Prolonged deficit of low gamma oscillations in the peri-infarct cortex of mice after stroke

Days and weeks after an ischemic stroke, the peri-infarct area adjacent to the necrotic tissue exhibits very intense synaptic reorganization aimed at regaining lost functions. In order to enhance functional recovery, it is important to understand the mechanisms supporting neural repair and neuroplasticity in the cortex surrounding the lesion. Brain oscillations of the local field potential (LFP) are rhythmic fluctuations of neuronal excitability that synchronize neuronal activity to organize information processing and plasticity. Although the oscillatory activity of the brain has been probed after stroke in both animals and humans using electroencephalography (EEG), the latter is ineffective to precisely map the oscillatory changes in the peri-infarct zone where synaptic plasticity potential is high. Here, we worked on the hypothesis that the brain oscillatory system is altered in the surviving peri-infarct cortex, which may slow down the functional repair and reduce the recovery. In order to document the relevance of this hypothesis, oscillatory power was measured at various distances from the necrotic core at 7 and 21 days after a permanent cortical ischemia induced in mice. Delta and theta oscillations remained at a normal power in the peri-infarct cortex, in contrast to low gamma oscillations that displayed a gradual decrease, when approaching the border of the lesion. A broadband increase of power was also observed in the homotopic contralateral sites. Thus, the proximal peri-infarct cortex could become a target of therapeutic interventions applied to correct the oscillatory regimen in order to boost post-stroke functional recovery.

Electrophysiological signatures of resting state networks predict cognitive deficits in stroke

Localized damage to different brain regions can cause specific cognitive deficits. However, stroke lesions can also induce modifications in the functional connectivity of intrinsic brain networks, which could be responsible for the behavioral impairment. Though resting state networks (RSNs) are typically mapped using fMRI, it has been recently shown that they can also be detected from high-density EEG. We build on a state-of-the-art approach to extract RSNs from 64-channels EEG activity in a group of right stroke patients and to identify neural predictors of their cognitive performance. Fourteen RSNs previously found in fMRI and high-density EEG studies on healthy participants were successfully reconstructed from our patients' EEG recordings. We then correlated EEG-RSNs functional connectivity with neuropsychological scores, first considering a wide frequency band (1-80 Hz) and then specific frequency ranges in order to examine the association between each EEG rhythm and the behavioral impairment. We found that visuo-spatial and motor impairments were primarily associated with the dorsal attention network, with contribution dependent on the specific EEG band. These findings are in line with the hypothesis that there is a core system of brain networks involved in specific cognitive domains. Moreover, our results pave the way for low-cost EEG-based monitoring of intrinsic brain networks' functioning in neurological patients to complement clinical-behavioral measures.

Are early measured resting-state EEG parameters predictive for upper limb motor impairment six months poststroke?

OBJECTIVES

Investigate whether resting-state EEG parameters recorded early poststroke can predict upper extremity motor impairment reflected by the Fugl-Meyer motor score (FM-UE) after six months, and whether they have prognostic value in addition to FM-UE at baseline.

METHODS

Quantitative EEG parameters delta/alpha ratio (DAR), brain symmetry index (BSI) and directional BSI (BSIdir) were derived from 62-channel resting-state EEG recordings in 39 adults within three weeks after a first-ever ischemic hemispheric stroke. FM-UE scores were acquired within three weeks (FM-UE_baseline) and at 26 weeks poststroke (FM-UE_w26). Linear regression analyses were performed using a forward selection procedure to predict FM-UE_w26.

RESULTS

BSI calculated over the theta band (BSI_theta) (β = -0.40; p = 0.013) was the strongest EEG-based predictor regarding FM-UE_w26. BSI_theta (β = -0.27; p = 0.006) remained a significant predictor when added to a regression model including FM-UE_baseline, increasing explained variance from 61.5% to 68.1%.

CONCLUSION

Higher BSI_theta values, reflecting more power asymmetry over the hemispheres, predict more upper limb motor impairment six months after stroke. Moreover, BSI_theta shows additive prognostic value regarding FM-UE_w26 next to FM-UE_baseline scores, and thereby contains unique information regarding upper extremity motor recovery.

SIGNIFICANCE

To our knowledge, we are the first to show that resting-state EEG parameters can serve as prognostic biomarkers of stroke recovery, in addition to FM-UE_baseline scores.

Electroencephalographic Phase Synchrony Index as a Biomarker of Poststroke Motor Impairment and Recovery

Background. Motor recovery after stroke is of great clinical interest. Besides magnetic resonance imaging functional connectivity, electroencephalographic synchrony is also an available biomarker. However, the clinical relevance of electroencephalographic synchrony in hemiparesis has not been fully understood. Objective. We aimed to demonstrate the usefulness of the phase synchrony index (PSI) by showing associations between the PSI and poststroke outcome in patients with hemiparesis. Methods. This observational study included 40 participants with cortical ischemic stroke (aged 69.8 ± 13.8 years) and 22 healthy controls (aged 66.9 ± 6.5 years). Nineteen-channel electroencephalography was recorded at 36.9 ± 11.8 days poststroke. Upper extremity Fugl-Meyer scores were assessed at the time of admission/before discharge (FM-UE1/FM-UE2; 32.6 ± 12.3/121.0 ± 44.7 days poststroke). Then, correlations between the PSIs and FM-UE1 as well as impairment reduction after rehabilitation (FM-UEgain) were analyzed. Results. The interhemispheric PSI (alpha band) between the primary motor areas (M1s) was lower in patients than in controls and was selectively correlated with FM-UE1 (P = .001). In contrast, the PSI (theta band) centered on the contralesional M1 was higher in patients than in controls and was selectively correlated with FM-UEgain (P = .003). These correlations remained significant after adjusting for confounding factors (age, time poststroke, National Institute of Health Stroke Scale, and lesion volume). Furthermore, the latter correlation was significant in severely impaired patients (FM-UE1 ≤ 10). Conclusions. This study showed that the PSIs were selectively correlated with motor impairment and recovery. Therefore, the PSIs may be potential biomarkers in persons with a hemispheric infarction.

