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Ischemic stroke consists of rapid neural death as a consequence of brain vessel obstruction, followed by damage to the neighboring tissue known as ischemic penumbra. The cerebral tissue in the core of the lesions becomes irreversibly damaged, however, the ischemic penumbra is potentially recoverable during the initial phases after the stroke. Therefore, there is real need for emerging therapeutic strategies to reduce ischemic damage and its spread to the penumbral region. For this reason, we tested the effect of Extreme Low Frequency Electromagnetic Stimulation (ELF-EMS) on in vitro primary neuronal and microglial cultures under oxygen-glucose deprivation (OGD) conditions. ELF-EMS under basal non-OGD conditions did not induce any effect in cell survival. However, ELF-EMS significantly reduced neuronal cell death in OGD conditions and reduced ischemic induced Ca2+ overload. Likewise, ELF-EMS modulated microglia activation and OGD-induced microglia cell death. Hence, this study suggests potential benefits in the application of ELF-EMS to limit ischemic irreversible damages under in vitro stroke conditions, encouraging in vivo preclinical validations of ELF-EMS as a potential therapeutic strategy for ischemic stroke.

BackgroundIn healthy subjects, repetitive transcranial magnetic stimulation (rTMS) targeting the primary motor cortex (M1) demonstrated plasticity effects contingent on electroencephalography (EEG)-derived excitability states, defined by the phase of the ongoing sensorimotor μ-oscillation. The therapeutic potential of brain state-dependent rTMS in the rehabilitation of upper limb motor impairment post-stroke remains unexplored.ObjectiveProof-of-concept trial to assess the efficacy of rTMS, synchronized to the sensorimotor μ-oscillation, in improving motor impairment and reducing upper-limb spasticity in stroke patients.MethodsWe conducted a parallel group, randomized double-blind controlled trial in 30 chronic stroke patients (clinical trial registration number: NCT05005780). The experimental intervention group received EEG-triggered rTMS of the ipsilesional M1 [1,200 pulses; 0.33 Hz; 100% of the resting motor threshold (RMT)], while the control group received low-frequency rTMS of the contralesional motor cortex (1,200 pulses; 1 Hz, 115% RMT), i.e., an established treatment protocol. Both groups received 12 rTMS sessions (20 min, 3× per week, 4 weeks) followed by 50 min of physiotherapy. The primary outcome measure was the change in upper-extremity Fugl-Meyer assessment (FMA-UE) scores between baseline, immediately post-treatment and 3 months’ follow-up.ResultsBoth groups showed significant improvement in the primary outcome measure (FMA-UE) and the secondary outcome measures. This included the reduction in spasticity, measured objectively using the hand-held dynamometer, and enhanced motor function as measured by the Wolf Motor Function Test (WMFT). There were no significant differences between the groups in any of the outcome measures.ConclusionThe application of brain state-dependent rTMS for rehabilitation in chronic stroke patients is feasible. This pilot study demonstrated that the brain oscillation-synchronized rTMS protocol produced beneficial effects on motor impairment, motor function and spasticity that were comparable to those observed with an established therapeutic rTMS protocol.Clinical Trial RegistrationClinicalTrials.gov, identifier [NCT05005780].

Abstract Background Previous studies showed that repetitive transcranial magnetic stimulation (rTMS) reduces spasticity after stroke. However, clinical assessments like the modified Ashworth scale, cannot discriminate stretch reflex-mediated stiffness (spasticity) from passive stiffness components of resistance to muscle stretch. The mechanisms through which rTMS might influence spasticity are also not understood. Methods We measured the effects of contralesional motor cortex 1 Hz rTMS (1200 pulses + 50 min physiotherapy: 3×/week, for 4–6 weeks) on spasticity of the wrist flexor muscles in 54 chronic stroke patients using a hand-held dynamometer for objective quantification of the stretch reflex response. In addition, we measured the excitability of three spinal mechanisms thought to be related to post-stroke spasticity: post-activation depression, presynaptic inhibition and reciprocal inhibition before and after the intervention. Effects on motor impairment and function were also assessed using standardized stroke-specific clinical scales. Results The stretch reflex-mediated torque in the wrist flexors was significantly reduced after the intervention, while no change was detected in the passive stiffness. Additionally, there was a significant improvement in the clinical tests of motor impairment and function. There were no significant changes in the excitability of any of the measured spinal mechanisms. Conclusions We demonstrated that contralesional motor cortex 1 Hz rTMS and physiotherapy can reduce the stretch reflex-mediated component of resistance to muscle stretch without affecting passive stiffness in chronic stroke. The specific physiological mechanisms driving this spasticity reduction remain unresolved, as no changes were observed in the excitability of the investigated spinal mechanisms.

