Changes in resting state effective connectivity in the motor network following rehabilitation of upper extremity poststroke paresis

Whole-brain functional connectivity and structural network properties in stroke patients with hemiplegia

OBJECTIVE

This study explored structural and functional alterations in the whole brain of stroke patients with hemiplegia.

METHODS

We collected multimodal magnetic resonance images of 24 patients with ischaemic stroke and 16 age-matched controls. Resting-state functional connectivity (FC) for all brain regions was evaluated. Diffusion tensor imaging was used to construct white matter structural networks, and the graph properties of the structural network were analysed using graph theory to determine group differences.

RESULTS

The ipsilesional posterior parietal cortex (PPC) in the frontoparietal network accounts for more than half of the 25 brain regions with altered FC in stroke patients. The nodal efficiency of multiple ipsilesional frontal lobes and cerebellar regions, such as the ipsilateral cerebellum 8, was reduced. The contralesional cerebellum 8 showed elevated FC with the lingual gyrus and the visual network.

CONCLUSIONS

Our results suggest that the PPC and cerebellum 8 are regions worthy of in-depth study. The cerebellum 8 may supplement deficits in motor balance function by enhancing functional congruence with the visual area.

SIGNIFICANCE

This study identified key brain regions and characteristics that exhibit structural and functional changes following stroke injury.

Stroke-induced neuroplasticity in spiny mice in the absence of tissue regeneration

Stroke is a major cause of disability for adults over 40 years of age. While research into animal models has prioritized treatments aimed at diminishing post-stroke damage, no studies have investigated the response to a severe stroke injury in a highly regenerative adult mammal. Here we investigate the effects of transient ischemia on adult spiny mice, Acomys cahirinus, due to their ability to regenerate multiple tissues without scarring. Transient middle cerebral artery occlusion was performed and Acomys showed rapid behavioral recovery post-stroke yet failed to regenerate impacted brain regions. An Acomys brain atlas in combination with functional (f)MRI demonstrated recovery coincides with neuroplasticity. The strength and quality of the global connectome are preserved post-injury with distinct contralateral and ipsilateral brain regions compensating for lost tissue. Thus, we propose Acomys recovers functionally from an ischemic stroke injury not by tissue regeneration but by altering its brain connectome.

Network Reorganization for Neurophysiological and Behavioral Recovery Following Stroke

Stroke continues to be the main cause of motor disability worldwide. While rehabilitation has been promised to improve recovery after stroke, efficacy in clinical trials has been mixed. We need to understand the cortical recombination framework to understand how biomarkers for neurophysiological reorganized neurotechnologies alter network activity. Here, we summarize the principles of the movement network, including the current evidence of changes in the connections and function of encephalic regions, recovery from stroke and the therapeutic effects of rehabilitation. Overall, improvements or therapeutic effects in limb motor control following stroke are correlated with the effects of interhemispheric competition or compensatory models of the motor supplementary cortex. This review suggests that future research should focus on cross-regional communication and provide fundamental insights into further treatment and rehabilitation for post-stroke patients.

Relationship between resting-state functional connectivity and change in motor function after motor imagery intervention in patients with stroke: a scoping review

BACKGROUND

In clinical practice, motor imagery has been proposed as a treatment modality for stroke owing to its feasibility in patients with severe motor impairment. Motor imagery-based interventions can be categorized as open- or closed-loop. Closed-loop intervention is based on voluntary motor imagery and induced peripheral sensory afferent (e.g., Brain Computer Interface (BCI)-based interventions). Meanwhile, open-loop interventions include methods without voluntary motor imagery or sensory afferent. Resting-state functional connectivity (rs-FC) is defined as a significant temporal correlated signal among functionally related brain regions without any stimulus. rs-FC is a powerful tool for exploring the baseline characteristics of brain connectivity. Previous studies reported changes in rs-FC after motor imagery interventions. Systematic reviews also reported the effects of motor imagery-based interventions at the behavioral level. This study aimed to review and describe the relationship between the improvement in motor function and changes in rs-FC after motor imagery in patients with stroke.