Estimating Fugl-Meyer Upper Extremity Motor Score From Functional-Connectivity Measures

Fugl-Meyer assessment is an accepted method of evaluating motor function for people with stroke. A challenge associated with this assessment is the availability of trained examiners to carry out the evaluation. Neurophysiological biomarkers show promise in addressing the above impediment. Our study investigated the potential of using resting state electroencephalographic (EEG) functional connectivity measures as biomarkers for estimating Fugl-Meyer upper extremity motor score (FMU) in people with chronic stroke. Resting state EEG was recorded from 10 individuals with stroke. Functional connectivity was evaluated through five different processing algorithms and quantified in terms of maximum-coherence between EEG electrodes at 15 frequencies from 1 to 45 Hz. We applied a multi-variate Partial Least Squares (PLS) Correlation analysis to simultaneously identify specific connectivity channels (EEG electrode pairings) and frequencies that robustly correlated with FMU. We then applied PLS-Regression to the identified channels and frequencies to generate a set of coefficients for estimating the FMU. Participants were randomly assigned to a training-set of eight and a test-set of two. Cross-validation with leave-one-out approach on the training-set, using Phase-Lag-Index processing algorithm, resulted in an R² of 0.97 and a least-square linear fit slope of 1 for predicted versus actual FMU, with a root-mean-square error of 1.9 on FMU scale. Application of regression coefficients to the connectivity measures from the test-set resulted in predicted FMU of 47 and 38 versus actual scores of 46 and 39, respectively. Our results demonstrated that the evaluation of neural correlates of FMU shows promise in addressing the challenges associated with the availability of trained examiners to carry out the assessments.

Position-Cortical Coherence as a Marker of Afferent Pathway Integrity Early Poststroke: A Prospective Cohort Study

Background. Addressing the role of somatosensory impairment, that is, afferent pathway integrity, in poststroke motor recovery may require neurophysiological assessment. Objective. We investigated the longitudinal construct validity of position-cortical coherence (PCC), that is, the agreement between mechanically evoked wrist perturbations and electroencephalography (EEG), as a measure of afferent pathway integrity. Methods. PCC was measured serially in 48 patients after a first-ever ischemic stroke in addition to Fugl-Meyer motor assessment of the upper extremity (FM-UE) and Nottingham Sensory Assessment hand-finger subscores (EmNSA-HF, within 3 and at 5, 12, and 26 weeks poststroke. Changes in PCC over time, represented by percentage presence of PCC (%PCC), mean amplitude of PCC over the affected (Amp-A) and nonaffected hemisphere (Amp-N) and a lateralization index (L-index), were analyzed, as well as their association with FM-UE and EmNSA-HF. Patients were retrospectively categorized based on FM-UE score at baseline and 26 weeks poststroke into high- and low-baseline recoverers and non-recoverers. Results. %PCC increased from baseline to 12 weeks poststroke (β = 1.6%, CI = 0.32% to 2.86%, P = .01), which was no longer significant after adjusting for EmNSA-HF and FM-UE. A significant positive association was found between %PCC, Amp-A, and EmNSA-HF. Low-baseline recoverers (n = 8) showed longitudinally significantly higher %PCC than high-baseline recoverers (n = 23). Conclusions. We demonstrated the longitudinal construct validity of %PCC and Amp-A as a measure of afferent pathway integrity. A high %PCC in low-baseline recoverers suggests that this measure also contains information on cortical excitability. Use of PCC as an EEG-based measure to address the role of somatosensory integrity to motor recovery poststroke requires further attention.

Synaptic Plasticity Shapes Brain Connectivity: Implications for Network Topology

Studies of brain network connectivity improved understanding on brain changes and adaptation in response to different pathologies. Synaptic plasticity, the ability of neurons to modify their connections, is involved in brain network remodeling following different types of brain damage (e.g., vascular, neurodegenerative, inflammatory). Although synaptic plasticity mechanisms have been extensively elucidated, how neural plasticity can shape network organization is far from being completely understood. Similarities existing between synaptic plasticity and principles governing brain network organization could be helpful to define brain network properties and reorganization profiles after damage. In this review, we discuss how different forms of synaptic plasticity, including homeostatic and anti-homeostatic mechanisms, could be directly involved in generating specific brain network characteristics. We propose that long-term potentiation could represent the neurophysiological basis for the formation of highly connected nodes (hubs). Conversely, homeostatic plasticity may contribute to stabilize network activity preventing poor and excessive connectivity in the peripheral nodes. In addition, synaptic plasticity dysfunction may drive brain network disruption in neuropsychiatric conditions such as Alzheimer's disease and schizophrenia. Optimal network architecture, characterized by efficient information processing and resilience, and reorganization after damage strictly depend on the balance between these forms of plasticity.

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.

Critical Language Areas Show Increased Functional Connectivity in Human Cortex

Electrocortical stimulation (ECS) mapping is routinely used to identify critical language sites before resective neurosurgery. The precise locations of these sites are highly variable across patients, occurring in the frontal, temporal, and parietal lobes-it is this variability that necessitates individual patient mapping. But why these particular anatomical sites are so privileged in each patient is unknown. We hypothesized that critical language sites have greater functional connectivity with nearby cortex than sites without critical functions, since they serve as central nodes within the language network. Functional connectivity across language, motor, and cleared sites was measured in 15 patients undergoing electrocortiographic (ECoG) mapping for epilepsy surgery. Critical language sites had significantly higher connectivity than sites without critical functions (P = 0.001), and this also held for motor sites (P = 0.022). These data support the hypothesis that critical language sites are highly connected within the local cortical network, perhaps explaining why their disruption with ECS leads to transient disturbances in language function. It is our hope that improved understanding of the mechanisms of ECS will permit improved surgical planning and perhaps contribute to the understanding of normal language physiology.

