ABSTRACT Transcranial direct current stimulation (tDCS) may facilitate neuroplasticity but with a limited effect when administered while stroke patients are at rest. Muscle-computer interface (MCI) training is a promising approach for training stroke patients even if they cannot produce overt movements. However, using tDCS to enhance MCI training has not been investigated. We combined bihemispheric tDCS with MCI training of the paretic wrist and examined the effectiveness of this intervention in chronic stroke patients. A crossover, double-blind, randomized trial was conducted. Twenty-six chronic stroke patients performed MCI wrist training for three consecutive days at home while receiving either real tDCS or sham tDCS in counterbalanced order and separated by at least 8 months. The primary outcome measure was the Fugl-Meyer Assessment Upper Extremity Scale (FMA-UE) which was measured one week before training, on the first training day, on the last training day, and one week after training. There was no significant difference in the baseline FMA-UE score between groups nor between intervention periods. Patients improved 3.850 ± 0.582 points in FMA-UE score when receiving real tDCS, and 0.963 ± 0.725 points when receiving sham tDCS (p=0.003). Additionally, patients also showed continuous improvement of their motor control of the MCI tasks over the training days. Our study showed that the training paradigm could lead to functional improvement in chronic stroke patients. We argue that an appropriate MCI training in combination with bihemispheric tDCS could be a useful adjuvant for neurorehabilitation in stroke patients. NEW & NOTEWORTHY Bihemispheric tDCS combined with a novel MCI training for motor control of wrist extensor can improve both proximal and distal arm function in chronic stroke patients. The training regimen can be personalized with adjustments made daily to accommodate the functional change throughout the intervention. This demonstrates that bihemispheric tDCS with MCI training could complement conventional post-stroke neurorehabilitation.

Background Effective stroke rehabilitation requires high-dose, repetitive-task training, especially during the early recovery phase. However, the usability of upper-limb rehabilitation technology in acute and subacute stroke survivors remains relatively unexplored. In this study, we introduce subacute stroke survivors to MyoGuide, a mobile training platform that employs surface electromyography (sEMG)-guided neurofeedback training that specifically targets wrist extension. Notably, the study emphasizes evaluating the platform’s usability within clinical contexts. Methods Seven subacute post-stroke patients (1 female, mean age 53.7 years, mean time post-stroke 58.9 days, mean duration per training session 48.9 min) and three therapists (one for eligibility screening, two for conducting training) participated in the study. Participants underwent ten days of supervised one-on-one wrist extension training with MyoGuide, which encompassed calibration, stability assessment, and dynamic tasks. All training records including the Level of Difficulty (LoD) and Stability Assessment Scores were recorded within the application. Usability was assessed through the System Usability Scale (SUS) and participants’ willingness to continue home-based training was gauged through a self-developed survey post-training. Therapists also documented the daily performance of participants and the extent of support required. Results The usability analysis yielded positive results, with a median SUS score of 82.5. Compared to the first session, participants significantly improved their performance at the final session as indicated by both the Stability Assessment Scores ( p = 0.010, mean = 229.43, CI = [25.74–433.11]) and the LoD ( p < 0.001; mean: 45.43, CI: [25.56–65.29]). The rate of progression differed based on the initial impairment levels of the patient. After training, participants expressed a keen interest in continuing home-based training. However, they also acknowledged challenges related to independently using the Myo armband and software. Conclusions This study introduces the MyoGuide training platform and demonstrates its usability in a clinical setting for stroke rehabilitation, with the assistance of a therapist. The findings support the potential of MyoGuide for wrist extension training in patients across a wide range of impairment levels. However, certain usability challenges, such as donning/doffing the armband and navigating the application, need to be addressed to enable independent MyoGuide training requiring only minimal supervision by a therapist.

This study describes a pipeline designed to address post-stroke compensatory movements that hinder long-term motor recovery. To achieve this goal, a markerless body tracking approach is employed to track trunk flexion during a robotic reaching task and multi-modal feedback is provided-comprising visual, audio, and haptic elements-when excessive trunk flexion occurs. Our aim is to improve the quality of robotic training targeting motor recovery. To evaluate the feasibility of this pipeline, three different phases of robotic training (Baseline, Training, and Test) are performed, with only the Training phase including the multi-modal compensatory movement feedback. The preliminary findings from a single stroke patient show the initial feasibility of the proposed pipeline, demonstrating the potential of postural adaptations facilitated by feedback. While the current report is limited to a single participant, validation with a diverse sample to test the overall feasibility and applicability across a wider range of patients is essential.

