Evolution of EEG Motor Rhythms after Spinal Cord Injury: A Longitudinal Study

Effects of altered functional connectivity on motor imagery brain-computer interfaces based on the laterality of paralysis in hemiplegia patients

Motor imagery (MI)-based brain-computer interfaces are widely employed for improving the rehabilitation of paralyzed people and their quality of life. It has been well documented that brain activity patterns in the primary motor cortex and sensorimotor cortex during MI are similar to those of motor execution/imagery. However, individuals paralyzed owing to various neurological disorders have debilitated activation of the motor control region. Therefore, the differences in brain activation based on the paralysis location should be considered. We analyzed brain activation patterns using the electroencephalogram (EEG) acquired while performing MI on the right upper limb to investigate hemiplegia-related brain activation patterns. Participants with hemiplegia of the right upper limb (n=7) and left upper limb (n=4) performed the MI task within the right upper limb. EEG signals were acquired using 14 channels based on a 10-20 global system, and analyzed for event-related desynchronization (ERD) based on event-related spectral perturbation and functional connectivity, using the weighted phase-lag index of both hemispheres at the location of hemiplegia. Enhanced ERD was found in the ipsilateral region, compared to the contralateral region, after MI of the affected limb. The reduced difference in the centrality of the channels was observed in all subjects, likely reflecting an altered brain network from increased interhemispheric connections. Furthermore, the tendency of distinct network-based features depending on the MI task on the affected limb was diluted between the inter-hemispheres. Analysis of interaction between inter-region using functional connectivity could provide avenues for further investigation of BCI strategy through the brain state of individuals with hemiplegia.

Spinal Cord Injury Patients Exhibit Changes in Motor-Related Activity and Topographic Distribution

Spinal Cord Injury (SCI) is a common disease that usually limits the patient's independence by affecting their motor function. SCI patients usually present neuroplasticity, which allows brain signals transmission through spread pathways. Some innovative rehabilitation therapies, such as functional electrical stimulation (FES) or Brain-computer interfaces (BCIs) jointly with motor neuroprostheses, provide hope for functional restoration. BCIs require the analysis of event-related EEG potentials (ERPs). Movement-related cortical potentials (MRCPs) and event-related desynchroni-zation and synchronization (ERD/ERS) are the most commonly studied ERPs during motor activity. ERPs of healthy subjects may vary from SCI patients. Thus, this study aimed to compare ERPs between healthy subjects and SCI patients during upper-limb movements (forearm supination and pronation, and hand open). Differences between controls and SCI patients were shown in terms of ERPs' amplitude as well as in topographic maps. Changes in amplitude were more substantial in ERD potentials than in MRCPs, while topographic maps showed better localization of all features in healthy patients. The level of SCI injury determines the patients' mobility. A comparison between complete, partial and no motor function subjects showed lower values of feature's amplitudes in the latter group.Clinical Relevance- This demonstrates the existence of significant statistical differences between healthy and SCI subjects, and might be helpful when performing SCI rehabilitation techniques such as designing BCI and neuroprostheses, or analyzing and understanding the brain plasticity process.

Paving the Way for Motor Imagery-Based Tele-Rehabilitation through a Fully Wearable BCI System

The present study introduces a brain-computer interface designed and prototyped to be wearable and usable in daily life. Eight dry electroencephalographic sensors were adopted to acquire the brain activity associated with motor imagery. Multimodal feedback in extended reality was exploited to improve the online detection of neurological phenomena. Twenty-seven healthy subjects used the proposed system in five sessions to investigate the effects of feedback on motor imagery. The sample was divided into two equal-sized groups: a "neurofeedback" group, which performed motor imagery while receiving feedback, and a "control" group, which performed motor imagery with no feedback. Questionnaires were administered to participants aiming to investigate the usability of the proposed system and an individual's ability to imagine movements. The highest mean classification accuracy across the subjects of the control group was about 62% with 3% associated type A uncertainty, and it was 69% with 3% uncertainty for the neurofeedback group. Moreover, the results in some cases were significantly higher for the neurofeedback group. The perceived usability by all participants was high. Overall, the study aimed at highlighting the advantages and the pitfalls of using a wearable brain-computer interface with dry sensors. Notably, this technology can be adopted for safe and economically viable tele-rehabilitation.