Introduction: The primary constraint of non-invasive brain-machine interfaces (BMIs) in stroke rehabilitation lies in the poor spatial resolution of motor intention related neural activity capture. To address this limitation, hybrid brain-muscle-machine interfaces (hBMIs) have been suggested as superior alternatives. These hybrid interfaces incorporate supplementary input data from muscle signals to enhance the accuracy, smoothness and dexterity of rehabilitation device control. Nevertheless, determining the distribution of control between the brain and muscles is a complex task, particularly when applied to exoskeletons with multiple degrees of freedom (DoFs). Here we present a feasibility, usability and functionality study of a bio-inspired hybrid brain-muscle machine interface to continuously control an upper limb exoskeleton with 7 DoFs.Methods: The system implements a hierarchical control strategy that follows the biologically natural motor command pathway from the brain to the muscles. Additionally, it employs an innovative mirror myoelectric decoder, offering patients a reference model to assist them in relearning healthy muscle activation patterns during training. Furthermore, the multi-DoF exoskeleton enables the practice of coordinated arm and hand movements, which may facilitate the early use of the affected arm in daily life activities. In this pilot trial six chronic and severely paralyzed patients controlled the multi-DoF exoskeleton using their brain and muscle activity. The intervention consisted of 2 weeks of hBMI training of functional tasks with the system followed by physiotherapy. Patients’ feedback was collected during and after the trial by means of several feedback questionnaires. Assessment sessions comprised clinical scales and neurophysiological measurements, conducted prior to, immediately following the intervention, and at a 2-week follow-up.Results: Patients’ feedback indicates a great adoption of the technology and their confidence in its rehabilitation potential. Half of the patients showed improvements in their arm function and 83% improved their hand function. Furthermore, we found improved patterns of muscle activation as well as increased motor evoked potentials after the intervention.Discussion: This underscores the significant potential of bio-inspired interfaces that engage the entire nervous system, spanning from the brain to the muscles, for the rehabilitation of stroke patients, even those who are severely paralyzed and in the chronic phase.

Abstract Background Evidence suggests that patients suffering from different mental disorders benefit from exercise programs combined with behavior change techniques. Based on this evidence, we have developed an exercise program (ImPuls) specifically designed to provide an additional treatment option in the outpatient mental health care system. The implementation of such complex programs into the outpatient context requires research that goes beyond the evaluation of effectiveness, and includes process evaluation. So far, process evaluation related to exercise interventions has rarely been conducted. As part of a current pragmatic randomized controlled trial evaluating ImPuls treatment effects, we are therefore carrying out comprehensive process evaluation according to the Medical Research Council (MRC) framework. The central aim of our process evaluation is to support the findings of the ongoing randomized controlled trial. Methods The process evaluation follows a mixed-methods approach. We collect quantitative data via online-questionnaires from patients, exercise therapists, referring healthcare professionals and managers of outpatient rehabilitative and medical care facilities before, during, and after the intervention. In addition, documentation data as well as data from the ImPuls smartphone application are collected. Quantitative data is complemented by qualitative interviews with exercise therapists as well as a focus-group interview with managers. Treatment fidelity will be assessed through the rating of video-recorded sessions. Quantitative data analysis includes descriptive as well as mediation and moderation analyses. Qualitative data will be analyzed via qualitative content analysis. Discussion The results of our process evaluation will complement the evaluation of effectiveness and cost-effectiveness and will, for example, provide important information about mechanisms of impact, structural prerequisites, or provider qualification that may support the decision-making process of health policy stakeholders. It might contribute to paving the way for exercise programs like ImPuls to be made successively available for patients with heterogeneous mental disorders in the German outpatient mental health care system. Trial registration The parent clinical study was registered in the German Clinical Trials Register (ID: DRKS00024152, registered 05/02/2021, https://drks.de/search/en/trial/DRKS00024152 ).

