore, this study explored whether the addition of motor imagery to routine physical therapy reduces the deterioration of quadriceps muscle strength and voluntary activation (VA) as well as other variables related to motor performance in patients after total knee arthroplasty (TKA).

METHODS

Twenty-six patients scheduled for TKA were randomized to either MI practice combined with routine physical therapy group (MIp) or to a control group receiving physical therapy alone (CON). MIp consisted of maximal voluntary isometric contraction (MViC) task: 15 min/day in the hospital, then 5 times/week in their homes for 4 weeks. MViC and VA of quadriceps muscle, knee flexion and extension range of motion, pain level, along with a Timed Up-and-Go Test (TUG) and self-reported measure of physical function (assessed using the Oxford Knee Score questionnaire [OKS]) were evaluated before (PRE) and 1 month after surgery (POST).

RESULTS

Significantly better rehabilitation outcomes were evident on the operated leg for the MIp group compared to CON: at POST, the MIp showed lower strength decrease (p = 0.012, η2 = 0.237) and unaltered VA, significantly greater than CON (p = 0.014, η2 = 0.227). There were no significant differences in knee flexion and extension range of motion and pain level (p > 0.05). Further, MIp patients performed better in TUG (p < 0.001, η2 = 0.471) and reported better OKS scores (p = 0.005, η2 = 0.280). The non-operated leg showed no significant differences in any outcomes at POST (all p > 0.05). In addition, multiple linear regression analysis showed that failure of voluntary activation explained 47% of the quadriceps muscle strength loss, with no significant difference in perceived level of pain.

CONCLUSION

MI practice, when added to physical therapy, improves both objective and subjective measures of patients' physical function after TKA, and facilitates transfer of MI strength task on functional mobility.

TRIAL REGISTRATION

Retrospectively registered on ClinicalTrials.gov NCT03684148.

Improving Real-Time Brain State Classification of Motor Imagery Tasks During Neurofeedback Training

In this study, we investigated the effect of the dynamic changes in brain activation during neurofeedback training in the classification of the different brain states associated with the target tasks. We hypothesized that ongoing activation patterns could change during neurofeedback session due to learning effects and, in the process, could affect the performance of brain state classifiers trained using data obtained prior to the session. Using a motor imagery paradigm, we then examined the application of an incremental training approach where classifiers were continuously updated in order to account for these activation changes. Our results confirmed our hypothesis that neurofeedback training could be associated with dynamic changes in brain activation characterized by an initially more widespread brain activation followed by a more focused and localized activation pattern. By continuously updating the trained classifiers after each feedback run, significant improvement in accurately classifying the different brain states associated with the target motor imagery tasks was achieved. These findings suggest the importance of taking into account brain activation changes during neurofeedback in order to provide more reliable and accurate feedback information to the participants, which is critical for an effective neurofeedback application.

On the (in)efficacy of motor imagery training without feedback and event-related desynchronizations considerations

Motor imagery (MI) constitutes a recurrent strategy for signals generation in brain-computer interfaces (BCIs) - systems that aim to control external devices by directly associating brain responses to distinct commands. Although great improvement has been achieved in MI-BCIs performance over recent years, they still suffer from inter- and intra-subject variability issues. As an attempt to cope with this, some studies have suggested that MI training should aid users to appropriately modulate their response for BCI usage: generally, this training is performed based on the sensorimotor rhythms' modulation over the primary sensorimotor cortex (PMC), with the signal being feedbacked to the user. Nonetheless, recent studies have revisited the actual involvement of the PMC into MI, and little to no attention has been devoted to understanding the participation of other cortical areas into training protocols. Therefore, in this work, our aim was to analyze the response induced by hands MI of 10 healthy subjects in the form of event-related desynchronizations (ERDs) and to assess whether features from beyond the PMC might be useful for hands MI classification. We investigated how this response occurs for distinct frequency intervals between 7-30 Hz, and ex0plored changes in their evocation pattern across 12 MI training sessions without feedback. Overall, we found that ERD patterns occur differently for the frequencies encompassed by the μ and β bands, with its evocation being favored for the first band. Over time, the no-feedback approach was inefficient to aid in enhancing ERD evocation (EO). Moreover, to some extent, EO tends to decrease over blocks within a given run, and runs within an MI session, but remains stable within an MI block. We also found that the C3/C4 pair is not necessarily optimal for data classification, and both spectral and spatial subjects' specificities should be considered when designing training protocols.