Compensatory movements are commonly observed post-stroke and can negatively affect long-term motor recovery. In this context, a system that monitors movement quality and provides feedback would be beneficial. In this study, we aimed to detect compensatory movements during seated reaching using a conventional tablet camera and an open-source markerless body pose tracking algorithm called MediaPipe [1]. We annotated compensatory movements of stroke patients per frame based on the comparison between the paretic and non-paretic arms. We trained a binary classification model using the XGBoost algorithm to detect compensatory movements, which showed an average accuracy of 0.92 (SD 0.07) in leave-one-trial-out cross-validation across four participants. Although we observed good model performance, we also encountered challenges such as missing landmarks and misalignment, when using MediaPipe Pose. This study highlights the feasibility of using near real-time compensatory movement detection with a simple camera system in stroke rehabilitation. More work is necessary to assess the generalizability of our approach across diverse groups of stroke survivors and fully implement near real-time compensatory movement detection on a mobile device.

The human brain's ability to store information and remember past events is thought to be orchestrated by the synchronization of neuronal oscillations in various frequency bands. A vast amount of research has found that neural oscillations in the theta (similar to 4-7 Hz) and alpha (similar to 8-12 Hz) bands play an important role in memory formation. More specifically, it has been suggested that memory performance benefits if the same oscillatory pattern is present during encoding and retrieval. However, the causal relevance of these oscillations is not well understood. Rhythmic sensory stimulation is thought to entrain ongoing brain oscillations and modulate associated functions (e.g., memory formation). In the present study, we used rhythmic visual stimulation at 6 and 10 Hz to experimentally modulate the memory encoding process in a recognition memory task. In addition, we reinstated oscillatory activity from the encoding episode during retrieval, which has been hypothesized to result in memory performance improvements compared to non-reinstated conditions and incongruent reinstatement. Contrary to our hypothesis, we find no effect of neural entrainment during encoding on subsequent memory performance. Likewise, memory retrieval does not benefit from neural reinstatement. The results are discussed with respect to methodological challenges of rhythmic sensory stimulation as a means to alter cognitive processes and induce context-dependent memory effects.

Background Chronic hand and wrist impairment are frequently present following stroke and severely limit independence in everyday life. The wrist orientates and stabilizes the hand before and during grasping, and is therefore of critical importance in activities of daily living (ADL). To improve rehabilitation outcomes, classical therapy could be supplemented by novel therapies that can be applied in unsupervised settings. This would enable more distributed practice and could potentially increase overall training dose. Robotic technology offers new possibilities to address this challenge, but it is critical that devices for independent training are easy and appealing to use. Here, we present the development, characterization and wearability evaluation of a fully portable exoskeleton for active wrist extension/flexion support in stroke rehabilitation. Methods First we defined the requirements, and based on these, constructed the exoskeleton. We then characterized the device with standardized haptic and human-robot interaction metrics. The exoskeleton is composed of two modules placed on the forearm/hand and the upper arm. These modules weigh 238 g and 224 g, respectively. The forearm module actively supports wrist extension and flexion with a torque up to 3.7 Nm and an angular velocity up to 530 deg/s over a range of 154 ∘ . The upper arm module includes the control electronics and battery, which can power the device for about 125 min in normal use. Special emphasis was put on independent donning and doffing of the device, which was tested via a wearability evaluation in 15 healthy participants and 2 stroke survivors using both qualitative and quantitative methods. Results All participants were able to independently don and doff the device after only 4 practice trials. For healthy participants the donning and doffing process took 61 ±15 s and 24 ±6 s, respectively. The two stroke survivors donned and doffed the exoskeleton in 54 s/22 s and 113 s/32 s, respectively. Usability questionnaires revealed that despite minor difficulties, all participants were positive regarding the device. Conclusions This study describes an actuated wrist exoskeleton which weighs less than 500 g, and which is easy and fast to don and doff with one hand. Our design has put special emphasis on the donning aspect of robotic devices which constitutes the first barrier a user will face in unsupervised settings. The proposed device is a first and intermediate step towards wearable rehabilitation technologies that can be used independently by the patient and in unsupervised settings.