Motor intention is a high-level brain function related to planning for movement. Although studies have shown that motor intentions can be decoded from brain signals before movement execution, it is unclear whether intentions relating to mental imagery of movement can be decoded. Here, we investigated whether differences in spatial and temporal patterns of brain activation were elicited by intentions to perform different types of motor imagery and whether the patterns could be used by a multivariate pattern classifier to detect such differential intentions. The results showed that it is possible to decode intentions before the onset of different types of motor imagery from functional MR signals obtained from fronto-parietal brain regions, such as the premotor cortex and posterior parietal cortex, while controlling for eye movements and for muscular activity of the hands. These results highlight the critical role played by the aforementioned brain regions in covert motor intentions. Moreover, they have substantial implications for rehabilitating patients with motor disabilities.

Objective: We evaluated the resistance to externally induced wrist extension in chronic stroke patients. We aimed to objectively measure and distinguish passive (muscle and soft tissue stiffness) and active (spasticity and spastic dystonia) components of the resistance. Methods: We used a hand-held dynamometer, which measures torque, joint movement and electromyography (EMG) simultaneously, to assess the resistance to externally induced wrist extension. Slow and fast stretches were applied to the affected and unaffected wrists in 57 chronic stroke patients (57 ± 11 years). We extracted from the data parameters that represent passive and muscle activity components and assessed the validity, test–retest reliability and the clinical utility of the measurement. Results: The analysis showed (1) a significant difference in the passive and muscle activity components between the affected and unaffected sides; (2) a significant correlation between passive and muscle activity components and the modified Ashworth scale (MAS); (3) a significant difference between the subgroups of patients stratified by the MAS; (4) an excellent intra-rater reliability on each of the passive and muscle activity components with intra-class coefficients between 0.92 and 0.99; (5) and small measurement error. Conclusions: Using a hand-held dynamometer, we were able to objectively measure the resistance to muscle stretch in the wrist joint in chronic stroke patients and discriminate muscle overactivity components from muscle and soft tissue stiffness. We demonstrated validity, test–retest reliability and the clinical utility of the measurement. Significance: Quantification of the different components of resistance to externally induced movement enables the objective evaluation of neurorehabilitation effects in chronic stroke patients.

More than 85% of stroke survivors suffer from different degrees of disability for the rest of their lives. They will require support that can vary from occasional to full time assistance. These conditions are also associated to an enormous economic impact for their families and health care systems. Current rehabilitation treatments have limited efficacy and their long-term effect is controversial. Here we review different challenges related to the design and development of neural interfaces for rehabilitative purposes. We analyze current bibliographic evidence of the effect of neuro-feedback in functional motor rehabilitation of stroke patients. We highlight the potential of these systems to reconnect brain and muscles. We also describe all aspects that should be taken into account to restore motor control. Our aim with this work is to help researchers designing interfaces that demonstrate and validate neuromodulation strategies to enforce a contingent and functional neural linkage between the central and the peripheral nervous system. We thus give clues to design systems that can improve or/and re-activate neuroplastic mechanisms and open a new recovery window for stroke patients.

Chronic constipation affects around 20% of the population and there is no efficient solution. This perspective review explores the potential of colonic electric stimulation (CES) using neural implants and methods of bioelectronic medicine as a therapeutic way to treat chronic constipation. The review covers the neurophysiology of colonic peristaltic function, the pathophysiology of chronic constipation, the technical aspects of CES, including stimulation parameters, electrode placement, and neuromodulation target selection, as well as a comprehensive analysis of various animal models highlighting their advantages and limitations in elucidating the mechanistic insights and translational relevance for CES. Finally, the main challenges and trends in CES are discussed.