REVIEW PROCESS

The literature review was based on Arksey and O'Malley's framework. PubMed, Ovid MEDLINE, Cochrane Central Register of Controlled Trials, and Web of Science were searched up to September 30, 2023. The included studies covered the following topics: illusion without voluntary action, motor imagery, action imitation, and BCI-based interventions. The correlation between rs-FC and motor function before and after the intervention was analyzed. After screening by two independent researchers, 13 studies on BCI-based intervention, motor imagery intervention, and kinesthetic illusion induced by visual stimulation therapy were included.

CONCLUSION

All studies relating to motor imagery in this review reported improvement in motor function post-intervention. Furthermore, all those studies demonstrated a significant relationship between the change in motor function and rs-FC (e.g., sensorimotor network and parietal cortex).

Functional MRI evaluation of hyperbaric oxygen therapy effect on hand motor recovery in a chronic post-stroke patient: a case report and physiological discussion

Introduction

Impairments in activities of daily living (ADL) are a major concern in post-stroke rehabilitation. Upper-limb motor impairments, specifically, have been correlated with low quality of life. In the current case report, we used both task-based and resting state functional MRI (fMRI) tools to investigate the neural response mechanisms and functional reorganization underlying hyperbaric oxygen therapy (HBOT)-induced motor rehabilitation in a chronic post-stroke patient suffering from severe upper-limb motor impairment.

Methods

We studied motor task fMRI activation and resting-state functional connectivity (rsFC) in a 61-year-old right-handed male patient who suffered hemiparesis and physical weakness in the right upper limb, 2 years after his acute insult, pre- and post-treatment of 60 daily HBOT sessions. Motor functions were assessed at baseline and at the end of the treatment using the Fugl-Meyer assessment (FMA) and the handgrip maximum voluntary contraction (MVC).

Results

Following HBOT, the FMA score improved from 17 (severe impairment) to 31 (moderate impairment). Following the intervention during trials involving the affected hand, there was an observed increase in fMRI activation in both the supplementary motor cortex (SMA) and the premotor cortex (PMA) bilaterally. The lateralization index (LI) decreased from 1 to 0.63, demonstrating the recruitment of the contralesional hemisphere. The region of interest, ROI-to-ROI, analysis revealed increased post-intervention inter-hemispheric connectivity (P = 0.002) and a between-network connectivity increase (z-score: 0.35 ± 0.21 to 0.41 ± 0.21, P < 0.0001). Seed-to-voxel-based rsFC analysis using the right SMA as seed showed increased connectivity to the left posterior parietal cortex, the left primary somatosensory cortex, and the premotor cortex.

Conclusion

This study provides additional insights into HBOT-induced brain plasticity and functional improvement in chronic post-stroke patients.

Aberrant interhemispheric functional reciprocities of the default mode network and motor network in subcortical ischemic stroke patients with motor impairment: A longitudinal study

Purpose

The purpose of the present study was to explore the longitudinal changes in functional homotopy in the default mode network (DMN) and motor network and its relationships with clinical characteristics in patients with stroke.

Methods

Resting-state functional magnetic resonance imaging was performed in stroke patients with subcortical ischemic lesions and healthy controls. The voxel-mirrored homotopic connectivity (VMHC) method was used to examine the differences in functional homotopy in patients with stroke between the two time points. Support vector machine (SVM) and correlation analyses were also applied to investigate whether the detected significant changes in VMHC were the specific feature in patients with stroke.

Results

The patients with stroke had significantly lower VMHC in the DMN and motor-related regions than the controls, including in the precuneus, parahippocampus, precentral gyrus, supplementary motor area, and middle frontal gyrus. Longitudinal analysis revealed that the impaired VMHC of the superior precuneus showed a significant increase at the second time point, which was no longer significantly different from the controls. Between the two time points, the changes in VMHC in the superior precuneus were significantly correlated with the changes in clinical scores. SVM analysis revealed that the VMHC of the superior precuneus could be used to correctly identify the patients with stroke from the controls with a statistically significant accuracy of 81.25% (P ≤ 0.003).