Predictors for early motor improvement in patients with ischemic stroke

Disability as a stroke consequence is reported by 3% males and 2% females in general population. Motor deficits are common in stroke patients, but their complete recovery is seen only in a minority of cases. Assessment of motor deficits uses clinical methods, especially standardized scales, but also electrophysiological and imagistic methods. The motor recovery is a continuous process, maximal in the first month after stroke, decreasing gradually over the first 6 months. Most powerful predictors for motor recovery are clinical parameters: severity of motor deficit, onset of first voluntary movements after stroke in the first 48-72 hours, a continuous improvement in motor function during the first 8 weeks, a good postural control during the first month, young age, male sex, left hemispheric stroke and absence of other neurological impairments are strong positive predictors. Presence of motor-evoked potentials in paretic muscles and imagistic parameters as location, stroke volume and motor pathways integrity are paraclinical predictors for recovery. There are no specific biomarker which is efficient in predicting recovery. In patients with poor chances for recovery according to actual predictors, the development of more precise algorithms to assess functional outcome is needed, in order to support the choice of appropriate methods and intensity of rehabilitation treatment. Key words: ischemic stroke rehabilitation, functional assessment, motor improvement, recovery predictors, prognostic factors,

The functional role of beta-oscillations in the supplementary motor area during reaching and grasping after stroke: A question of structural damage to the corticospinal tract

Hand motor function is often severely affected in stroke patients. Non-satisfying recovery limits reintegration into normal daily life. Understanding stroke-related network changes and identifying common principles that might underlie recovered motor function is a prerequisite for the development of interventional therapies to support recovery. Here, we combine the evaluation of functional activity (multichannel electroencephalography) and structural integrity (diffusion tensor imaging) in order to explain the degree of residual motor function in chronic stroke patients. By recording neural activity during a reaching and grasping task that mimics activities of daily living, the study focuses on deficit-related neural activation patterns. The study showed that the functional role of movement-related beta desynchronization in the supplementary motor area (SMA) for residual hand motor function in stroke patients depends on the microstructural integrity of the corticospinal tract (CST). In particular, in patients with damaged CST, stronger task-related activity in the SMA was associated with worse residual motor function. Neither CST damage nor functional brain activity alone sufficiently explained residual hand motor function. The findings suggest a central role of the SMA in the motor network during reaching and grasping in stroke patients, the degree of functional relevance of the SMA is depending on CST integrity.

Brain networks and their relevance for stroke rehabilitation

Stroke has long been regarded as focal disease with circumscribed damage leading to neurological deficits. However, advances in methods for assessing the human brain and in statistics have enabled new tools for the examination of the consequences of stroke on brain structure and function. Thereby, it has become evident that stroke has impact on the entire brain and its network properties and can therefore be considered as a network disease. The present review first gives an overview of current methodological opportunities and pitfalls for assessing stroke-induced changes and reorganization in the human brain. We then summarize principles of plasticity after stroke that have emerged from the assessment of networks. Thereby, it is shown that neurological deficits do not only arise from focal tissue damage but also from local and remote changes in white-matter tracts and in neural interactions among wide-spread networks. Similarly, plasticity and clinical improvements are associated with specific compensatory structural and functional patterns of neural network interactions. Innovative treatment approaches have started to target such network patterns to enhance recovery. Network assessments to predict treatment response and to individualize rehabilitation is a promising way to enhance specific treatment effects and overall outcome after stroke.

Cortical beta oscillations are associated with motor performance following visuomotor learning

People vary in their capacity to learn and retain new motor skills. Although the relationship between neuronal oscillations in the beta frequency range (15-30 Hz) and motor behaviour is well established, the electrophysiological mechanisms underlying individual differences in motor learning are incompletely understood. Here, we investigated the degree to which measures of resting and movement-related beta power from sensorimotor cortex account for inter-individual differences in motor learning behaviour in the young and elderly. Twenty young (18-30 years) and twenty elderly (62-77 years) healthy adults were trained on a novel wrist flexion/extension tracking task and subsequently retested at two different time points (45-60 min and 24 h after initial training). Scalp EEG was recorded during a separate simple motor task before each training and retest session. Although short-term motor learning was comparable between young and elderly individuals, there was considerable variability within groups with subsequent analysis aiming to find the predictors of this variability. As expected, performance during the training phase was the best predictor of performance at later time points. However, regression analysis revealed that movement-related beta activity significantly explained additional variance in individual performance levels 45-60 min, but not 24 h after initial training. In the context of disease, these findings suggest that measurements of beta-band activity may offer novel targets for therapeutic interventions designed to promote rehabilitative outcomes.

Novel gait training alters functional brain connectivity during walking in chronic stroke patients: a randomized controlled pilot trial

Background

A recent study has demonstrated that a turning-based treadmill program yields greater improvements in gait speed and temporal symmetry than regular treadmill training in chronic stroke patients. However, it remains unknown how this novel and challenging gait training shapes the cortico-cortical network and cortico-spinal network during walking in chronic stroke patients. The purpose of this study was to examine how a novel type of gait training, which is an unfamiliar but effective task for people with chronic stroke, enhances brain reorganization.

Methods

Subjects in the experimental and control groups received 30 min of turning-based treadmill training and regular treadmill training, respectively. Cortico-cortical connectivity and cortico-muscular connectivity during walking and gait performance were assessed before and after completing the 12-session training.

Results

Eighteen subjects (n = 9 per group) with a mean age of 52.5 ± 9.7 years and an overground walking speed of 0.61 ± 0.26 m/s consented and participated in this study. There were significant group by time interactions for gait speed, temporal gait symmetry, and cortico-cortical connectivity as well as cortico-muscular connectivity in walk-related frequency (24–40 Hz) over the frontal-central-parietal areas. Compared with the regular treadmill training, the turning-based treadmill training resulted in greater improvements in these measures. Moreover, the increases in cortico-cortical connectivity and cortico-muscular connectivity while walking were associated with improvements in temporal gait symmetry.

Conclusions

Our findings suggest this novel turning-based treadmill training is effective for enhancing brain functional reorganization underlying cortico-cortical and corticomuscular mechanisms and thus may result in gait improvement in people with chronic stroke.