IntroductionLike alpha rhythm, the somatosensory mu rhythm is suppressed in the presence of somatosensory inputs by implying cortical excitation. Sensorimotor rhythm (SMR) can be classified into two oscillatory frequency components: mu rhythm (8–13 Hz) and beta rhythm (14–25 Hz). The suppressed/enhanced SMR is a neural correlate of cortical activation related to efferent and afferent movement information. Therefore, it would be necessary to understand cortical information processing in diverse movement situations for clinical applications.MethodsIn this work, the EEG of 10 healthy volunteers was recorded while fingers were moved passively under different kinetic and kinematic conditions for proprioceptive stimulation. For the kinetics aspect, afferent brain activity (no simultaneous volition) was compared under two conditions of finger extension: (1) generated by an orthosis and (2) generated by the orthosis simultaneously combined and assisted with functional electrical stimulation (FES) applied at the forearm muscles related to finger extension. For the kinematic aspect, the finger extension was divided into two phases: (1) dynamic extension and (2) static extension (holding the extended position).ResultsIn the kinematic aspect, both mu and beta rhythms were more suppressed during a dynamic than a static condition. However, only the mu rhythm showed a significant difference between kinetic conditions (with and without FES) affected by attention to proprioception after transitioning from dynamic to static state, but the beta rhythm was not.DiscussionOur results indicate that mu rhythm was influenced considerably by muscle kinetics during finger movement produced by external devices, which has relevant implications for the design of neuromodulation and neurorehabilitation interventions.

Abstract Background Mental disorders are prevalent and cause considerable burden of disease. Exercise has been shown to be efficacious to treat major depressive disorders, insomnia, panic disorder with and without agoraphobia and post traumatic stress disorder (PTSD). Methods This pragmatic, two arm, multi-site randomised controlled trial will evaluate the efficacy and cost-effectiveness of the manualized, group-based six-months exercise intervention “ImPuls”, among physically inactive patients with major depressive disorders, insomnia, panic disorder, agoraphobia and PTSD within a naturalistic outpatient context in Germany. A minimum of 375 eligible outpatients from 10 different study sites will be block-randomized to either ImPuls in addition to treatment as usual (TAU) or TAU only. ImPuls will be conducted by trained exercise therapists and delivered in groups of six patients. The program will combine (a) moderate to vigorous aerobic exercise carried out two-three times a week for at least 30 min with (b) behavior change techniques for sustained exercise behavior change. All outcomes will be assessed pre-treatment, post-treatment (six months after randomization) and at follow-up (12 months after randomization). Primary outcome will be self-reported global symptom severity assessed with the Brief Symptom Inventory (BSI-18). Secondary outcomes will be accelerometry-based moderate to vigorous physical activity, self-reported exercise, disorder-specific symptoms, quality-adjusted life years (QALY) and healthcare costs. Intention-to-treat analyses will be conducted using mixed models. Cost-effectiveness and cost-utility analysis will be conducted using incremental cost-effectiveness and cost-utility ratios. Discussion Despite its promising therapeutic effects, exercise programs are currently not provided within the outpatient mental health care system in Germany. This trial will inform service providers and policy makers about the efficacy and cost-effectiveness of the group-based exercise intervention ImPuls within a naturalistic outpatient health care setting. Group-based exercise interventions might provide an option to close the treatment gap within outpatient mental health care settings. Trial registration The study was registered in the German Clinical Trials Register (ID: DRKS00024152 , 05/02/2021).