Objective: Surface electromyography (sEMG) is a potentially useful signal that can provide therapeutic biofeedback. However, sEMG signal processing is difficult because of the low signal-to-noise ratio and non-stationarity of the raw signal. Conventional online filters often suffer from a compromise between smoothness and responsiveness. Here we propose a new particle filtering method for sEMG processing and compare it to established filtering methods. Methods: A wrist apparatus measuring isometric wrist extension/flexion force was developed. Six filters (moving average windowing (MAW), adaptive-MAW, 3-layer, Kalman, Bayes and particle filters) were tested on forearm sEMG collected with a Myo armband. Fourteen subjects performed two visuomotor tracking tasks (square and sine wave tracking). Tracking error, measured as the root mean square error (RMSE2), was used as a metric to compare the influence of different filters on overall performance. Results: For sine wave tracking tasks (representing continuous trajectory control), the particle filter (RMSE2: 53.30 +/- 15.69 pixels) had the lowest tracking error. For the square wave tracking task (representing discrete endpoint control), the Bayes filter (RMSE2: 37.82 +/- 23.53 pixels) had the lowest tracking error. With respect to computational requirements, the Kalman filter was the most efficient. Conclusion: Our results indicate that the filter requirements for sEMG controllers are task specific, but the new particle filtering method presented here represents a good compromise for the different types of motor control tested here. Significance: The particle filter has the potential to improve sEMG based therapeutic biofeedback. (C) 2020 Elsevier Ltd. All rights reserved.

When learning new information, contextual information about the encoding situation is stored in addition to the focal memory content. Later, these strings of extra information can help retrieve the learned content as demonstrated by experiments where contextual cues from an encoding situation facilitate remembering and improve memory performance when reinstated during retrieval. This context-dependent memory effect has been investigated over the course of several decades and has been demonstrated with many different types of contexts. Based on this, the widely held belief is that context-dependent memory is a strong and robust effect, with transferable substance for everyday learning and potential clinical applications. Here we report the results of a multi-study design investigating the influence of reinstated visual contexts on memory performance. Data from 120 participants were included in three studies comprising a variety of visual cues. We show convincingly that even rich, salient and fully surrounding visual contexts provided by virtual reality are not sufficient to induce effects of context-dependency in a free recall memory task. We also investigated contextual modulation of oscillatory brain activity in order to test the effect of reinstated neural contexts, which failed to evoke a robust effect when re-tested in an internal conceptual replication study. Moreover, a Bayesian sequential statistical analysis revealed moderate to strong evidence against the hypothesis that reinstatement of visual contexts benefits free recall memory tasks indicating that effects are small and may not be suitable for transfer into everyday learning.

Goal: Mirror movements (MM) occur during unilateral actions and manifest as involuntary muscle activity of the passive limb, "mirroring" voluntary actions executed by the contralateral homologous body part. They are a normal motor feature in young children that gradually disappears. In children suffering from neurological disorders, e.g., unilateral cerebral palsy, MMs have been proposed to yield relevant information for diagnosis and therapy. However, in clinical practice, MM are typically assessed using an ordinal rating scale. Here, we introduce the grip force tracking (GriFT) device, a portable system to quantitatively assess MM during repetitive unimanual squeezing while playing a computer game. Methods: The GriFT device consists of two handles, each equipped with two compressive force sensors (range 0-23 kg, F-z 1000 Hz). Children complete three trials of unimanual squeezing, whereby the visual display on the screen determines the squeezing rhythm (0.67 Hz at 15% maximum voluntary contraction, force-level adjusted per hand). MMs are characterized based on frequency, amplitude, and temporal features (synchronization, timing). Results: MM differed significantly between children with different clinical MM scores. MM frequency and amplitude were most discriminative. Categorization of physiological MM proved highly sensitive (89%-97%). Conclusion: We demonstrated feasibility and validity of the GriFT device in a large cohort of typically developing children (N = 174, age 5-15 years), and its clinical applicability in children with unilateral cerebral palsy with various levels of hand function. Significance: The quantification of MM is a promising tool to further investigate and categorize MM in children with unilateral cerebral palsy.