The Effects of Instruction Manipulation on Motor Performance Following Action Observation

The effects of action observation (AO) on motor performance can be modulated by instruction. The effects of two top-down aspects of the instruction on motor performance have not been fully resolved: those related to attention to the observed task and the incorporation of motor imagery (MI) during AO. In addition, the immediate vs. 24-h retention test effects of those instruction’s aspects are yet to be elucidated. Forty-eight healthy subjects were randomly instructed to: (1) observe reaching movement (RM) sequences toward five lighted units with the intention of reproducing the same sequence as fast and as accurate as possible (Intentional + Attentional group; AO+At); (2) observe the RMs sequence with the intention of reproducing the same sequence as fast and as accurate as possible and simultaneously to the observation to imagine performing the RMs (Intentional + attentional + MI group; AO+At+MI); and (3) observe the RMs sequence (Passive AO group). Subjects’ performance was tested before and immediately after the AO and retested after 24 h. During each of the pretest, posttest, and retest, the subject performed RMs toward the units that were activated in the same order as the observed sequence. Occasionally, the sequence order was changed by beginning the sequence with a different activated unit. The outcome measures were: averaged response time of the RMs during the sequences, difference between the response time of the unexpected and expected RMs and percent of failures to reach the target within 1 s. The averaged response time and the difference between the response time of the unexpected and expected RMs were improved in all groups at posttest compared to pretest, regardless of instruction. Averaged response time was improved in the retest compared to the posttest only in the Passive AO group. The percent of failures across groups was higher in pretest compared to retest. Our findings suggest that manipulating top-down aspects of instruction by adding attention and MI to AO in an RM sequence task does not improve subsequent performance more than passive observation. Off-line learning of the sequence in the retention test was improved in comparison to posttest following passive observation only.

Low-Cost Robotic Guide Based on a Motor Imagery Brain-Computer Interface for Arm Assisted Rehabilitation

Motor imagery has been suggested as an efficient alternative to improve the rehabilitation process of affected limbs. In this study, a low-cost robotic guide is implemented so that linear position can be controlled via the user’s motor imagination of movement intention. The patient can use this device to move the arm attached to the guide according to their own intentions. The first objective of this study was to check the feasibility and safety of the designed robotic guide controlled via a motor imagery (MI)-based brain–computer interface (MI-BCI) in healthy individuals, with the ultimate aim to apply it to rehabilitation patients. The second objective was to determine which are the most convenient MI strategies to control the different assisted rehabilitation arm movements. The results of this study show a better performance when the BCI task is controlled with an action–action MI strategy versus an action–relaxation one. No statistically significant difference was found between the two action–action MI strategies.

Nonlinear Analysis of Eye-Tracking Information for Motor Imagery Assessments

This study investigates the assessment of motor imagery (MI) ability in humans. Commonly, MI ability is measured through two methodologies: a self-administered questionnaire (MIQ-3) and the mental chronometry (MC), which measures the temporal discrepancy between the actual and the imagined motor tasks. However, both measures rely on subjects' self-assessment and do not use physiological measures. In this study, we propose a novel set of features extracted from the nonlinear dynamics of the eye gaze signal to discriminate between good and bad imagers. To this aim, we designed an experiment where twenty volunteers, categorized as good or bad imagers according to MC, performed three tasks: a motor task (MT), a visual Imagery task (VI), and a kinaesthetic Imagery task (KI). Throughout the experiment, the subjects' eye gaze was continuously monitored using an eye-tracking system. Eye gaze time series were analyzed through recurrence quantification analysis of the reconstructed phase space and compared between the two groups. Statistical results have shown how nonlinear eye behavior can express an inner dynamics of imagery mental process and may be used as a more objective and physiological-based measure of MI ability.