Brain-controlled neuromodulation has emerged as a promising tool to promote functional recovery in patients with motor disorders. Brain-machine interfaces exploit this neuromodulatory strategy and could be used for restoring voluntary control of lower limbs. In this work, we propose a non-invasive brain-spine interface (BSI) that processes electroencephalographic (EEG) activity to volitionally control trans-spinal magnetic stimulation (ts-MS), as an approach for lower-limb neurorehabilitation. This novel platform allows to contingently connect motor cortical activation during leg motor imagery with the activation of leg muscles via ts-MS. We tested this closed-loop system in 10 healthy participants using different stimulation conditions. This BSI efficiently removed stimulation artifacts from EEG regardless of ts-MS intensity used, allowing continuous monitoring of cortical activity and real-time closed-loop control of ts-MS. Our BSI induced afferent and efferent evoked responses, being this activation ts-MS intensity-dependent. We demonstrated the feasibility, safety and usability of this non-invasive BSI. The presented system represents a novel non-invasive means of brain-controlled neuromodulation and opens the door towards its integration as a therapeutic tool for lower-limb rehabilitation.

Background Persistent sensorimotor impairments after stroke can negatively impact quality of life. The hippocampus is vulnerable to poststroke secondary degeneration and is involved in sensorimotor behavior but has not been widely studied within the context of poststroke upper‐limb sensorimotor impairment. We investigated associations between non‐lesioned hippocampal volume and upper limb sensorimotor impairment in people with chronic stroke, hypothesizing that smaller ipsilesional hippocampal volumes would be associated with greater sensorimotor impairment. Methods and Results Cross‐sectional T1‐weighted magnetic resonance images of the brain were pooled from 357 participants with chronic stroke from 18 research cohorts of the ENIGMA (Enhancing NeuoImaging Genetics through Meta‐Analysis) Stroke Recovery Working Group. Sensorimotor impairment was estimated from the FMA‐UE (Fugl‐Meyer Assessment of Upper Extremity). Robust mixed‐effects linear models were used to test associations between poststroke sensorimotor impairment and hippocampal volumes (ipsilesional and contralesional separately; Bonferroni‐corrected, P

Motor learning mediated by motor training has in the past been explored for rehabilitation. Myoelectric interfaces together with exoskeletons allow patients to receive real-time feedback about their muscle activity. However, the number of degrees of freedom that can be simultaneously controlled is limited, which hinders the training of functional tasks and the effectiveness of the rehabilitation therapy. The objective of this study was to develop a myoelectric interface that would allow multi-degree-of-freedom control of an exoskeleton involving arm, wrist and hand joints, with an eye toward rehabilitation. We tested the effectiveness of a myoelectric decoder trained with data from one upper limb and mirrored to control a multi-degree-of-freedom exoskeleton with the opposite upper limb (i.e., mirror myoelectric interface) in 10 healthy participants. We demonstrated successful simultaneous control of multiple upper-limb joints by all participants. We showed evidence that subjects learned the mirror myoelectric model within the span of a five-session experiment, as reflected by a significant decrease in the time to execute trials and in the number of failed trials. These results are the necessary precursor to evaluating if a decoder trained with EMG from the healthy limb could foster learning of natural EMG patterns and lead to motor rehabilitation in stroke patients.

Neuromuscular electrical stimulation (NMES) of the nervous system has been extensively used in neurorehabilitation due to its capacity to engage the muscle fibers, improving muscle tone, and the neural pathways, sending afferent volleys toward the brain. Although different neuroimaging tools suggested the capability of NMES to regulate the excitability of sensorimotor cortex and corticospinal circuits, how the intensity and dose of NMES can neuromodulate the brain oscillatory activity measured with electroencephalography (EEG) is still unknown to date. We quantified the effect of NMES parameters on brain oscillatory activity of 12 healthy participants who underwent stimulation of wrist extensors during rest. Three different NMES intensities were included, two below and one above the individual motor threshold, fixing the stimulation frequency to 35 Hz and the pulse width to 300 μs. Firstly, we efficiently removed stimulation artifacts from the EEG recordings. Secondly, we analyzed the effect of amplitude and dose on the sensorimotor oscillatory activity. On the one hand, we observed a significant NMES intensity-dependent modulation of brain activity, demonstrating the direct effect of afferent receptor recruitment. On the other hand, we described a significant NMES intensity-dependent dose-effect on sensorimotor activity modulation over time, with below-motor-threshold intensities causing cortical inhibition and above-motor-threshold intensities causing cortical facilitation. Our results highlight the relevance of intensity and dose of NMES, and show that these parameters can influence the recruitment of the sensorimotor pathways from the muscle to the brain, which should be carefully considered for the design of novel neuromodulation interventions based on NMES.