Conclusions

Our findings indicated that the increased VMHC in the superior precuneus could be regarded as the neuroimaging manifestation of functional recovery. The significant correlation and the discriminative power in classification results might provide novel evidence to understand the neural mechanisms responsible for brain reorganization after stroke.

Ability of an altered functional coupling between resting-state networks to predict behavioral outcomes in subcortical ischemic stroke: A longitudinal study

Stroke can be viewed as an acute disruption of an individual's connectome caused by a focal or widespread loss of blood flow. Although individuals exhibit connectivity changes in multiple functional networks after stroke, the neural mechanisms that underlie the longitudinal reorganization of the connectivity patterns are still unclear. The study aimed to determine whether brain network connectivity patterns after stroke can predict longitudinal behavioral outcomes. Nineteen patients with stroke with subcortical lesions underwent two sessions of resting-state functional magnetic resonance imaging scanning at a 1-month interval. By independent component analysis, the functional connectivity within and between multiple brain networks (including the default mode network, the dorsal attention network, the limbic network, the visual network, and the frontoparietal network) was disrupted after stroke and partial recovery at the second time point. Additionally, regression analyses revealed that the connectivity between the limbic and dorsal attention networks at the first time point showed sufficient reliability in predicting the clinical scores (Fugl-Meyer Assessment and Neurological Deficit Scores) at the second time point. The overall findings suggest that functional coupling between the dorsal attention and limbic networks after stroke can be regarded as a biomarker to predict longitudinal clinical outcomes in motor function and the degree of neurological functional deficit. Overall, the present study provided a novel opportunity to improve prognostic ability after subcortical strokes.

Upper extremity self-efficacy correlates with daily hand-use of individuals with high functional capacity post-stroke

PURPOSE

To understand the role of affected upper extremity (UE) self-efficacy for explaining daily-hand-use in individuals post-stroke. Specifically, to describe UE self-efficacy and to assess the associations between UE self-efficacy to UE motor and functional capacity and daily hand-use.

MATERIALS AND METHODS

This cross-sectional study included individuals post-stroke receiving rehabilitation with high UE functional capacity [Action Research Arm Test (ARAT) > 50]. The Rating of Everyday Arm-Use in the Community and Home (REACH) assessed perceived UE daily use and the Confidence in Arm and Hand Movement scale (CAHM) assessed UE self-efficacy. Functional capacity was assessed by the ARAT and the Fugl-Meyer-motor-assessment assessed motor impairment. Correlations between measures were assessed.

RESULTS

Twenty-two individuals, aged 19-80, with high UE functional capacity [median (IQR) ARAT-56.5 (54-57)] and varying UE self-efficacy [median (IQR) CAHM-76.7 (58-84.4)], were included. UE self-efficacy was significantly correlated with the ARAT (r_s = 0.53, p < 0.01) and REACH (r_s = 0.51, p < 0.01) but ARAT was not significantly correlated with REACH.

CONCLUSIONS

UE self-efficacy is correlated with perceived daily hand-use in individuals with high functional capacity. Further research and a deeper understanding of the clinical implications of UE self-efficacy are warranted. UE self-efficacy should perhaps be assessed during rehabilitation. IMPLICATIONS FOR REHABILITATIONIndividuals with stroke with high affected upper extremity functional capacity do not necessarily use this hand for daily living.Upper extremity self-efficacy is correlated with perceived daily hand-use in individuals with high functional capacity; participants with higher upper extremity self-efficacy also reported more daily hand-use.Upper extremity self-efficacy seems to be upper extremity task or situation-specific.Upper extremity self-efficacy should be assessed during rehabilitation and the clinical implications of (low) upper extremity self-efficacy should be further researched.

More than just statics: Altered complexity of dynamic amplitude of low-frequency fluctuations in the resting brain after stroke

OBJECTIVE

Previous neuroimaging studies mainly focused on static characteristics of brain activity, and little is known about its characteristics over time, especially in post-stroke (PS) patients. In this study, we aimed to investigate the static and dynamic characteristics of brain activity after stroke using functional magnetic resonance imaging (fMRI).