Recent work in young adults has demonstrated that motor learning can modulate resting state functional connectivity. However, evidence for older adults is scarce. Here, we investigated whether learning a bimanual tracking task modulates resting state functional connectivity of both inter- and intra-hemispheric regions differentially in young and older individuals, and whether this has behavioral relevance. Both age groups learned a set of complex bimanual tracking task variants over a 2-week training period. Resting-state and task-related functional magnetic resonance imaging scans were collected before and after training. Our analyses revealed that both young and older adults reached considerable performance gains. Older adults even obtained larger training-induced improvements relative to baseline, but their overall performance levels were lower than in young adults. Short-term practice resulted in a modulation of resting state functional connectivity, leading to connectivity increases in young adults, but connectivity decreases in older adults. This pattern of age differences occurred for both inter- and intra-hemispheric connections related to the motor network. Additionally, long-term training-induced increases were observed in intra-hemispheric connectivity in the right hemisphere across both age groups. Overall, at the individual level, the long-term changes in inter-hemispheric connectivity correlated with training-induced motor improvement. Our findings confirm that short-term task practice shapes spontaneous brain activity differentially in young and older individuals. Importantly, the association between changes in resting state functional connectivity and improvements in motor performance at the individual level may be indicative of how training shapes the short-term functional reorganization of the resting state motor network for improvement of behavioral performance.

Cross-education (CE) is the process whereby training with one limb leads to subsequent improvement in performance by the opposite untrained limb. We used multimodal neuroimaging in humans to investigate the mediating neural mechanisms by relating quantitative estimates of functional and structural cortical connectivity to individual levels of interlimb transfer. Resting-state (rs)-fMRI and diffusion weighted imaging (DWI) scans were undertaken before unilateral ballistic wrist flexion training. The rs-fMRI sequence was repeated immediately afterward. The increase in performance of the untrained limb was 83.6% of that observed for the trained limb and significantly greater than that of a control group who undertook no training. Functional connectivity in the resting motor network between right and left supplementary motor areas (SMA) was elevated after training. These changes were not, however, correlated with individual levels of transfer. Analysis of the DWI data using constrained spherical deconvolution-based tractography indicated that fractional anisotropy and apparent fiber density in tracts connecting bilateral SMA were negatively correlated with and predictive of transfer. The findings suggest that interhemispheric interactions between bilateral SMA play an instrumental role in CE and that the structural integrity of the connecting white matter pathways influences the level of transfer. SIGNIFICANCE STATEMENT Strength or skill training with one limb also brings about improvements in the performance of the opposite, untrained limb. This phenomenon, termed cross-education (CE), has obvious potential for the rehabilitation of functional capacity that has been lost through brain insult or musculoskeletal injury. The neural mechanisms that give rise to CE are, however, poorly understood. We used a combination of neuroimaging methods to investigate the pathways in the human brain that mediate CE. We determined that the supplementary motor area (SMA) plays an important role in the interlimb transfer of performance gains and demonstrate that the quality of the white matter fibers connecting right and left SMA predicts the benefit that an individual derives from CE.

Chronic wrist impairment is frequent following stroke and negatively impacts everyday life. Rehabilitation of the dysfunctional limb is possible but requires extensive training and motivation. Wearable training devices might offer new opportunities for rehabilitation. However, few devices are available to train wrist extension even though this movement is highly relevant for many upper limb activities of daily living. As a proof of concept, we developed the eWrist, a wearable one degree-of-freedom powered exoskeleton which supports wrist extension training. Conceptually one might think of an electric bike which provides mechanical support only when the rider moves the pedals, i.e. it enhances motor activity but does not replace it. Stroke patients may not have the ability to produce overt movements, but they might still be able to produce weak muscle activation that can be measured via surface electromyography (sEMG). By combining force and sEMG-based control in an assist-as-needed support strategy, we aim at providing a training device which enhances activity of the wrist extensor muscles in the context of daily life activities, thereby, driving cortical reorganization and recovery. Preliminary results show that the integration of sEMG signals in the control strategy allow for adjustable assistance with respect to a proxy measurement of corticomotor drive.