A garment that measures brain activity: proof of concept of an EEG sensor layer fully implemented with smart textiles

This paper presents the first garment capable of measuring brain activity with accuracy comparable to that of state-of-the art dry electroencephalogram (EEG) systems. The main innovation is an EEG sensor layer (i.e., the electrodes, the signal transmission, and the cap support) made entirely of threads, fabrics, and smart textiles, eliminating the need for metal or plastic materials. The garment is connected to a mobile EEG amplifier to complete the measurement system. As a first proof of concept, the new EEG system (Garment-EEG) was characterized with respect to a state-of-the-art Ag/AgCl dry-EEG system (Dry-EEG) over the forehead area of healthy participants in terms of: (1) skin-electrode impedance; (2) EEG activity; (3) artifacts; and (4) user ergonomics and comfort. The results show that the Garment-EEG system provides comparable recordings to Dry-EEG, but it is more susceptible to artifacts under adverse recording conditions due to poorer contact impedances. The textile-based sensor layer offers superior ergonomics and comfort compared to its metal-based counterpart. We provide the datasets recorded with Garment-EEG and Dry-EEG systems, making available the first open-access dataset of an EEG sensor layer built exclusively with textile materials. Achieving user acceptance is an obstacle in the field of neurotechnology. The introduction of EEG systems encapsulated in wearables has the potential to democratize neurotechnology and non-invasive brain-computer interfaces, as they are naturally accepted by people in their daily lives. Furthermore, supporting the EEG implementation in the textile industry may result in lower cost and less-polluting manufacturing processes compared to metal and plastic industries.

Brain-Computer interface control of stepping from invasive electrocorticography upper-limb motor imagery in a patient with quadriplegia

Introduction: Most spinal cord injuries (SCI) result in lower extremities paralysis, thus diminishing ambulation. Using brain-computer interfaces (BCI), patients may regain leg control using neural signals that actuate assistive devices. Here, we present a case of a subject with cervical SCI with an implanted electrocorticography (ECoG) device and determined whether the system is capable of motor-imagery-initiated walking in an assistive ambulator. Methods: A 24-year-old male subject with cervical SCI (C5 ASIA A) was implanted before the study with an ECoG sensing device over the sensorimotor hand region of the brain. The subject used motor-imagery (MI) to train decoders to classify sensorimotor rhythms. Fifteen sessions of closed-loop trials followed in which the subject ambulated for one hour on a robotic-assisted weight-supported treadmill one to three times per week. We evaluated the stability of the best-performing decoder over time to initiate walking on the treadmill by decoding upper-limb (UL) MI. Results: An online bagged trees classifier performed best with an accuracy of 84.15% averaged across 9 weeks. Decoder accuracy remained stable following throughout closed-loop data collection. Discussion: These results demonstrate that decoding UL MI is a feasible control signal for use in lower-limb motor control. Invasive BCI systems designed for upper-extremity motor control can be extended for controlling systems beyond upper extremity control alone. Importantly, the decoders used were able to use the invasive signal over several weeks to accurately classify MI from the invasive signal. More work is needed to determine the long-term consequence between UL MI and the resulting lower-limb control.

Frequency-tuned electromagnetic field therapy improves post-stroke motor function: A pilot randomized controlled trial

BACKGROUND AND PURPOSE

Impaired upper extremity (UE) motor function is a common disability after ischemic stroke. Exposure to extremely low frequency and low intensity electromagnetic fields (ELF-EMF) in a frequency-specific manner (Electromagnetic Network Targeting Field therapy; ENTF therapy) is a non-invasive method available to a wide range of patients that may enhance neuroplasticity, potentially facilitating motor recovery. This study seeks to quantify the benefit of the ENTF therapy on UE motor function in a subacute ischemic stroke population.

METHODS

In a randomized, sham-controlled, double-blind trial, ischemic stroke patients in the subacute phase with moderately to severely impaired UE function were randomly allocated to active or sham treatment with a novel, non-invasive, brain computer interface-based, extremely low frequency and low intensity ENTF therapy (1-100 Hz, < 1 G). Participants received 40 min of active ENTF or sham treatment 5 days/week for 8 weeks; ~three out of the five treatments were accompanied by 10 min of concurrent physical/occupational therapy. Primary efficacy outcome was improvement on the Fugl-Meyer Assessment - Upper Extremity (FMA-UE) from baseline to end of treatment (8 weeks).

RESULTS

In the per protocol set (13 ENTF and 8 sham participants), mean age was 54.7 years (±15.0), 19% were female, baseline FMA-UE score was 23.7 (±11.0), and median time from stroke onset to first stimulation was 11 days (interquartile range (IQR) 8-15). Greater improvement on the FMA-UE from baseline to week 4 was seen with ENTF compared to sham stimulation, 23.2 ± 14.1 vs. 9.6 ± 9.0, p = 0.007; baseline to week 8 improvement was 31.5 ± 10.7 vs. 23.1 ± 14.1. Similar favorable effects at week 8 were observed for other UE and global disability assessments, including the Action Research Arm Test (Pinch, 13.4 ± 5.6 vs. 5.3 ± 6.5, p = 0.008), Box and Blocks Test (affected hand, 22.5 ± 12.4 vs. 8.5 ± 8.6, p < 0.0001), and modified Rankin Scale (-2.5 ± 0.7 vs. -1.3 ± 0.7, p = 0.0005). No treatment-related adverse events were reported.

CONCLUSIONS

ENTF stimulation in subacute ischemic stroke patients was associated with improved UE motor function and reduced overall disability, and results support its safe use in the indicated population. These results should be confirmed in larger multicenter studies.