Trial registration

ACTRN12617000190303. Registered 3 February 2017, retrospectively registered.

Dynamics of brain connectivity after stroke

Recovery from a stroke is a dynamic time-dependent process, in which the central nervous system reorganises to accommodate for the impact of the injury. The purpose of this paper is to review recent longitudinal studies of changes in brain connectivity after stroke. A systematic review of research papers reporting functional or effective connectivity at two or more time points in stroke patients was conducted. Stroke leads to an early reduction of connectivity in the motor network. With recovery time, the connectivity increases and can reach the same levels as in healthy participants. The increase in connectivity is correlated with functional motor gains. A new, more randomised pattern of connectivity may then emerge in the longer term. In some instances, a pattern of increased connectivity even higher than in healthy controls can be observed, and is related either to a specific time point or to a specific neural structure. Rehabilitation interventions can help improve connectivity between specific regions. Moreover, motor network connectivity undergoes reorganisation during recovery from a stroke and can be related to behavioural recovery. A detailed analysis of changes in connectivity pattern may enable a better understanding of adaptation to a stroke and how compensatory mechanisms in the brain may be supported by rehabilitation.

Language as a Predictor of Motor Recovery: The Case for a More Global Approach to Stroke Rehabilitation

Stroke is the third leading cause of death in the developed world and the primary cause of adult disability. The most common site of stroke is the middle cerebral artery (MCA), an artery that supplies a range of areas involved in both language and motor function. As a consequence, many stroke patients experience a combination of language and motor deficits. Indeed, those suffering from Broca's aphasia have an 80% chance of also suffering hemiplegia. Despite the prevalence of multifaceted disability in patients, the current trend in both clinical trials and clinical practice is toward compartmentalization of dysfunction. In this article, we review evidence that aphasia and hemiplegia do not just coexist, but that they interact. We review a number of clinical reports describing how therapies for one type of deficit can improve recovery in the other and vice versa. We go on to describe how language deficits should be seen as a warning to clinicians that the patient is likely to experience motor impairment and slower motor recovery, aiding clinicians to optimize their choice of therapy. We explore these findings and offer a tentative link between language and arm function through their shared need for sequential action, which we term fluency. We propose that area BA44 (part of Broca's area) acts as a hub for fluency in both movement and language, both in terms of production and comprehension.

Compressibility of High-Density EEG Signals in Stroke Patients

Stroke is a critical event that causes the disruption of neural connections. There is increasing evidence that the brain tries to reorganize itself and to replace the damaged circuits, by establishing compensatory pathways. Intra- and extra-cellular currents are involved in the communication between neurons and the macroscopic effects of such currents can be detected at the scalp through electroencephalographic (EEG) sensors. EEG can be used to study the lesions in the brain indirectly, by studying their effects on the brain electrical activity. The primary goal of the present work was to investigate possible asymmetries in the activity of the two hemispheres, in the case one of them is affected by a lesion due to stroke. In particular, the compressibility of High-Density-EEG (HD-EEG) recorded at the two hemispheres was investigated since the presence of the lesion is expected to impact on the regularity of EEG signals. The secondary objective was to evaluate if standard low density EEG is able to provide such information. Eighteen patients with unilateral stroke were recruited and underwent HD-EEG recording. Each EEG signal was compressively sensed, using Block Sparse Bayesian Learning, at increasing compression rate. The two hemispheres showed significant differences in the compressibility of EEG. Signals acquired at the electrode locations of the affected hemisphere showed a better reconstruction quality, quantified by the Structural SIMilarity index (SSIM), than the EEG signals recorded at the healthy hemisphere (p < 0.05), for each compression rate value. The presence of the lesion seems to induce an increased regularity in the electrical activity of the brain, thus an increased compressibility.

Neurophysiological effects of mirror visual feedback in stroke patients with unilateral hemispheric damage

BACKGROUND AND OBJECTIVE

Mirror visual feedback (MVF; the illusory perception of movement in one hand upon viewing the moving opposite hand in a midsagittal mirror) is thought to facilitate restoration of mal-adaptive neurophysiological processes underlying conditions like complex regional pain syndrome and phantom limb pain, and to have a positive effect on brain plasticity processes underlying motor recovery after stroke. However, its exact mode of action remains unclear. The aim of the current study was to explore the immediate neurophysiological effects of MVF in patients with stroke-related hemiparesis. We also investigated how these effects relate to lesion location and extent.

METHOD

EEG and EMG data were obtained from 14 first-event sub-acute stroke patients (8 with right-, 6 with left-hemiparesis) during repeated wrist extension movements of the Non-paretic Upper-Limb (NUL), without (NUL/M-) and with (NUL/M+) a midsagittal mirror, as well as during bilateral movements with a mirror (Bil/M+). EEG data was correlated with normalized lesion data obtained from follow-up CT scans.

RESULTS

NUL movement was accompanied by an asymmetric event-related de-synchronization (ERD) of low-beta EEG oscillations, with a more conspicuous ERD in the non-affected hemisphere. In the mirror condition, ERD magnitude was attenuated in both hemispheres. Stronger attenuation in the non-affected hemisphere abolished the hemispheric asymmetry. ERD attenuation by the mirror was affected by lesion side, the severity of hemiparesis and by lesion location and extent.

CONCLUSION

Following hemispheric stroke, the magnitude of low-beta ERD accompanying unilateral movement of the non-involved upper limb, and its hemispheric asymmetry, are both reduced by MVF. Low-beta ERD dynamics may serve as a marker of neurophysiological response to MVF in research aimed to elucidate the factors influencing patients' clinical gain from this treatment.

A systematic review investigating the relationship of electroencephalography and magnetoencephalography measurements with sensorimotor upper limb impairments after stroke

BACKGROUND

Predicting sensorimotor upper limb outcome receives continued attention in stroke. Neurophysiological measures by electroencephalography (EEG) and magnetoencephalography (MEG) could increase the accuracy of predicting sensorimotor upper limb recovery.