Stroke patients often suffer from severe upper limb paresis. Rehabilitation treatment typically targets motor impairments as early as possible, however, muscular contractions, particularly in the wrist and fingers, are often too weak to produce overt movements, making the initial phase of rehabilitation training difficult. Here we propose a new training tool whereby electromyographic (EMG) activity is measured in the wrist extensors and serves as a proxy of voluntary corticomotor drive. We used the Myo armband to develop a proportional EMG controller which allowed volunteers to perform a simple visuomotor task by modulating wrist extensor activity. In this preliminary study six healthy participants practiced the task for one session (144 trials), which resulted in a significant reduction of the average trial time required to move and hold a cursor in different target zones (p < 0.001, ANOVA), indicating skill learning. Additionally, we implemented an EMG based classifier to distinguish between the desired movement strategy and unwanted alternatives. Validation of the classifier indicated that accuracy for detecting rest, wrist extension and unwanted strategies was 92.5 + 6.9% (M + SD) across all participants. When performing the motor task the classification algorithm flagged 4.3 + 3.5% of the trials as 'unwanted strategies', even in healthy subjects. We also report initial feedback from a survey submitted to two chronic stroke patients to inquire about feasibility and acceptance of the general setup by patients.

Reconsolidation is observed when a consolidated stable memory is recalled, which renders it transiently labile and requires re-stabilization. Motor memory reconsolidation has previously been demonstrated using a three-day design: on day 1 the memory is encoded, on day 2 it is reactivated and experimentally manipulated, and on day 3 memory strength is tested. The aim of the current study is to determine specific boundary conditions in order to consistently degrade motor memory through reconsolidation paradigms. We investigated a sequence tapping task (n = 48) with the typical three-day design and confirmed that reactivating the motor sequence briefly (10 times tapping the learned motor sequence) destabilizes the memory trace and makes it susceptible to behavioral interference. By systematically varying the time delay between memory reactivation and interference while keeping all other aspect constant we found that a short delay (i.e., 20 s) significantly decreased performance on day 3, whereas performance was maintained or small (but not significant) improvements were observed for longer delays (i.e., 60 s). We also tested a statistical model that assumed a linear effect of the different time delays (0 s, 20 s, 40 s, 60 s) on the performance changes from day 2 to day 3. This linear model revealed a significant effect consistent with the interpretation that increasing time delays caused a gradual change from performance degradation to performance conservation across groups. These findings indicate that re-stabilizing motor sequence memories during reconsolidation does not solely rely on additional motor practice but occurs with the passage of time. This study provides further support for the hypothesis that reconsolidation is a time-dependent process with a transition phase from destabilization to re-stabilization.

Although the Morris water maze (MWM) is the most frequently used protocol to examine hippocampus-dependent learning in mice, not much is known about the spatio-temporal dynamics of underlying plasticity processes. Here, we studied molecular and cellular hippocampal plasticity mechanisms during early and late phases of spatial learning in the MWM. Quantitative in situ hybridization for the immediate early genes zif268 and Homer1a (H1a) revealed phase-dependent differences in their expression between areas CA1 and CA3. During the initial learning phase, CA1 expression levels of the molecular plasticity marker H1a, but not of the activity reporter gene zif268, were related to task proficiency; whereas no learning-specific changes could be detected in CA3. Simultaneously, the ratio of surface-expressed NMDAR subunits NR2A and NR2B was downregulated as measured by acute slice biotinylation assay, while the total number of surface NMDARs was unaltered. When intrinsic 'somatic' and synaptic plasticity in the CA1-region of hippocampal slices were examined, we found that early learning promotes intrinsic neuronal plasticity as manifested by a reduction of spike frequency adaptation and postburst afterhyperpolarization. At the synaptic level, however, maintenance of long-term potentiation (LTP) in all learning groups was impaired which is most likely due to 'intrinsic' learning-induced LTP which occluded any further electrically induced LTP. Late learning, in contrast, was characterized by re-normalized H1a, NR2A and NR2B expression and neuronal firing, yet a further strengthening of learning-induced LTP. Together, our data support a precisely timed cascade of complex molecular and subcellular transformations occurring from early to late MWM learning.