CLINICAL TRIAL REGISTRATION

https://clinicaltrials.gov/ct2/show/NCT04039178, identifier: NCT04039178.

Non-invasive brain-spine interface: Continuous control of trans-spinal magnetic stimulation using EEG

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.

Contribution of the sensorimotor beta oscillations and the cortico-basal ganglia-thalamic circuitry during value-based decision making: A simultaneous EEG-fMRI investigation

In decision neuroscience, the motor system has primarily been considered to be involved in executing choice actions. However, a competing perspective suggests its engagement in the evaluation of options, traditionally considered to be performed by the brain's valuation system. Here, we investigate the role of the motor system in value-based decision making by determining the neural circuitries associated with the sensorimotor beta oscillations previously identified to encode decision options. In a simultaneous EEG-fMRI study, participants evaluated reward and risk associated with a forthcoming action. A significant sensorimotor beta desynchronization was identified prior to and independent of response. The level of beta desynchronization showed evidence of encoding the reward levels. This beta desynchronization covaried, on a trial-by-trial level, with BOLD activity in the cortico-basal ganglia-thalamic circuitry. In contrast, there was only a weak covariation within the valuation network, despite significant modulation of its BOLD activity by reward levels. These results suggest that the way in which decision variables are processed differs in the valuation network and in the cortico-basal ganglia-thalamic circuitry. We propose that sensorimotor beta oscillations indicate incentive motivational drive towards a choice action computed from the decision variables even prior to making a response, and it arises from the cortico-basal ganglia-thalamic circuitry.

Effect of long-term paired associative stimulation on the modulation of cortical sensorimotor oscillations after spinal cord injury

Study design

A prospective interventional case series.

Objectives

To explore changes in the modulation of cortical sensorimotor oscillations after long-term paired associative stimulation (PAS) in participants with spinal cord injury (SCI).

Setting

BioMag Laboratory, HUS Diagnostic Center, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.

Methods

Five patients with chronic incomplete SCI received unilateral spinal PAS to upper limb for 16–22 days. Changes in the modulation of sensorimotor oscillations in response to tactile stimulus and active and imaginary hand movements were assessed with magnetoencephalography recorded before and after the intervention.

Results

PAS restored the modulation of sensorimotor oscillations in response to active hand movement in four patients, whereas the modulation following tactile stimulation remained unaltered. The observed change was larger in the hemisphere that received PAS and preceded the clinical effect of the intervention.

Conclusions

Long-term spinal PAS treatment, which enhances the motor functions of SCI patients, also restores the modulation of cortical sensorimotor oscillations.

Implantable brain-computer interface for neuroprosthetic-enabled volitional hand grasp restoration in spinal cord injury

Loss of hand function after cervical spinal cord injury severely impairs functional independence. We describe a method for restoring volitional control of hand grasp in one 21-year-old male subject with complete cervical quadriplegia (C5 American Spinal Injury Association Impairment Scale A) using a portable fully implanted brain-computer interface within the home environment. The brain-computer interface consists of subdural surface electrodes placed over the dominant-hand motor cortex and connects to a transmitter implanted subcutaneously below the clavicle, which allows continuous reading of the electrocorticographic activity. Movement-intent was used to trigger functional electrical stimulation of the dominant hand during an initial 29-weeks laboratory study and subsequently via a mechanical hand orthosis during in-home use. Movement-intent information could be decoded consistently throughout the 29-weeks in-laboratory study with a mean accuracy of 89.0% (range 78-93.3%). Improvements were observed in both the speed and accuracy of various upper extremity tasks, including lifting small objects and transferring objects to specific targets. At-home decoding accuracy during open-loop trials reached an accuracy of 91.3% (range 80-98.95%) and an accuracy of 88.3% (range 77.6-95.5%) during closed-loop trials. Importantly, the temporal stability of both the functional outcomes and decoder metrics were not explored in this study. A fully implanted brain-computer interface can be safely used to reliably decode movement-intent from motor cortex, allowing for accurate volitional control of hand grasp.

Maladaptive reorganization following SCI: The role of body representation and multisensory integration

In this review we focus on maladaptive brain reorganization after spinal cord injury (SCI), including the development of neuropathic pain, and its relationship with impairments in body representation and multisensory integration. We will discuss the implications of altered sensorimotor interactions after SCI with and without neuropathic pain and possible deficits in multisensory integration and body representation. Within this framework we will examine published research findings focused on the use of bodily illusions to manipulate multisensory body representation to induce analgesic effects in heterogeneous chronic pain populations and in SCI-related neuropathic pain. We propose that the development and intensification of neuropathic pain after SCI is partly dependent on brain reorganization associated with dysfunctional multisensory integration processes and distorted body representation. We conclude this review by suggesting future research avenues that may lead to a better understanding of the complex mechanisms underlying the sense of the body after SCI, with a focus on cortical changes.