NEW METHOD

The aim of this systematic review was to summarize the current evidence for EEG/MEG-based measures to index neural activity after stroke and the relationship between abnormal neural activity and sensorimotor upper limb impairment. Relevant papers from databases EMBASE, CINHAL, MEDLINE and pubMED were identified. Methodological quality of selected studies was assessed with the Modified Downs and Black form. Data collected was reported descriptively.

RESULTS

Seventeen papers were included; 13 used EEG and 4 used MEG applications. Findings showed that: (a) the presence of somatosensory evoked potentials in the acute stage are related to better outcome of upper limb motor impairment from 10 weeks to 6 months post-stroke; (b) an interhemispheric imbalance of cortical oscillatory signals associated with upper limb impairment; and (c) predictive models including beta oscillatory cortical signal factors with corticospinal integrity and clinical measures could enhance upper limb motor prognosis.

COMPARING WITH EXISTING METHOD

The combination of neurological biomarkers with clinical measures results in higher statistical power than using neurological biomarkers alone when predicting motor recovery in stroke.

CONCLUSIONS

Alterations in neural activity by means of EEG and MEG are demonstrated from the early post-stroke stage onwards, and related to sensorimotor upper limb impairment. Future work exploring cortical oscillatory signals in the acute stage could provide further insight about prediction of upper limb sensorimotor recovery.

Modulating functional connectivity after stroke with neurofeedback: Effect on motor deficits in a controlled cross-over study

Synchronization of neural activity as measured with functional connectivity (FC) is increasingly used to study the neural basis of brain disease and to develop new treatment targets. However, solid evidence for a causal role of FC in disease and therapy is lacking. Here, we manipulated FC of the ipsilesional primary motor cortex in ten chronic human stroke patients through brain-computer interface technology with visual neurofeedback. We conducted a double-blind controlled crossover study to test whether manipulation of FC through neurofeedback had a behavioral effect on motor performance. Patients succeeded in increasing FC in the motor cortex. This led to improvement in motor function that was significantly greater than during neurofeedback training of a control brain area and proportional to the degree of FC enhancement. This result provides evidence that FC has a causal role in neurological function and that it can be effectively targeted with therapy.

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Stroke patients participated in clinical trial on neurofeedback of functional connectivity.

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Patients learned to enhance synchrony of neural activity in their motor cortex.

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This led to reduced motor impairment.

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Evidence for a causal role of neural synchrony in neurological deficits and recovery.

Predicting Gains With Visuospatial Training After Stroke Using an EEG Measure of Frontoparietal Circuit Function

The heterogeneity of stroke prompts the need for predictors of individual treatment response to rehabilitation therapies. We previously studied healthy subjects with EEG and identified a frontoparietal circuit in which activity predicted training-related gains in visuomotor tracking. Here we asked whether activity in this same frontoparietal circuit also predicts training-related gains in visuomotor tracking in patients with chronic hemiparetic stroke. Subjects (n = 12) underwent dense-array EEG recording at rest, then received 8 sessions of visuomotor tracking training delivered via home-based telehealth methods. Subjects showed significant training-related gains in the primary behavioral endpoint, Success Rate score on a standardized test of visuomotor tracking, increasing an average of 24.2 ± 21.9% (p = 0.003). Activity in the circuit of interest, measured as coherence (20–30 Hz) between leads overlying ipsilesional frontal (motor cortex) and parietal lobe, significantly predicted training-related gains in visuomotor tracking change, measured as change in Success Rate score (r = 0.61, p = 0.037), supporting the main study hypothesis. Results were specific to the hypothesized ipsilesional motor-parietal circuit, as coherence within other circuits did not predict training-related gains. Analyses were repeated after removing the four subjects with injury to motor or parietal areas; this increased the strength of the association between activity in the circuit of interest and training-related gains. The current study found that (1) Eight sessions of training can significantly improve performance on a visuomotor task in patients with chronic stroke, (2) this improvement can be realized using home-based telehealth methods, (3) an EEG-based measure of frontoparietal circuit function predicts training-related behavioral gains arising from that circuit, as hypothesized and with specificity, and (4) incorporating measures of both neural function and neural injury improves prediction of stroke rehabilitation therapy effects.

Brain-actuated functional electrical stimulation elicits lasting arm motor recovery after stroke

Brain-computer interfaces (BCI) are used in stroke rehabilitation to translate brain signals into intended movements of the paralyzed limb. However, the efficacy and mechanisms of BCI-based therapies remain unclear. Here we show that BCI coupled to functional electrical stimulation (FES) elicits significant, clinically relevant, and lasting motor recovery in chronic stroke survivors more effectively than sham FES. Such recovery is associated to quantitative signatures of functional neuroplasticity. BCI patients exhibit a significant functional recovery after the intervention, which remains 6-12 months after the end of therapy. Electroencephalography analysis pinpoints significant differences in favor of the BCI group, mainly consisting in an increase in functional connectivity between motor areas in the affected hemisphere. This increase is significantly correlated with functional improvement. Results illustrate how a BCI-FES therapy can drive significant functional recovery and purposeful plasticity thanks to contingent activation of body natural efferent and afferent pathways.

Neuroplasticity and network connectivity of the motor cortex following stroke: A transcranial direct current stimulation study

Transcranial direct current stimulation (tDCS) is a noninvasive brain stimulation technique that has potential for clinical utility in neurorehabilitation. However, recent evidence indicates that the responses to tDCS are highly variable. This study investigated whether electroencephalographic (EEG) measures of functional connectivity of the target network were associated with the response to ipsilesional anodal tDCS in stroke survivors. Ten chronic stroke patients attended two experimental sessions in a randomized cross-over trial and received anodal or sham tDCS. Single-pulse transcranial magnetic stimulation was used to quantify change in corticospinal excitability following tDCS. At the beginning of each session, functional connectivity was estimated using the debiased-weighted phase lag index from EEG recordings at rest. Magnetic resonance imaging identified lesion location and lesion volume. Partial least squares regression identified models of connectivity which maximally accounted for variance in anodal tDCS responses. Stronger connectivity of a network with a seed approximating the stimulated ipsilesional motor cortex, and clusters of electrodes approximating the ipsilesional parietal cortex and contralesional frontotemporal cortex in the alpha band (8-13 Hz) was strongly associated with a greater increase of corticospinal excitability following anodal tDCS. This association was not observed following sham stimulation. Addition of a structural measure(s) of injury (lesion volume) provided an improved model fit for connectivity between the seed electrode and ipsilesional parietal cortex, but not the contralesional frontotemporal cortex. TDCS has potential to greatly assist stroke rehabilitation and functional connectivity appears a robust and specific biomarker of response which may assist clinical translation of this therapy.