APPROACH

Twenty ischemic PS patients and nineteen healthy controls (HCs) were recruited to receive a resting-state fMRI scanning. The static amplitude of low-frequency fluctuations (sALFF) and fuzzy entropy of dynamic ALFF (FE-dALFF) were applied to identify the stroke-induced alterations.

MAIN RESULTS

Compared with the HCs, PS patients showed significantly increased FE-dALFF values in the right angular gyrus (ANG), bilateral precuneus (PCUN), and right inferior parietal lobule (IPL) as well as significantly decreased FE-dALFF values in the right postcentral gyrus (PoCG), right dorsolateral superior frontal gyrus (SFGdor), and right precentral gyrus (PreCG). The ROC analyses demonstrated that FE-dALFF and sALFF possess comparable sensitivity in distinguishing PS patients from the HCs. Moreover, a significantly positive correlation was observed between the FE-dALFF values and the Fugl-Meyer Assessment (FMA) scores in the right SFGdor (r =0.547), right IPL (r =0.522), and right PCUN (r =0.486).

SIGNIFICANCE

This study provided insight into the stroke-induced alterations in static and dynamic characteristics of local brain activity, highlighting the potential of FE-dALFF in understanding neurophysiological mechanisms and evaluating pathological changes.

Resting State EEG Directed Functional Connectivity Unveils Changes in Motor Network Organization in Subacute Stroke Patients After Rehabilitation

Brain plasticity and functional reorganization are mechanisms behind functional motor recovery of patients after an ischemic stroke. The study of resting-state motor network functional connectivity by means of EEG proved to be useful in investigating changes occurring in the information flow and find correlation with motor function recovery. In the literature, most studies applying EEG to post-stroke patients investigated the undirected functional connectivity of interacting brain regions. Quite recently, works started to investigate the directionality of the connections and many approaches or features have been proposed, each of them being more suitable to describe different aspects, e.g., direct or indirect information flow between network nodes, the coupling strength or its characteristic oscillation frequency. Each work chose one specific measure, despite in literature there is not an agreed consensus, and the selection of the most appropriate measure is still an open issue. In an attempt to shed light on this methodological aspect, we propose here to combine the information of direct and indirect coupling provided by two frequency-domain measures based on Granger’s causality, i.e., the directed coherence (DC) and the generalized partial directed coherence (gPDC), to investigate the longitudinal changes of resting-state directed connectivity associated with sensorimotor rhythms α and β, occurring in 18 sub-acute ischemic stroke patients who followed a rehabilitation treatment. Our results showed a relevant role of the information flow through the pre-motor regions in the reorganization of the motor network after the rehabilitation in the sub-acute stage. In particular, DC highlighted an increase in intra-hemispheric coupling strength between pre-motor and primary motor areas, especially in ipsi-lesional hemisphere in both α and β frequency bands, whereas gPDC was more sensitive in the detection of those connection whose variation was mostly represented within the population. A decreased causal flow from contra-lesional premotor cortex towards supplementary motor area was detected in both α and β frequency bands and a significant reinforced inter-hemispheric connection from ipsi to contra-lesional pre-motor cortex was observed in β frequency. Interestingly, the connection from contra towards ipsilesional pre-motor area correlated with upper limb motor recovery in α band. The usage of two different measures of directed connectivity allowed a better comprehension of those coupling changes between brain motor regions, either direct or mediated, which mostly were influenced by the rehabilitation, revealing a particular involvement of the pre-motor areas in the cerebral functional reorganization.

Functional brain networks assessed with surface electroencephalography for predicting motor recovery in a neural guided intervention for chronic stroke