Towards a mechanistic approach for the development of non-invasive brain-computer interfaces for motor rehabilitation

Brain-computer interfaces (BCIs) designed for motor rehabilitation use brain signals associated with motor-processing states to guide neuroplastic changes in a state-dependent manner. These technologies are uniquely positioned to induce targeted and functionally relevant plastic changes in the human motor nervous system. However, while several studies have shown that BCI-based neuromodulation interventions may improve motor function in patients with lesions in the central nervous system, the neurophysiological structures and processes targeted with the BCI interventions have not been identified. In this review, we first summarize current knowledge of the changes in the central nervous system associated with learning new motor skills. Then, we propose a classification of current BCI paradigms for plasticity induction and motor rehabilitation based on the expected neural plastic changes promoted. This classification proposes four paradigms based on two criteria: the plasticity induction methods and the brain states targeted. The existing evidence regarding the brain circuits and processes targeted with these different BCIs is discussed in detail. The proposed classification aims to serve as a starting point for future studies trying to elucidate the underlying plastic changes following BCI interventions.

Electroencephalography as a Biomarker for Functional Recovery in Spinal Cord Injury Patients

BACKGROUND

Functional changes after spinal cord injury (SCI) are related to changes in cortical plasticity. These changes can be measured with electroencephalography (EEG) and has potential to be used as a clinical biomarker.

METHOD

In this longitudinal study participants underwent a total of 30 sessions of robotic-assisted gait training (RAGT) over a course of 6 weeks. The duration of each session was 30 min. Resting state EEG was recorded before and after 30-session rehabilitation therapy. To measure gait, we used the Walking Index for Spinal Cord Injury Scale, 10-Meter- Walking Test, Timed-Up-and-Go, and 6-Min-Walking Test. Balance was measured using Berg Balance Scale.

RESULTS

Fifteen participants with incomplete SCI who had AIS C or D injuries based on American Spinal Cord Injury Association Impairment Scale classification were included in this study. Mean age was 35.7 years (range 17-51) and the mean time since injury was 17.08 (range 4-37) months. All participants showed clinical improvement with the rehabilitation program. EEG data revealed that high beta EEG activity in the central area had a negative correlation with gait (p = 0.049; β coefficient: -0.351; and adj-R 2: 0.23) and balance (p = 0.043; β coefficient: -0.158; and adj-R 2:0.24) measured at baseline, in a way that greater high beta EEG power was related to worse clinical function at baseline. Moreover, improvement in gait and balance had negative correlations with the change in alpha/theta ratio in the parietal area (Gait: p = 0.049; β coefficient: -0.351; adj-R 2: 0.23; Balance: p = 0.043; β coefficient: -0.158; and adj-R 2: 0.24).

CONCLUSION

In SCI, functional impairment and subsequent improvement following rehabilitation therapy with RAGT correlated with the change in cortical activity measured by EEG. Our results suggest that EEG alpha/theta ratio may be a potential surrogate marker of functional improvement during rehabilitation. Future studies are necessary to improve and validate these findings as a neurophysiological biomarker for SCI rehabilitation.

Divergent Findings in Brain Reorganization After Spinal Cord Injury: A Review

Spinal cord injury (SCI) leads to a general lack of sensory and motor functions below the level of injury and may promote deafferentation-induced brain reorganization. Functional magnetic resonance imaging (fMRI) has been established as an essential tool in neuroscience research and can precisely map the spatiotemporal distribution of brain activity. Task-based fMRI experiments associated with the tongue, upper limbs, or lower limbs have been used as the primary paradigms to study brain reorganization following SCI. A review of the current literature on the subject shows one common trait: while most articles agree that brain networks are usually preserved after SCI, and that is not the case as some articles describe possible alterations in brain activation after the lesion. There is no consensus if those alterations indeed occur. In articles that show alterations, there is no agreement if they are transient or permanent. Besides, there is no consensus on which areas are most prone to activation changes, or on the intensity and direction (increase vs. decrease) of those possible changes. In this article, we present a critical review of the literature and trace possible reasons for those contradictory findings on brain reorganization following SCI. fMRI studies based on the ankle dorsiflexion, upper-limb, and tongue paradigms are used as case studies for the analyses.

Motor-system dynamics during naturalistic reading of action narratives in first and second language

Do embodied semantic systems play different roles depending on when and how well a given language was learned? Emergent evidence suggests that this is the case for isolated, decontextualized stimuli, but no study has addressed the issue considering naturalistic narratives. Seeking to bridge this gap, we assessed motor-system dynamics in 26 Spanish-English bilinguals as they engaged in free, unconstrained reading of naturalistic action texts (ATs, highlighting the characters’ movements) and neutral texts (NTs, featuring low motility) in their first and second language (L1, L2). To explore functional connectivity spread over each reading session, we recorded ongoing high-density electroencephalographic signals and subjected them to functional connectivity analysis via a spatial clustering approach. Results showed that, in L1, AT (relative to NT) reading involved increased connectivity between left and right central electrodes consistently implicated in action-related processes, as well as distinct source-level modulations in motor regions. In L2, despite null group-level effects, enhanced motor-related connectivity during AT reading correlated positively with L2 proficiency and negatively with age of L2 learning. Taken together, these findings suggest that action simulations during unconstrained narrative reading involve neural couplings between motor-sensitive mechanisms, in proportion to how consolidated a language is. More generally, such evidence addresses recent calls to test the ecological validity of motor-resonance effects while offering new insights on their relation with experiential variables.