Parietofrontal network upregulation after motor stroke

Objective

Motor recovery after stroke shows a high inter-subject variability. The brain's potential to form new connections determines individual levels of recovery of motor function. Most of our daily activities require visuomotor integration, which engages parietal areas. Compared to the frontal motor system, less is known about the parietal motor system's reconfiguration related to stroke recovery. Here, we tested if functional connectivity among parietal and frontal motor areas undergoes plastic changes after stroke and assessed the behavioral relevance for motor function after stroke.

Methods

We investigated stroke lesion-induced changes in functional connectivity by measuring high-density electroencephalography (EEG) and assessing task-related changes in coherence during a visually guided grip task with the paretic hand in 30 chronic stroke patients with variable motor deficits and 19 healthy control subjects. Quantitative changes in task-related coherence in sensorimotor rhythms were compared to the residual motor deficit.

Results

Parietofrontal coupling was significantly stronger in patients compared to controls. Whereas motor network coupling generally increased during the task in both groups, the task-related coherence between the parietal and primary motor cortex in the stroke lesioned hemisphere showed increased connectivity across a broad range of sensorimotor rhythms. Particularly the parietofrontal task-induced coupling pattern was significantly and positively related to residual impairment in the Nine-Hole Peg Test performance and grip force.

Interpretation

These results demonstrate that parietofrontal motor system integration during visually guided movements is stronger in the stroke-lesioned brain. The correlation with the residual motor deficit could either indicate an unspecific marker of motor network damage or it might indicate that upregulated parietofrontal connectivity has some impact on post-stroke motor function.

Considerations for the Use of Neuroimaging Technologies for Predicting Recovery of Speech and Language in Aphasia

PURPOSE

The number of research articles aimed at identifying neuroimaging biomarkers for predicting recovery from aphasia continues to grow. Although the clinical use of these biomarkers to determine prognosis has been proposed, there has been little discussion of how this would be accomplished. This is an important issue because the best translational science occurs when translation is considered early in the research process. The purpose of this clinical focus article is to present a framework to guide the discussion of how neuroimaging biomarkers for recovery from aphasia could be implemented clinically.

METHOD

The genomics literature reveals that implementing genetic testing in the real-world poses both opportunities and challenges. There is much similarity between these opportunities and challenges and those related to implementing neuroimaging testing to predict recovery in aphasia. Therefore, the Center for Disease Control's model list of questions aimed at guiding the review of genetic testing has been adapted to guide the discussion of using neuroimaging biomarkers as predictors of recovery in aphasia.

CONCLUSION

The adapted model list presented here is a first and useful step toward initiating a discussion of how neuroimaging biomarkers of recovery could be employed clinically to provide improved quality of care for individuals with aphasia.

Longitudinal Structural and Functional Differences Between Proportional and Poor Motor Recovery After Stroke

BACKGROUND

Evolution of motor function during the first months after stroke is stereotypically bifurcated, consisting of either recovery to about 70% of maximum possible improvement ("proportional recovery, PROP") or in little to no improvement ("poor recovery, POOR"). There is currently no evidence that any rehabilitation treatment will prevent POOR and favor PROP.

OBJECTIVE

To perform a longitudinal and multimodal assessment of functional and structural changes in brain organization associated with PROP.

METHODS

Fugl-Meyer Assessments of the upper extremity and high-density electroencephalography (EEG) were obtained from 63 patients, diffusion tensor imaging from 46 patients, at 2 and 4 weeks (T0) and at 3 months (T1) after stroke onset.

RESULTS

We confirmed the presence of 2 distinct recovery patterns (PROP and POOR) in our sample. At T0, PROP patients had greater integrity of the corticospinal tract (CST) and greater EEG functional connectivity (FC) between the affected hemisphere and rest of the brain, in particular between the ventral premotor and the primary motor cortex. POOR patients suffered from degradation of corticocortical and corticofugal fiber tracts in the affected hemisphere between T0 and T1, which was not observed in PROP patients. Better initial CST integrity correlated with greater initial global FC, which was in turn associated with less white matter degradation between T0 and T1.

CONCLUSIONS

These findings suggest links between initial CST integrity, systems-level cortical network plasticity, reduction of white matter atrophy, and clinical motor recovery after stroke. This identifies candidate treatment targets.

Early Rehabilitation After Stroke: a Narrative Review

PURPOSE OF REVIEW

Despite current rehabilitative strategies, stroke remains a leading cause of disability in the USA. There is a window of enhanced neuroplasticity early after stroke, during which the brain's dynamic response to injury is heightened and rehabilitation might be particularly effective. This review summarizes the evidence of the existence of this plastic window, and the evidence regarding safety and efficacy of early rehabilitative strategies for several stroke domain-specific deficits.

RECENT FINDINGS

Overall, trials of rehabilitation in the first 2 weeks after stroke are scarce. In the realm of very early mobilization, one large and one small trial found potential harm from mobilizing patients within the first 24 h after stroke, and only one small trial found benefit in doing so. For the upper extremity, constraint-induced movement therapy appears to have benefit when started within 2 weeks of stroke. Evidence for non-invasive brain stimulation in the acute period remains scant and inconclusive. For aphasia, the evidence is mixed, but intensive early therapy might be of benefit for patients with severe aphasia. Mirror therapy begun early after stroke shows promise for the alleviation of neglect. Novel approaches to treating dysphagia early after stroke appear promising, but the high rate of spontaneous improvement makes their benefit difficult to gauge. The optimal time to begin rehabilitation after a stroke remains unsettled, though the evidence is mounting that for at least some deficits, initiation of rehabilitative strategies within the first 2 weeks of stroke is beneficial. Commencing intensive therapy in the first 24 h may be harmful.