Predicting whether a chronic stroke patient is likely to benefit from a specific intervention can help patients establish reasonable expectations. It also provides the basis for candidates selecting for the intervention. Recent convergent evidence supports the value of network-based approach for understanding the relationship between dysfunctional neural activity and motor deficits after stroke. In this study, we applied resting-state brain connectivity networks to investigate intervention-specific predictive biomarkers of motor improvement in 22 chronic stroke participants who received either combined action observation with EEG-guided robot-hand training (Neural Guided-Action Observation Group, n = 12, age: 34–68 years) or robot-hand training without action observation and EEG guidance (non-Neural Guided-text group, n = 10, age: 42–57 years). The robot hand in Neural Guided-Action Observation training was activated only when significant mu suppression (8–12 Hz) was detected from participant’s EEG signals in ipsilesional hemisphere while it was randomly activated in non-Neural Guided-text training. Only the Neural Guided-Action Observation group showed a significant long-term improvement in their upper-limb motor functions (P < 0.5). In contrast, no significant training effect on the paretic motor functions was found in the non-Neural Guided-text group (P > 0.5). The results of brain connectivity estimated via EEG coherence showed that the pre-training interhemispheric connectivity of delta, theta, alpha and contralesional connectivity of beta were motor improvement related in the Neural Guided-Action Observation group. They can not only differentiate participants with good and poor recovery (interhemispheric delta: P = 0.047, Hedges’ g = 1.409; interhemispheric theta: P = 0.046, Hedges’ g = 1.333; interhemispheric alpha: P = 0.038, Hedges’ g = 1.536; contralesional beta: P = 0.027, Hedges’ g = 1.613) but also significantly correlated with post-training intervention gains (interhemispheric delta: r = −0.901, P < 0.05; interhemispheric theta: r = −0.702, P < 0.05; interhemispheric alpha: r = −0.641, P < 0.05; contralesional beta: r = −0.729, P < 0.05). In contrast, no EEG coherence was significantly correlated with intervention gains in the non-Neural Guided-text group (all Ps>0.05). Partial least square regression showed that the combination of pre-training interhemispheric and contralesional local connectivity could precisely predict intervention gains in the Neural Guided-Action Observation group with a strong correlation between predicted and observed intervention gains (r = 0.82r=0.82) and between predicted and observed intervention outcomes (r = 0.90r=0.90). In summary, EEG-based resting-state brain connectivity networks may serve clinical decision-making by offering an approach to predicting Neural Guided-Action Observation training-induced motor improvement.

MRI markers of functional connectivity and tissue microstructure in stroke-related motor rehabilitation: A systematic review

BACKGROUND

Stroke-related disability is a major problem at individual and socio-economic levels. Neuromotor rehabilitation has a key role for its dual action on affected body segment and brain reorganization. Despite its known efficacy in clinical practice, the extent and type of effect at a brain level, mediated by neuroplasticity, are still under question.

OBJECTIVE

To analyze studies applying MRI markers of functional and structural connectivity in patients affected with stroke undergoing motor rehabilitation, and to evaluate the effect of rehabilitation on brain reorganization.

METHODS

Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) criteria were applied to select studies applying quantitative non-conventional MRI techniques on patients undergoing motor rehabilitation, both physical and virtual (virtual reality, mental imagery). Literature search was conducted using MEDLINE (via PubMed), Cochrane Central Register of Controlled Trials (CENTRAL), and EMBASE from inception to 30th June 2020.

RESULTS

Forty-one out of 6983 papers were included in the current review. Selected studies are heterogeneous in terms of patient characteristics as well as type, duration and frequency of rehabilitative approach. Neuromotor rehabilitation promotes neuroplasticity, favoring functional recovery of the ipsilesional hemisphere and activation of anatomically and functionally related brain areas in both hemispheres, to compensate for damaged tissue.

CONCLUSIONS

The evidence derived from the analyzed studies supports the positive impact of rehabilitation on brain reorganization, despite the high data heterogeneity. Advanced MRI techniques provide reliable markers of structural and functional connectivity that may potentially aid in helping to implement the most appropriate rehabilitation intervention.

Resting-state Functional Connectivity After Occipital Stroke

BACKGROUND

Resting-state functional magnetic resonance imaging (rsfMRI) reflects spontaneous activation of cortical networks. After stroke, these networks reorganize, both due to structural lesion and reorganization of functional connectivity (FC).

OBJECTIVE

We studied FC in chronic phase occipital stroke patients with homonymous visual field defects before and after repetitive transorbital alternating current stimulation (rtACS).