Visuo-motor and interoceptive influences on peripersonal space representation following spinal cord injury

Peripersonal space (PPS) representation is modulated by information coming from the body. In paraplegic individuals, whose lower limb sensory-motor functions are impaired or completely lost, the representation of PPS around the feet is reduced. However, passive motion can have short-term restorative effects. What remains unclear is the mechanisms underlying this recovery, in particular with regard to the contribution of visual and motor feedback and of interoception. Using virtual reality technology, we dissociated the motor and visual feedback during passive motion in paraplegics with complete and incomplete lesions and in healthy controls. The results show that in the case of paraplegics, the presence of motor feedback was necessary for the recovery of PPS representation, both when the motor feedback was congruent and when it was incongruent with the visual feedback. In contrast, visuo-motor incongruence led to an inhibition of PPS representation in the control group. There were no differences in sympathetic responses between the three groups. Nevertheless, in individuals with incomplete lesions, greater interoceptive sensitivity was associated with a better representation of PPS around the feet in the visuo-motor incongruent conditions. These results shed new light on the modulation of PPS representation, and demonstrate the importance of residual motor feedback and its integration with other bodily information in maintaining space representation.

Brain oscillatory activity as a biomarker of motor recovery in chronic stroke

In the present work, we investigated the relationship of oscillatory sensorimotor brain activity to motor recovery. The neurophysiological data of 30 chronic stroke patients with severe upper‐limb paralysis are the basis of the observational study presented here. These patients underwent an intervention including movement training based on combined brain–machine interfaces and physiotherapy of several weeks recorded in a double‐blinded randomized clinical trial. We analyzed the alpha oscillations over the motor cortex of 22 of these patients employing multilevel linear predictive modeling. We identified a significant correlation between the evolution of the alpha desynchronization during rehabilitative intervention and clinical improvement. Moreover, we observed that the initial alpha desynchronization conditions its modulation during intervention: Patients showing a strong alpha desynchronization at the beginning of the training improved if they increased their alpha desynchronization. Patients showing a small alpha desynchronization at initial training stages improved if they decreased it further on both hemispheres. In all patients, a progressive shift of desynchronization toward the ipsilesional hemisphere correlates significantly with clinical improvement regardless of lesion location. The results indicate that initial alpha desynchronization might be key for stratification of patients undergoing BMI interventions and that its interhemispheric balance plays an important role in motor recovery.

Longitudinal Analysis of Stroke Patients' Brain Rhythms during an Intervention with a Brain-Computer Interface

Stroke is a leading cause of motor disability worldwide. Upper limb rehabilitation is particularly challenging since approximately 35% of patients recover significant hand function after 6 months of the stroke's onset. Therefore, new therapies, especially those based on brain-computer interfaces (BCI) and robotic assistive devices, are currently under research. Electroencephalography (EEG) acquired brain rhythms in alpha and beta bands, during motor tasks, such as motor imagery/intention (MI), could provide insight of motor-related neural plasticity occurring during a BCI intervention. Hence, a longitudinal analysis of subacute stroke patients' brain rhythms during a BCI coupled to robotic device intervention was performed in this study. Data of 9 stroke patients were acquired across 12 sessions of the BCI intervention. Alpha and beta event-related desynchronization/synchronization (ERD/ERS) trends across sessions and their association with time since stroke onset and clinical upper extremity recovery were analyzed, using correlation and linear stepwise regression, respectively. More EEG channels presented significant ERD/ERS trends across sessions related with time since stroke onset, in beta, compared to alpha. Linear models implied a moderate relationship between alpha rhythms in frontal, temporal, and parietal areas with upper limb motor recovery and suggested a strong association between beta activity in frontal, central, and parietal regions with upper limb motor recovery. Higher association of beta with both time since stroke onset and upper limb motor recovery could be explained by beta relation with closed-loop communication between the sensorimotor cortex and the paralyzed upper limb, and alpha being probably more associated with motor learning mechanisms. The association between upper limb motor recovery and beta activations reinforces the hypothesis that broader regions of the cortex activate during movement tasks as a compensatory mechanism in stroke patients with severe motor impairment. Therefore, EEG across BCI interventions could provide valuable information for prognosis and BCI cortical activity targets.