The effects of mental practice based on motor imagery for mobility recovery after subacute stroke: Protocol for a randomized controlled trial

BACKGROUND AND PURPOSE

Mental practice of motor imagery has shown beneficial effects in stroke recovery. However, there are few clinical trials investigating it on the subacute phase. This study will investigate the effects of mental practice in the mobility of patients with subacute stroke.

MATERIALS AND METHODS

Randomized controlled trial including persons with subacute stroke (<3 months). All participants will receive physical exercises and will be randomly allocated into an experimental group (Mental Practice) or into a control group (cognitive training) for 4 weeks(12 sessions).

RESULTS

Primary outcomes will be assessed at baseline and after intervention and will be related to mobility, using Timed Up and Go test and 5 m walking speed test. Whereas secondary outcomes will be muscular strength, biomechanical strategies, mental health and quality of life.

CONCLUSION

The beneficial effects that may be found in this trial can be greatly relevant in clinical practice, justifying this scientific question.

Effectiveness and Superiority of Rehabilitative Treatments in Enhancing Motor Recovery Within 6 Months Poststroke: A Systemic Review

OBJECTIVE

To investigate the effects of various rehabilitative interventions aimed at enhancing poststroke motor recovery by assessing their effectiveness when compared with no treatment or placebo and their superiority when compared with conventional training program (CTP).

DATA SOURCE

A literature search was based on 19 Cochrane reviews and 26 other reviews. We also updated the searches in PubMed up to September 30, 2017.

STUDY SELECTION

Randomized controlled trials associated with 18 experimented training programs (ETP) were included if they evaluated the effects of the programs on either upper extremity (UE) or lower extremity (LE) motor recovery among adults within 6 months poststroke; included ≥10 participants in each arm; and had an intervention duration of ≥10 consecutive weekdays.

DATA EXTRACTION

Four reviewers evaluated the eligibility and quality of literature. Methodological quality was assessed using the PEDro scale.

DATA SYNTHESIS

Among the 178 included studies, 129 including 7450 participants were analyzed in this meta-analysis. Six ETPs were significantly effective in enhancing UE motor recovery, with the standard mean differences (SMDs) and 95% confidence intervals outlined as follow: constraint-induced movement therapy (0.82, 0.45-1.19), electrostimulation (ES)-motor (0.42, 0.22-0.63), mirror therapy (0.71, 0.22-1.20), mixed approach (0.21, 0.01-0.41), robot-assisted training (0.51, 0.22-0.80), and task-oriented training (0.57, 0.16-0.99). Six ETPs were significantly effective in enhancing LE motor recovery: body-weight-supported treadmill training (0.27, 0.01-0.52), caregiver-mediated training (0.64, 0.20-1.08), ES-motor (0.55, 0.27-0.83), mixed approach (0.35, 0.15-0.54), mirror therapy (0.56, 0.13-1.00), and virtual reality (0.60, 0.15-1.05). However, compared with CTPs, almost none of the ETPs exhibited significant SMDs for superiority.

CONCLUSIONS

Certain experimented interventions were effective in enhancing poststroke motor recovery, but little evidence supported the superiority of experimented interventions over conventional rehabilitation.

Effects of Real-Time (Sonification) and Rhythmic Auditory Stimuli on Recovering Arm Function Post Stroke: A Systematic Review and Meta-Analysis

Background: External auditory stimuli have been widely used for recovering arm function post-stroke. Rhythmic and real-time auditory stimuli have been reported to enhance motor recovery by facilitating perceptuomotor representation, cross-modal processing, and neural plasticity. However, a consensus as to their influence for recovering arm function post-stroke is still warranted because of high variability noted in research methods. Objective: A systematic review and meta-analysis was carried out to analyze the effects of rhythmic and real-time auditory stimuli on arm recovery post stroke. Method: Systematic identification of published literature was performed according to PRISMA guidelines, from inception until December 2017, on online databases: Web of science, PEDro, EBSCO, MEDLINE, Cochrane, EMBASE, and PROQUEST. Studies were critically appraised using PEDro scale. Results: Of 1,889 records, 23 studies which involved 585 (226 females/359 males) patients met our inclusion criteria. The meta-analysis revealed beneficial effects of training with both types of auditory inputs for Fugl-Meyer assessment (Hedge's g: 0.79), Stroke impact scale (0.95), elbow range of motion (0.37), and reduction in wolf motor function time test (-0.55). Upon further comparison, a beneficial effect of real-time auditory feedback was found over rhythmic auditory cueing for Fugl-meyer assessment (1.3 as compared to 0.6). Moreover, the findings suggest a training dosage of 30 min to 1 h for at least 3-5 sessions per week with either of the auditory stimuli. Conclusion: This review suggests the application of external auditory stimuli for recovering arm functioning post-stroke.