Abstract Background Brain machine interface (BMI) technology has demonstrated its efficacy for rehabilitation of paralyzed chronic stroke patients. The critical component in BMI-training consists of the associative connection (contingency) between the intention and the feedback provided. However, the relationship between the BMI design and its performance in stroke patients is still an open question. Methods In this study we compare different methodologies to design a BMI for rehabilitation and evaluate their effects on movement intention decoding performance. We analyze the data of 37 chronic stroke patients who underwent 4 weeks of BMI intervention with different types of association between their brain activity and the proprioceptive feedback. We simulate the pseudo-online performance that a BMI would have under different conditions, varying: (1) the cortical source of activity (i.e., ipsilesional, contralesional, bihemispheric), (2) the type of spatial filter applied, (3) the EEG frequency band, (4) the type of classifier; and also evaluated the use of residual EMG activity to decode the movement intentions. Results We observed a significant influence of the different BMI designs on the obtained performances. Our results revealed that using bihemispheric beta activity with a common average reference and an adaptive support vector machine led to the best classification results. Furthermore, the decoding results based on brain activity were significantly higher than those based on muscle activity. Conclusions This paper underscores the relevance of the different parameters used to decode movement, using EEG in severely paralyzed stroke patients. We demonstrated significant differences in performance for the different designs, which supports further research that should elucidate if those approaches leading to higher accuracies also induce higher motor recovery in paralyzed stroke patients.

The electroencephalogram (EEG) constitutes a relevant tool to study neural dynamics and to develop brain-machine interfaces (BMI) for rehabilitation of patients with paralysis due to stroke. However, the EEG is easily contaminated by artifacts of physiological origin, which can pollute the measured cortical activity and bias the interpretations of such data. This is especially relevant when recording EEG of stroke patients while they try to move their paretic limbs, since they generate more artifacts due to compensatory activity. In this paper, we study how physiological artifacts (i.e., eye movements, motion artifacts, muscle artifacts and compensatory movements with the other limb) can affect EEG activity of stroke patients. Data from 31 severely paralyzed stroke patients performing/attempting grasping movements with their healthy/paralyzed hand were analyzed offline. We estimated the cortical activation as the event-related desynchronization (ERD) of sensorimotor rhythms and used it to detect the movements with a pseudo-online simulated BMI. Automated state-of-the-art methods (linear regression to remove ocular contaminations and statistical thresholding to reject the other types of artifacts) were used to minimize the influence of artifacts. The effect of artifact reduction was quantified in terms of ERD and BMI performance. The results reveal a significant contamination affecting the EEG, being involuntary muscle activity the main source of artifacts. Artifact reduction helped extracting the oscillatory signatures of motor tasks, isolating relevant information from noise and revealing a more prominent ERD activity. Lower BMI performances were obtained when artifacts were eliminated from the training datasets. This suggests that artifacts produce an optimistic bias that improves theoretical accuracy but may result in a poor link between task-related oscillatory activity and BMI peripheral feedback. With a clinically relevant dataset of stroke patients, we evidence the need of appropriate methodologies to remove artifacts from EEG datasets to obtain accurate estimations of the motor brain activity. Keywords: Electroencephalogram (EEG), artifacts, motor cortical activity, brain-machine interfaces (BMI), stroke