Impact Of Spinal Cord Injury On Sleep: Current Perspectives

Sleep disorders are commonly encountered in people living with spinal cord injury (SCI). Primary sleep disorders such as sleep-disordered breathing (SDB), sleep-related movement disorders, circadian rhythm sleep-wake disorders, and insomnia disorder are common conditions after SCI but remain under-recognized, underdiagnosed and therefore remain untreated for a majority of patients. Sleep disturbances in people living with SCI are associated with significant impairments of daytime function and quality of life. Previous reviews have described findings related mainly to SDB but have not examined the relationship between other sleep disorders and SCI. This narrative review examines various sleep abnormalities and related functional and physical impairments in people living with SCI. It discusses new evidence pertaining to management, highlights existing limitations in the literature and recommends future directions for research.

Event-related desynchronization during movement attempt and execution in severely paralyzed stroke patients: An artifact removal relevance analysis

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.

Reactivating the Dormant Motor Cortex After Spinal Cord Injury With EEG Neurofeedback: A Case Study With a Chronic, Complete C4 Patient

Chronic spinal cord injury (SCI) patients present poor motor cortex activation during movement attempts. The reactivation of this brain region can be beneficial for them, for instance, allowing them to use brain-machine interfaces for motor rehabilitation or restoration. These brain-machine interfacess generally use electroencephalography (EEG) to measure the cortical activation during the attempts of movement, quantifying it as the event-related desynchronization (ERD) of the alpha/mu rhythm. Based on previous evidence showing that higher tonic EEG alpha power is associated with higher ERD, we hypothesized that artificially increasing the alpha power over the motor cortex of these patients could enhance their ERD (ie, motor cortical activation) during movement attempts. We used EEG neurofeedback (NF) to enhance the tonic EEG alpha power, providing real-time visual feedback of the alpha oscillations measured over the motor cortex. This approach was evaluated in a C4, ASIA A, SCI patient (9 months after the injury) who did not present ERD during the movement attempts of his paralyzed hands. The patient performed 4 NF sessions (in 4 consecutive days) and screenings of his EEG activity before and after each session. After the intervention, the patient presented a significant increase in the alpha power over the motor cortex, and a significant enhancement of the mu ERD in the contralateral motor cortex when he attempted to close the assessed right hand. As a proof of concept investigation, this article shows how a short NF intervention might be used to enhance the motor cortical activation in patients with chronic tetraplegia.

Comparing Recalibration Strategies for Electroencephalography-Based Decoders of Movement Intention in Neurological Patients with Motor Disability

Motor rehabilitation based on the association of electroencephalographic (EEG) activity and proprioceptive feedback has been demonstrated as a feasible therapy for patients with paralysis. To promote long-lasting motor recovery, these interventions have to be carried out across several weeks or even months. The success of these therapies partly relies on the performance of the system decoding movement intentions, which normally has to be recalibrated to deal with the nonstationarities of the cortical activity. Minimizing the recalibration times is important to reduce the setup preparation and maximize the effective therapy time. To date, a systematic analysis of the effect of recalibration strategies in EEG-driven interfaces for motor rehabilitation has not yet been performed. Data from patients with stroke (4 patients, 8 sessions) and spinal cord injury (SCI) (4 patients, 5 sessions) undergoing two different paradigms (self-paced and cue-guided, respectively) are used to study the performance of the EEG-based classification of motor intentions. Four calibration schemes are compared, considering different combinations of training datasets from previous and/or the validated session. The results show significant differences in classifier performances in terms of the true and false positives (TPs) and (FPs). Combining training data from previous sessions with data from the validation session provides the best compromise between the amount of data needed for calibration and the classifier performance. With this scheme, the average true (false) positive rates obtained are 85.3% (17.3%) and 72.9% (30.3%) for the self-paced and the cue-guided protocols, respectively. These results suggest that the use of optimal recalibration schemes for EEG-based classifiers of motor intentions leads to enhanced performances of these technologies, while not requiring long calibration phases prior to starting the intervention.

Influence of artifacts on movement intention decoding from EEG activity in severely paralyzed stroke patients

Brain-machine interfaces (BMI) can be used to control robotic and prosthetic devices for rehabilitation of motor disorders, such as stroke. The calibration of these BMI systems is of paramount importance in order to establish a precise contingent link between the brain activity related to movement intention and the peripheral feedback. However, electroencephalographic (EEG) activity, commonly used to build non-invasive BMIs, can be easily contaminated by artifacts of electrical or physiological origin. The way these interferences can affect the performance of movement intention decoders has not been deeply studied, especially when dealing with severely paralyzed patients, which often generate more artifacts by compensatory movements. This paper evaluates the effects of removing artifacts from the data used to train a BMI decoder on a dataset of 28 severely paralyzed stroke patients. We show that cleaning the training datasets reduces the global BMI performance for decoding attempts of movement. Further, we demonstrate that this performance drop especially affects the test trials contaminated by artifacts (i.e., trials that might not reflect cortical activity but noise), but not the clean test trials (i.e., trials representing correct cortical activity). This paper underlines the importance of cleaning the datasets used to train BMI systems to improve their efficacy for decoding movement intention and maximize their neurorehabilitative potential.