A functional limitation to the lower limbs affects the neural bases of motor imagery of gait

Studies on athletes or neurological patients with motor disorders have shown a close link between motor experience and motor imagery skills. Here we evaluated whether a functional limitation due to a musculoskeletal disorder has an impact on the ability to mentally rehearse the motor patterns of walking, an overlearned and highly automatic behaviour. We assessed the behavioural performance (measured through mental chronometry tasks) and the neural signatures of motor imagery of gait in patients with chronic knee arthrosis and in age-matched, healthy controls. During fMRI, participants observed (i) stationary or (ii) moving videos of a path in a park shown in the first-person perspective: they were asked to imagine themselves (i) standing on or (ii) walking along the path, as if the camera were “their own eyes” (gait imagery (GI) task). In half of the trials, participants performed a dynamic gait imagery (DGI) task by combining foot movements with GI. Behavioural tests revealed a lower degree of isochrony between imagined and performed walking in the patients, indicating impairment in the ability to mentally rehearse gait motor patterns. Moreover, fMRI showed widespread hypoactivation during GI in motor planning (premotor and parietal) brain regions, the brainstem, and the cerebellum. Crucially, the performance of DGI had a modulatory effect on the patients and enhanced activation of the posterior parietal, brainstem, and cerebellar regions that the healthy controls recruited during the GI task. These findings show that functional limitations of peripheral origin may impact on gait motor representations, providing a rationale for cognitive rehabilitation protocols in patients with gait disorders of orthopaedic nature. The DGI task may be a suitable tool in this respect.

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Patients with chronic knee arthrosis show impairment in gait motor imagery

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Impairment is selective for gait and paralleled by hypoactivation in premotor areas

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Peripheral limitation of lower limb movements affects central gait motor control

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Dynamic motor imagery favours the recruitment of a motor strategy during imagery

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Mental motor training might help to restore gait control in orthopaedic patients

Improved Volitional Recall of Motor-Imagery-Related Brain Activation Patterns Using Real-Time Functional MRI-Based Neurofeedback

Motor imagery (MI), a covert cognitive process where an action is mentally simulated but not actually performed, could be used as an effective neurorehabilitation tool for motor function improvement or recovery. Recent approaches employing brain–computer/brain–machine interfaces to provide online feedback of the MI during rehabilitation training have promising rehabilitation outcomes. In this study, we examined whether participants could volitionally recall MI-related brain activation patterns when guided using neurofeedback (NF) during training. The participants’ performance was compared to that without NF. We hypothesized that participants would be able to consistently generate the relevant activation pattern associated with the MI task during training with NF compared to that without NF. To assess activation consistency, we used the performance of classifiers trained to discriminate MI-related brain activation patterns. Our results showed significantly higher predictive values of MI-related activation patterns during training with NF. Additionally, this improvement in the classification performance tends to be associated with the activation of middle temporal gyrus/inferior occipital gyrus, a region associated with visual motion processing, suggesting the importance of performance monitoring during MI task training. Taken together, these findings suggest that the efficacy of MI training, in terms of generating consistent brain activation patterns relevant to the task, can be enhanced by using NF as a mechanism to enable participants to volitionally recall task-related brain activation patterns.

Muscle Activation During Grasping With and Without Motor Imagery in Healthy Volunteers and Patients After Stroke or With Parkinson's Disease

Introduction: The present study assessed whether motor imagery (MI) produces electromyographic activation in specific muscles of the upper limb during a hand grasping and arm-lifting task in healthy volunteers, patients after stroke, or with Parkinson's disease. Electromyographic (EMG) activation was compared under three conditions: MI, physical execution (PE), and rest. The task is clinically relevant unilateral executed movement using open muscle chains.