Effective assessments of electroencephalography during stroke recovery: contemporary approaches and considerations

Stroke is one of the leading causes of permanent disability worldwide, relying conventionally on extended periods of physiotherapy to recover functional ability. While neuroimaging techniques and emerging neurorehabilitation paradigms have advanced our understanding of pathophysiological mechanisms underlying stroke, recent evidence has renewed focus on quantifying features of cortical activity present in electroencephalography recordings to greatly enhance our understanding of stroke treatment and recovery. This Neuro Forum article reviews these key advances and discusses the importance of quantifying electroencephalography in future assessments of stroke survivors.

EEG-based motor network biomarkers for identifying target patients with stroke for upper limb rehabilitation and its construct validity

Rehabilitation is the main therapeutic approach for reducing poststroke functional deficits in the affected upper limb; however, significant between-patient variability in rehabilitation efficacy indicates the need to target patients who are likely to have clinically significant improvement after treatment. Many studies have determined robust predictors of recovery and treatment gains and yielded many great results using linear approachs. Evidence has emerged that the nonlinearity is a crucial aspect to study the inter-areal communication in human brains and abnormality of oscillatory activities in the motor system is linked to the pathological states. In this study, we hypothesized that combinations of linear and nonlinear (cross-frequency) network connectivity parameters are favourable biomarkers for stratifying patients for upper limb rehabilitation with increased accuracy. We identified the biomarkers by using 37 prerehabilitation electroencephalogram (EEG) datasets during a movement task through effective connectivity and logistic regression analyses. The predictive power of these biomarkers was then tested by using 16 independent datasets (i.e. construct validation). In addition, 14 right handed healthy subjects were also enrolled for comparisons. The result shows that the beta plus gamma or theta network features provided the best classification accuracy of 92%. The predictive value and the sensitivity of these biomarkers were 81.3% and 90.9%, respectively. Subcortical lesion, the time poststroke and initial Wolf Motor Function Test (WMFT) score were identified as the most significant clinical variables affecting the classification accuracy of this predictive model. Moreover, 12 of 14 normal controls were classified as having favourable recovery. In conclusion, EEG-based linear and nonlinear motor network biomarkers are robust and can help clinical decision making.

Injured Brains and Adaptive Networks: The Benefits and Costs of Hyperconnectivity

A common finding in human functional brain-imaging studies is that damage to neural systems paradoxically results in enhanced functional connectivity between network regions, a phenomenon commonly referred to as 'hyperconnectivity'. Here, we describe the various ways that hyperconnectivity operates to benefit a neural network following injury while simultaneously negotiating the trade-off between metabolic cost and communication efficiency. Hyperconnectivity may be optimally expressed by increasing connections through the most central and metabolically efficient regions (i.e., hubs). While adaptive in the short term, we propose that chronic hyperconnectivity may leave network hubs vulnerable to secondary pathological processes over the life span due to chronically elevated metabolic stress. We conclude by offering novel, testable hypotheses for advancing our understanding of the role of hyperconnectivity in systems-level brain plasticity in neurological disorders.

Neuroplasticity of language in left-hemisphere stroke: Evidence linking subsecond electrophysiology and structural connections

The understanding of neuroplasticity following stroke is predominantly based on neuroimaging measures that cannot address the subsecond neurodynamics of impaired language processing. We combined behavioral and electrophysiological measures and structural-connectivity estimates to characterize neuroplasticity underlying successful compensation of language abilities after left-hemispheric stroke. We recorded the electroencephalogram from patients with stroke lesions to the left temporal lobe and from matched controls during context-driven word retrieval. Participants heard lead-in sentences that either constrained the final word ("He locked the door with the") or not ("She walked in here with the"). The last word was shown as a picture to be named. Individual-participant analyses were conducted, focusing on oscillatory power as a subsecond indicator of a brain region's functional neurophysiological computations. All participants named pictures faster following constrained than unconstrained sentences, except for two patients, who had extensive damage to the left temporal lobe. Left-lateralized alpha-beta oscillatory power decreased in controls pre-picture presentation for constrained relative to unconstrained contexts. In patients, the alpha-beta power decreases were observed with the same time course as in controls but were lateralized to the intact right hemisphere. The right lateralization depended on the probability of white-matter connections between the bilateral temporal lobes. The two patients who performed poorly behaviorally showed no alpha-beta power decreases. Our findings suggest that incorporating direct measures of neural activity into investigations of neuroplasticity can provide important neural markers to help predict language recovery, assess the progress of neurorehabilitation, and delineate targets for therapeutic neuromodulation. Hum Brain Mapp 38:3151-3162, 2017. © 2017 Wiley Periodicals, Inc.

Movement-related beta oscillations show high intra-individual reliability

Oscillatory activity in the beta frequency range (15-30Hz) recorded from human sensorimotor cortex is of increasing interest as a putative biomarker of motor system function and dysfunction. Despite its increasing use in basic and clinical research, surprisingly little is known about the test-retest reliability of spectral power and peak frequency measures of beta oscillatory signals from sensorimotor cortex. Establishing that these beta measures are stable over time in healthy populations is a necessary precursor to their use in the clinic. Here, we used scalp electroencephalography (EEG) to evaluate intra-individual reliability of beta-band oscillations over six sessions, focusing on changes in beta activity during movement (Movement-Related Beta Desynchronization, MRBD) and after movement termination (Post-Movement Beta Rebound, PMBR). Subjects performed visually-cued unimanual wrist flexion and extension. We assessed Intraclass Correlation Coefficients (ICC) and between-session correlations for spectral power and peak frequency measures of movement-related and resting beta activity. Movement-related and resting beta power from both sensorimotor cortices was highly reliable across sessions. Resting beta power yielded highest reliability (average ICC=0.903), followed by MRBD (average ICC=0.886) and PMBR (average ICC=0.663). Notably, peak frequency measures yielded lower ICC values compared to the assessment of spectral power, particularly for movement-related beta activity (ICC=0.386-0.402). Our data highlight that power measures of movement-related beta oscillations are highly reliable, while corresponding peak frequency measures show greater intra-individual variability across sessions. Importantly, our finding that beta power estimates show high intra-individual reliability over time serves to validate the notion that these measures reflect meaningful individual differences that can be utilised in basic research and clinical studies.