Volition-adaptive control for gait training using wearable exoskeleton: preliminary tests with incomplete spinal cord injury individuals

BACKGROUND

Gait training for individuals with neurological disorders is challenging in providing the suitable assistance and more adaptive behaviour towards user needs. The user specific adaptation can be defined based on the user interaction with the orthosis and by monitoring the user intentions. In this paper, an adaptive control model, commanded by the user intention, is evaluated using a lower limb exoskeleton with incomplete spinal cord injury individuals (SCI).

METHODS

A user intention based adaptive control model has been developed and evaluated with 4 incomplete SCI individuals across 3 sessions of training per individual. The adaptive control model modifies the joint impedance properties of the exoskeleton as a function of the human-orthosis interaction torques and the joint trajectory evolution along the gait sequence, in real time. The volitional input of the user is identified by monitoring the neural signals, pertaining to the user's motor activity. These volitional inputs are used as a trigger to initiate the gait movement, allowing the user to control the initialization of the exoskeleton movement, independently. A Finite-state machine based control model is used in this set-up which helps in combining the volitional orders with the gait adaptation.

RESULTS

The exoskeleton demonstrated an adaptive assistance depending on the patients' performance without guiding them to follow an imposed trajectory. The exoskeleton initiated the trajectory based on the user intention command received from the brain machine interface, demonstrating it as a reliable trigger. The exoskeleton maintained the equilibrium by providing suitable assistance throughout the experiments. A progressive change in the maximum flexion of the knee joint was observed at the end of each session which shows improvement in the patient performance. Results of the adaptive impedance were evaluated by comparing with the application of a constant impedance value. Participants reported that the movement of the exoskeleton was flexible and the walking patterns were similar to their own distinct patterns.

CONCLUSIONS

This study demonstrates that user specific adaptive control can be applied on a wearable robot based on the human-orthosis interaction torques and modifying the joints' impedance properties. The patients perceived no external or impulsive force and felt comfortable with the assistance provided by the exoskeleton. The main goal of such a user dependent control is to assist the patients' needs and adapt to their characteristics, thus maximizing their engagement in the therapy and avoiding slacking. In addition, the initiation directly controlled by the brain allows synchronizing the user's intention with the afferent stimulus provided by the movement of the exoskeleton, which maximizes the potentiality of the system in neuro-rehabilitative therapies.

Altered modulation of sensorimotor rhythms with chronic paralysis

After paralysis, the disconnection between the cortex and its peripheral targets leads to neuroplasticity throughout the nervous system. However, it is unclear how chronic paralysis specifically impacts cortical oscillations associated with attempted movement of impaired limbs. We hypothesized that μ- (8-13 Hz) and β- (15-30 Hz) event-related desynchronization (ERD) would be less modulated for individuals with hand paralysis due to cervical spinal cord injury (SCI). To test this, we compared the modulation of ERD from magnetoencephalography (MEG) during attempted and imagined grasping performed by participants with cervical SCI (n = 12) and able-bodied controls (n = 13). Seven participants with tetraplegia were able to generate some electromyography (EMG) activity during attempted grasping, whereas the other five were not. The peak and area of ERD were significantly decreased for individuals without volitional muscle activity when they attempted to grasp compared with able-bodied subjects and participants with SCI,with some residual EMG activity. However, no significant differences were found between subject groups during mentally simulated tasks (i.e., motor imagery) where no muscle activity or somatosensory consequences were expected. These findings suggest that individuals who are unable to produce muscle activity are capable of generating ERD when attempting to move, but the characteristics of this ERD are altered. However, for people who maintain volitional muscle activity after SCI, there are no significant differences in ERD characteristics compared with able-bodied controls. These results provide evidence that ERD is dependent on the level of intact muscle activity after SCI.NEW & NOTEWORTHY Source space MEG was used to investigate sensorimotor cortical oscillations in individuals with SCI. This study provides evidence that individuals with cervical SCI exhibit decreased ERD when they attempt to grasp if they are incapable of generating muscle activity. However, there were no significant differences in ERD between paralyzed and able-bodied participants during motor imagery. These results have important implications for the design and evaluation of new therapies, such as motor imagery and neurofeedback interventions.

EEG patterns of subacute stroke patients performing motor tasks correlate with motor functional outcome: Preliminary results

If an early predictor of motor functional outcome after stroke were available, stroke patients would receive more appropriate treatments for motor recovery. We performed a correlation analysis of the electroencephalography (EEG) signal patterns of nine subacute stroke patients (recorded 22.9 ± 7.1 days after onset) and their motor recovery rates (measured 100.2 ± 8.9 days after onset). The beta band spectral power in the bilateral motor cortex after physical upper limb movement correlated significantly with the motor recovery rates [Fugl-Meyer assessment (FMA) scores; Pearson's linear correlation, p <; 0.05]. The R-squared of a regression model of the FMA scores and the EEG features was 0.89. These results suggest that the EEG patterns in motor areas correlate with motor recovery after stroke and can be used as an early predictor of motor functional outcome.