Abnormal upper arm-forearm muscle synergies after stroke are poorly understood. We investigated whether upper arm function primes paralyzed forearm muscles in chronic stroke patients after Brain-Machine Interface (BMI)-based rehabilitation. Shaping upper arm-forearm muscle synergies may support individualized motor rehabilitation strategies.Thirty-two chronic stroke patients with no active finger extensions were randomly assigned to experimental or sham groups and underwent daily BMI training followed by physiotherapy during four weeks. BMI sessions included desynchronization of ipsilesional brain activity and a robotic orthosis to move the paretic limb (experimental group, n = 16). In the sham group (n = 16) orthosis movements were random. Motor function was evaluated with electromyography (EMG) of forearm extensors, and upper arm and hand Fugl-Meyer assessment (FMA) scores. Patients performed distinct upper arm (e.g., shoulder flexion) and hand movements (finger extensions). Forearm EMG activity significantly higher during upper arm movements as compared to finger extensions was considered facilitation of forearm EMG activity. Intraclass correlation coefficient (ICC) was used to test inter-session reliability of facilitation of forearm EMG activity.Facilitation of forearm EMG activity ICC ranges from 0.52 to 0.83, indicating fair to high reliability before intervention in both limbs. Facilitation of forearm muscles is higher in the paretic as compared to the healthy limb (p

Several works have reported on the reconstruction of 2D/3D limb kinematics from low-frequency EEG signals using linear regression models based on positive correlation values between the recorded and the reconstructed trajectories. This paper describes the mathematical properties of the linear model and the correlation evaluation metric that may lead to a misinterpretation of the results of this type of decoders. Firstly, the use of a linear regression model to adjust the two temporal signals (EEG and velocity profiles) implies that the relevant component of the signal used for decoding (EEG) has to be in the same frequency range as the signal to be decoded (velocity profiles). Secondly, the use of a correlation to evaluate the fitting of two trajectories could lead to overly-optimistic results as this metric is invariant to scale. Also, the correlation has a non-linear nature that leads to higher values for sinus/cosinus-like signals at low frequencies. Analysis of these properties on the reconstruction results was carried out through an experiment performed in line with previous studies, where healthy participants executed predefined reaching movements of the hand in 3D space. While the correlations of limb velocity profiles reconstructed from low-frequency EEG were comparable to studies in this domain, a systematic statistical analysis revealed that these results were not above the chance level. The empirical chance level was estimated using random assignments of recorded velocity profiles and EEG signals, as well as combinations of randomly generated synthetic EEG with recorded velocity profiles and recorded EEG with randomly generated synthetic velocity profiles. The analysis shows that the positive correlation results in this experiment cannot be used as an indicator of successful trajectory reconstruction based on a neural correlate. Several directions are herein discussed to address the misinterpretation of results as well as the implications on previous invasive and non-invasive works.

Brain computer interface (BCI) technology has been proposed for motor neurorehabilitation, motor replacement and assistive technologies. It is an open question whether proprioceptive feedback affects the regulation of brain oscillations and therefore BCI control. We developed a BCI coupled on-line with a robotic hand exoskeleton for flexing and extending the fingers. 24 healthy participants performed five different tasks of closing and opening the hand: (1) motor imagery of the hand movement without any overt movement and without feedback, (2) motor imagery with movement as online feedback (participants see and feel their hand, with the exoskeleton moving according to their brain signals, (3) passive (the orthosis passively opens and closes the hand without imagery) and (4) active (overt) movement of the hand and rest. Performance was defined as the difference in power of the sensorimotor rhythm during motor task and rest and calculated offline for different tasks. Participants were divided in three groups depending on the feedback receiving during task 2 (the other tasks were the same for all participants). Group 1 (n = 9) received contingent positive feedback (participants' sensorimotor rhythm (SMR) desynchronization was directly linked to hand orthosis movements), group 2 (n = 8) contingent "negative" feedback (participants' sensorimotor rhythm synchronization was directly linked to hand orthosis movements) and group 3 (n = 7) sham feedback (no link between brain oscillations and orthosis movements). We observed that proprioceptive feedback (feeling and seeing hand movements) improved BCI performance significantly. Furthermore, in the contingent positive group only a significant motor learning effect was observed enhancing SMR desynchronization during motor imagery without feedback in time. Furthermore, we observed a significantly stronger SMR desynchronization in the contingent positive group compared to the other groups during active and passive movements. To summarize, we demonstrated that the use of contingent positive proprioceptive feedback BCI enhanced SMR desynchronization during motor tasks.