METHODS

This spin-off study, embedded in the randomized, sham-controlled REVIS trial, comprised 16 chronic occipital stroke patients with visual field defect and 12 healthy control subjects. The patients underwent rsfMRI at baseline, after two weeks of rtACS or sham treatment, and after two months of treatment-free follow-up, whereas the control subjects were measured once. We used a multivariate regression connectivity model to determine mutual prediction accuracy between 74 cortical regions of interest. Additionally, the model parameters were included into a graph to analyze average path length, centrality eigenvector, centrality degree, and clustering of the network. The patients and controls at baseline and the two treatment groups were compared with multilevel modeling.

RESULTS

Before treatment, the patients and controls had similar whole-network prediction accuracy and network parameters, whereas centrality eigenvector differed in perilesional regions, indicating local modification in connectivity. In line with behavioral results, neither prediction accuracy nor any network parameter changed systematically as a result of rtACS rehabilitation compared to sham.

CONCLUSIONS

Whole-network FC showed no difference between occipital stroke patients and healthy population, congruent with the peripheral location of the visual network in relation to the high-density cortical core. rtACS treatment in the given setting did not affect FC.

Effects of virtual reality intervention on neural plasticity in stroke rehabilitation: a systematic review

OBJECTIVE

To systematically review and examine the current literature regarding the effects of Virtual Reality (VR)-based rehabilitation on neural plasticity changes in stroke survivors.

DATA SOURCES

Six bioscience and engineering databases were searched, including Medline via Ebsco, Embase, PsycINFO, IEEE Explore, Cumulative Index of Nursing and Allied Health, and Scopus.

STUDY SELECTION

Studies reporting on the pre-post assessment of a VR intervention with neural plasticity measures published between 2000-2021 were included.

DATA EXTRACTION

Two independent reviewers conducted study selection, data extraction and quality assessment. Methodological quality of controlled trials was assessed using the Physiotherapy Evidence Database scale. Risk of bias of pre-post intervention and case studies was evaluated using the National Institutes of Health Quality Assessment Tool.

DATA SYNTHESIS

Twenty-seven studies (Total n=232) were included. Seven randomized controlled trials were rated as good quality while the two clinical controlled trials were moderate. Based on the risk of bias assessment, one pre-post study and one case study were graded as good quality, one pre-post study and one case study were poor, the other 14 studies were all at fair. After the VR intervention, main neurophysiological findings across studies include: (1) improved interhemispheric balance, (2) enhanced cortical connectivity, (3) increased cortical mapping of the affected limb muscles, (4) the improved neural plasticity measures were correlated to the enhanced behavior outcomes, (5) increased activation of regions in frontal cortex and (6) the mirror neuron system may be involved.

CONCLUSIONS

Virtual reality induced changes in neural plasticity for stroke survivors. Positive correlations between the neural plasticity changes and functional recovery elucidates the mechanisms of VR's therapeutic effects in stroke rehabilitation. This review prompts systematic understanding of the neurophysiological mechanisms of VR-based stroke rehabilitation and summarizes the emerging evidence for ongoing innovation of VR systems and application in stroke rehabilitation.

Electroencephalography resting-state networks in people with Stroke

INTRODUCTION

The purpose of this study was to characterize resting-state cortical networks in chronic stroke survivors using electroencephalography (EEG).

METHODS

Electroencephalography data were collected from 14 chronic stroke and 11 neurologically intact participants while they were in a relaxed, resting state. EEG power was normalized to reduce bias and used as an indicator of network activity. Correlations of orthogonalized EEG activity were used as a measure of functional connectivity between cortical regions.

RESULTS

We found reduced cortical activity and connectivity in the alpha (p < .05; p = .05) and beta (p < .05; p = .03) bands after stroke while connectivity in the gamma (p = .031) band increased. Asymmetries, driven by a reduction in the lesioned hemisphere, were also noted in cortical activity (p = .001) after stroke.

CONCLUSION

These findings suggest that stroke lesions cause a network alteration to more local (higher frequency), asymmetric networks. Understanding changes in cortical networks after stroke could be combined with controllability models to identify (and target) alternate brain network states that reduce functional impairment.