Movement-related brain oscillations vary with lesion location in severely paralyzed chronic stroke patients

In the past few years, innovative upper-limb rehabilitation methods have been proposed for chronic stroke patients. These methods aim at functional motor rehabilitation using Brain-machine interfaces to constitute an alternate pathway from the brain to the muscles. Even in patients with absence of residual finger movements, recovery could be achieved. The extent to which these interventions are affected by individual lesion topology is yet to be understood. In this study EEG was measured in 30 chronic stroke patients during movement attempts of the paretic arm. We show that the magnitude of the event-related desynchronization was smaller in patients presenting lesions with involvement of the motor cortex. This could have important implications on the design of new rehabilitation schemes for these patients, which might benefit from carefully tailored interventions.

Assessing motor imagery in brain-computer interface training: Psychological and neurophysiological correlates

Motor imagery (MI) is considered to be a promising cognitive tool for improving motor skills as well as for rehabilitation therapy of movement disorders. It is believed that MI training efficiency could be improved by using the brain-computer interface (BCI) technology providing real-time feedback on person's mental attempts. While BCI is indeed a convenient and motivating tool for practicing MI, it is not clear whether it could be used for predicting or measuring potential positive impact of the training. In this study, we are trying to establish whether the proficiency in BCI control is associated with any of the neurophysiological or psychological correlates of motor imagery, as well as to determine possible interrelations among them. For that purpose, we studied motor imagery in a group of 19 healthy BCI-trained volunteers and performed a correlation analysis across various quantitative assessment metrics. We examined subjects' sensorimotor event-related EEG events, corticospinal excitability changes estimated with single-pulse transcranial magnetic stimulation (TMS), BCI accuracy and self-assessment reports obtained with specially designed questionnaires and interview routine. Our results showed, expectedly, that BCI performance is dependent on the subject's capability to suppress EEG sensorimotor rhythms, which in turn is correlated with the idle state amplitude of those oscillations. Neither BCI accuracy nor the EEG features associated with MI were found to correlate with the level of corticospinal excitability increase during motor imagery, and with assessed imagery vividness. Finally, a significant correlation was found between the level of corticospinal excitability increase and kinesthetic vividness of imagery (KVIQ-20 questionnaire). Our results suggest that two distinct neurophysiological mechanisms might mediate possible effects of motor imagery: the non-specific cortical sensorimotor disinhibition and the focal corticospinal excitability increase. Acquired data suggests that BCI-based approach is unreliable in assessing motor imagery due to its high dependence on subject's innate EEG features (e.g. resting mu-rhythm amplitude). Therefore, employment of additional assessment protocols, such as TMS and psychological testing, is required for more comprehensive evaluation of the subject's motor imagery training efficiency.

Control of an Ambulatory Exoskeleton with a Brain-Machine Interface for Spinal Cord Injury Gait Rehabilitation

The closed-loop control of rehabilitative technologies by neural commands has shown a great potential to improve motor recovery in patients suffering from paralysis. Brain-machine interfaces (BMI) can be used as a natural control method for such technologies. BMI provides a continuous association between the brain activity and peripheral stimulation, with the potential to induce plastic changes in the nervous system. Paraplegic patients, and especially the ones with incomplete injuries, constitute a potential target population to be rehabilitated with brain-controlled robotic systems, as they may improve their gait function after the reinforcement of their spared intact neural pathways. This paper proposes a closed-loop BMI system to control an ambulatory exoskeleton-without any weight or balance support-for gait rehabilitation of incomplete spinal cord injury (SCI) patients. The integrated system was validated with three healthy subjects, and its viability in a clinical scenario was tested with four SCI patients. Using a cue-guided paradigm, the electroencephalographic signals of the subjects were used to decode their gait intention and to trigger the movements of the exoskeleton. We designed a protocol with a special emphasis on safety, as patients with poor balance were required to stand and walk. We continuously monitored their fatigue and exertion level, and conducted usability and user-satisfaction tests after the experiments. The results show that, for the three healthy subjects, 84.44 ± 14.56% of the trials were correctly decoded. Three out of four patients performed at least one successful BMI session, with an average performance of 77.6 1 ± 14.72%. The shared control strategy implemented (i.e., the exoskeleton could only move during specific periods of time) was effective in preventing unexpected movements during periods in which patients were asked to relax. On average, 55.22 ± 16.69% and 40.45 ± 16.98% of the trials (for healthy subjects and patients, respectively) would have suffered from unexpected activations (i.e., false positives) without the proposed control strategy. All the patients showed low exertion and fatigue levels during the performance of the experiments. This paper constitutes a proof-of-concept study to validate the feasibility of a BMI to control an ambulatory exoskeleton by patients with incomplete paraplegia (i.e., patients with good prognosis for gait rehabilitation).