When a stable memory is reactivated it becomes transiently labile and requires restabilization, a process known as reconsolidation. Animal studies have convincingly demonstrated that during reconsolidation memories are modifiable and can be erased when reactivation is followed by an interfering intervention. Few studies have been conducted in humans, however, and results are inconsistent regarding the extent to which a memory can be degraded. We used a motor sequence learning paradigm to show that the length of reactivation constitutes a crucial boundary condition determining whether human motor memories can be degraded. In our first experiment, we found that a short reactivation (less than 60 sec) renders the memory labile and susceptible to degradation through interference, while a longer reactivation does not. In our second experiment, we reproduce these results and show a significant linear relationship between the length of memory reactivation and the detrimental effect of the interfering task performed afterwards, i.e., the longer the reactivation, the smaller the memory loss due to interference. Our data suggest that reactivation via motor execution activates a time-dependent process that initially destabilizes the memory, which is then followed by restabilization during further practice.

Both increases and decreases in resting state functional connectivity have been previously observed within the motor network during aging. Moreover, the relationship between altered functional connectivity and age‐related declines in bimanual coordination remains unclear. Here, we explored the developmental dynamics of the resting brain within a task‐specific motor network in a sample of 128 healthy participants, aged 18–80 years. We found that age‐related increases in functional connectivity between interhemispheric dorsal and ventral premotor areas were associated with poorer performance on a novel bimanual visuomotor task. Additionally, a control analysis performed on the default mode network confirmed that our age‐related increases in functional connectivity were specific to the motor system. Our findings suggest that increases in functional connectivity within the resting state motor network with aging reflect a loss of functional specialization that may not only occur in the active brain but also in the resting brain. Hum Brain Mapp 35:3945–3961, 2014 . © 2014 Wiley Periodicals, Inc .

Recent work has demonstrated that functional connectivity between remote brain regions can be modulated by task learning or the performance of an already well‐learned task. Here, we investigated the extent to which initial learning and stable performance of a spatial navigation task modulates functional connectivity between subregions of hippocampus and striatum. Subjects actively navigated through a virtual water maze environment and used visual cues to learn the position of a fixed spatial location. Resting‐state functional magnetic resonance imaging scans were collected before and after virtual water maze navigation in two scan sessions conducted 1 week apart, with a behavior‐only training session in between. There was a large significant reduction in the time taken to intercept the target location during scan session 1 and a small significant reduction during the behavior‐only training session. No further reduction was observed during scan session 2. This indicates that scan session 1 represented initial learning and scan session 2 represented stable performance. We observed an increase in functional connectivity between left posterior hippocampus and left dorsal caudate that was specific to scan session 1. Importantly, the magnitude of the increase in functional connectivity was correlated with offline gains in task performance. Our findings suggest cooperative interaction occurs between posterior hippocampus and dorsal caudate during awake rest following the initial phase of spatial navigation learning. Furthermore, we speculate that the increase in functional connectivity observed during awake rest after initial learning might reflect consolidation‐related processing. Hum Brain Mapp 36:1265–1277, 2015. © 2014 Wiley Periodicals, Inc.

Objective: Previous studies have investigated how tDCS over the primary motor cortex modulates excitability in the intrinsic hand muscles. Here, we tested if tDCS changes corticomotor excitability and/or cortical inhibition when measured in the extensor carpi radialis (ECR) and if these aftereffects can be successfully assessed during controlled muscle contraction.Methods: We implemented a double blind cross-over design in which participants (n = 16) completed two sessions where the aftereffects of 20 min of 1 mA (0.04 mA/cm(2)) anodal vs sham tDCS were tested in a resting muscle, and two more sessions where the aftereffects of anodal vs sham tDCS were tested in an active muscle.Results: Anodal tDCS increased corticomotor excitability in ECR when aftereffects were measured with a low-level controlled muscle contraction. Furthermore, anodal tDCS decreased short interval intracortical inhibition but only when measured at rest and after non-responders (n = 2) were removed. We found no changes in the cortical silent period.Conclusion: These findings suggest that targeting more proximal muscles in the upper limb with anodal tDCS is achievable and corticomotor excitability can be assessed in the presence of a low-level controlled contraction of the target muscle.