Methods: In a cross-sectional study EMG activation was measured in four muscles: M. deltoideus pars clavicularis, M. biceps brachii, M. extensor digitorum, M. flexor carpi radialis. MI ability was evaluated with mental rotation, mental chronometry and the Kinaesthetic and Visual Imagery Questionnaire. Cognitive performance was screened with the Mini-Mental State Examination.

Results: Twenty-two participants (11 females, age 52.6 ±15.8, age range 21 to 72) were included: ten healthy volunteers, seven patients after stroke (time after stroke onset 16.3 ± 24.8 months), and five patients with Parkinson's disease (disease duration 60.4 ± 24.5 months). Overall Mini-Mental State Examination scores ranged between 27 and 30. An increased EMG activation during MI compared to rest condition was observed in M. deltoideus pars clavicularis and M. biceps brachii across all participants (p-value = 0.001, p = 0.007). Seven participants (two healthy volunteers, three patients after stroke and two patients with Parkinson's disease) showed a EMG activation during MI of the hand grasping and arm-lifting task in at least one of the target muscles. No correlation between EMG activation during MI and scores of three MI ability assessments were found.

Conclusions: The findings suggest that MI can yield subliminal EMG activation. However, that might vary on individual basis. It remains unclear what parameters contribute to or inhibit an EMG activation during MI. Future investigations should determine factors that influence EMG activation, e.g. MI instructions, tasks to imagine, amount of MI training, and longitudinal changes after an MI training period.

Motor imagery training induces changes in brain neural networks in stroke patients

Motor imagery is the mental representation of an action without overt movement or muscle activation. However, the effects of motor imagery on stroke-induced hand dysfunction and brain neural networks are still unknown. We conducted a randomized controlled trial in the China Rehabilitation Research Center. Twenty stroke patients, including 13 males and 7 females, 32–51 years old, were recruited and randomly assigned to the traditional rehabilitation treatment group (PP group, n = 10) or the motor imagery training combined with traditional rehabilitation treatment group (MP group, n = 10). All patients received rehabilitation training once a day, 45 minutes per session, five times per week, for 4 consecutive weeks. In the MP group, motor imagery training was performed for 45 minutes after traditional rehabilitation training, daily. Action Research Arm Test and the Fugl-Meyer Assessment of the upper extremity were used to evaluate hand functions before and after treatment. Transcranial magnetic stimulation was used to analyze motor evoked potentials in the affected extremity. Diffusion tensor imaging was used to assess changes in brain neural networks. Compared with the PP group, the MP group showed better recovery of hand function, higher amplitude of the motor evoked potential in the abductor pollicis brevis, greater fractional anisotropy of the right dorsal pathway, and an increase in the fractional anisotropy of the bilateral dorsal pathway. Our findings indicate that 4 weeks of motor imagery training combined with traditional rehabilitation treatment improves hand function in stroke patients by enhancing the dorsal pathway. This trial has been registered with the Chinese Clinical Trial Registry (registration number: ChiCTR-OCH-12002238).

Effect of motor imagery training and electromyogram-triggered neuromuscular electrical stimulation on lower extremity function in stroke patients: a pilot trial

[Purpose] To investigate the effect of motor imagery training and electromyogram-triggered neuromuscular electrical stimulation (MIT-EMG NMES) on the lower extremity function of stroke patients. [Subjects and Methods] This study recruited eight patients with hemiplegia due to stroke. All patients received MIT-EMG NMES for 20 min daily, 5 days per week for 4 weeks. Lower extremity function were assessed using the timed up-and-go (TUG) and 10-meter walk (10MW) tests. [Results] The results of TUG test decreased significantly from 20.5 ± 4.5 to 14.0 ± 3.5 s, while those of 10 MW test showed a significant decrease from 21.3 ± 4.5 to 15.5 ± 3.2 m. [Conclusion] This study suggests that MIT-EMG NMES is a new rehabilitation therapy for lower extremity recovery in hemiplegic stroke patients.