Proprioceptive Feedback Facilitates Motor Imagery-Related Operant Learning of Sensorimotor β-Band Modulation

Motor imagery (MI) activates the sensorimotor system independent of actual movements and might be facilitated by neurofeedback. Knowledge on the interaction between feedback modality and the involved frequency bands during MI-related brain self-regulation is still scarce. Previous studies compared the cortical activity during the MI task with concurrent feedback (MI with feedback condition) to cortical activity during the relaxation task where no feedback was provided (relaxation without feedback condition). The observed differences might, therefore, be related to either the task or the feedback. A proper comparison would necessitate studying a relaxation condition with feedback and a MI task condition without feedback as well. Right-handed healthy subjects performed two tasks, i.e., MI and relaxation, in alternating order. Each of the tasks (MI vs. relaxation) was studied with and without feedback. The respective event-driven oscillatory activity, i.e., sensorimotor desynchronization (during MI) or synchronization (during relaxation), was rewarded with contingent feedback. Importantly, feedback onset was delayed to study the task-related cortical activity in the absence of feedback provision during the delay period. The reward modality was alternated every 15 trials between proprioceptive and visual feedback. Proprioceptive input was superior to visual input to increase the range of task-related spectral perturbations in the α- and β-band, and was necessary to consistently achieve MI-related sensorimotor desynchronization (ERD) significantly below baseline. These effects occurred in task periods without feedback as well. The increased accuracy and duration of learned brain self-regulation achieved in the proprioceptive condition was specific to the β-band. MI-related operant learning of brain self-regulation is facilitated by proprioceptive feedback and mediated in the sensorimotor β-band.

What Turns Assistive into Restorative Brain-Machine Interfaces?

Brain-machine interfaces (BMI) may support motor impaired patients during activities of daily living by controlling external devices such as prostheses (assistive BMI). Moreover, BMIs are applied in conjunction with robotic orthoses for rehabilitation of lost motor function via neurofeedback training (restorative BMI). Using assistive BMI in a rehabilitation context does not automatically turn them into restorative devices. This perspective article suggests key features of restorative BMI and provides the supporting evidence: In summary, BMI may be referred to as restorative tools when demonstrating subsequently (i) operant learning and progressive evolution of specific brain states/dynamics, (ii) correlated modulations of functional networks related to the therapeutic goal, (iii) subsequent improvement in a specific task, and (iv) an explicit correlation between the modulated brain dynamics and the achieved behavioral gains. Such findings would provide the rationale for translating BMI-based interventions into clinical settings for reinforcement learning and motor rehabilitation following stroke.

Acute Exposure to Pacific Ciguatoxin Reduces Electroencephalogram Activity and Disrupts Neurotransmitter Metabolic Pathways in Motor Cortex

Ciguatera fish poisoning (CFP) is a common human food poisoning caused by consumption of ciguatoxin (CTX)-contaminated fish affecting over 50,000 people worldwide each year. CTXs are classified depending on their origin from the Pacific (P-CTXs), Indian Ocean (I-CTXs), and Caribbean (C-CTXs). P-CTX-1 is the most toxic CTX known and the major source of CFP causing an array of neurological symptoms. Neurological symptoms in some CFP patients last for several months or years; however, the underlying electrophysiological properties of acute exposure to CTXs remain unknown. Here, we used CTX purified from ciguatera fish sourced in the Pacific Ocean (P-CTX-1). Delta and theta electroencephalography (EEG) activity was reduced remarkably in 2 h and returned to normal in 6 h after a single exposure. However, second exposure to P-CTX-1 induced not only a further reduction in EEG activities but also a 2-week delay in returning to baseline EEG values. Ciguatoxicity was detected in the brain hours after the first and second exposure by mouse neuroblastoma assay. The spontaneous firing rate of single motor cortex neuron was reduced significantly measured by single-unit recording with high spatial resolution. Expression profile study of neurotransmitters using targeted profiling approach based on liquid chromatography-tandem mass spectrometry revealed an imbalance between excitatory and inhibitory neurotransmitters in the motor cortex. Our study provides a possible link between the brain oscillations and neurotransmitter release after acute exposure to P-CTX-1. Identification of EEG signatures and major metabolic pathways affected by P-CTX-1 provides new insight into potential biomarker development and therapeutic interventions.

Spontaneous and Therapeutic-Induced Mechanisms of Functional Recovery After Stroke

With increasing rates of survival throughout the past several years, stroke remains one of the leading causes of adult disability. Following the onset of stroke, spontaneous mechanisms of recovery at the cellular, molecular, and systems levels ensue. The degree of spontaneous recovery is generally incomplete and variable among individuals. Typically, the best recovery outcomes entail the restitution of function in injured but surviving neural matter. An assortment of restorative therapies exists or is under development with the goal of potentiating restitution of function in damaged areas or in nearby ipsilesional regions by fostering neuroplastic changes, which often rely on mechanisms similar to those observed during spontaneous recovery. Advancements in stroke rehabilitation depend on the elucidation of both spontaneous and therapeutic-driven mechanisms of recovery. Further, the implementation of neural biomarkers in research and clinical settings will enable a multimodal approach to probing brain state and predicting the extent of post-stroke functional recovery. This review will discuss spontaneous and therapeutic-induced mechanisms driving post-stroke functional recovery while underscoring several potential restorative therapies and biomarkers.