Functional relevance of resistance training-induced neuroplasticity in health and disease

Repetitive, monotonic, and effortful voluntary muscle contractions performed for just a few weeks, i.e., resistance training, can substantially increase maximal voluntary force in the practiced task and can also increase gross motor performance. The increase in motor performance is often accompanied by neuroplastic adaptations in the central nervous system. While historical data assigned functional relevance to such adaptations induced by resistance training, this claim has not yet been systematically and critically examined in the context of motor performance across the lifespan in health and disease. A review of muscle activation, brain and peripheral nerve stimulation, and imaging data revealed that increases in motor performance and neuroplasticity tend to be uncoupled, making a mechanistic link between neuroplasticity and motor performance inconclusive. We recommend new approaches, including causal mediation analytical and hypothesis-driven models to substantiate the functional relevance of resistance training-induced neuroplasticity in the improvements of gross motor function across the lifespan in health and disease.

Predicting Motor Imagery Performance From Resting-State EEG Using Dynamic Causal Modeling

Motor imagery-based brain–computer interfaces (MI-BCIs) send commands to a computer using the brain activity registered when a subject imagines—but does not perform—a given movement. However, inconsistent MI-BCI performance occurs in variations of brain signals across subjects and experiments; this is considered to be a significant problem in practical BCI. Moreover, some subjects exhibit a phenomenon referred to as “BCI-inefficiency,” in which they are unable to generate brain signals for BCI control. These subjects have significant difficulties in using BCI. The primary goal of this study is to identify the connections of the resting-state network that affect MI performance and predict MI performance using these connections. We used a public database of MI, which includes the results of psychological questionnaires and pre-experimental resting-state taken over two sessions on different days. A dynamic causal model was used to calculate the coupling strengths between brain regions with directionality. Specifically, we investigated the motor network in resting-state, including the dorsolateral prefrontal cortex, which performs motor planning. As a result, we observed a significant difference in the connectivity strength from the supplementary motor area to the right dorsolateral prefrontal cortex between the low- and high-MI performance groups. This coupling, measured in the resting-state, is significantly stronger in the high-MI performance group than the low-MI performance group. The connection strength is positively correlated with MI-BCI performance (Session 1: r = 0.54; Session 2: r = 0.42). We also predicted MI performance using linear regression based on this connection (r-squared = 0.31). The proposed predictors, based on dynamic causal modeling, can develop new strategies for improving BCI performance. These findings can further our understanding of BCI-inefficiency and help BCI users to lower costs and save time.

Influence of Motor Deficiency and Spatial Neglect on the Contralesional Posterior Parietal Cortex Functional and Structural Connectivity in Stroke Patients

The posterior parietal cortex (PPC) is a key structure for visual attention and upper limb function, two features that could be impaired after stroke, and could be implied in their recovery. If it is well established that stroke is responsible for intra- and interhemispheric connectivity troubles, little is known about those existing for the contralesional PPC. In this study, we aimed at mapping the functional (using resting state fMRI) and structural (using diffusion tensor imagery) networks from 3 subparts of the PPC of the contralesional hemisphere (the anterior intraparietal sulcus), the posterior intraparietal sulcus and the superior parieto-occipital cortex to bilateral frontal areas and ipsilesional homologous PPC parts in 11 chronic stroke patients compared to 13 healthy controls. We also aimed at assessing the relationship between connectivity and the severity of visuospatial and motor deficiencies. We showed that interhemispheric functional and structural connectivity between PPCs was altered in stroke patients compared to controls, without any specificity among seeds. Alterations of parieto-frontal intra- and interhemispheric connectivity were less observed. Neglect severity was associated with several alterations in intra- and interhemispheric connectivity, whereas we did not find any behavioral/connectivity correlations for motor deficiency. The results of this exploratory study shed a new light on the influence of the contralesional PPC in post-stroke patients, they have to be confirmed and refined in further larger studies.

Imaging Functional Recovery Following Ischemic Stroke: Clinical and Preclinical fMRI Studies

Disability and effectiveness of physical therapy are highly variable following ischemic stroke due to different brain regions being affected. Functional magnetic resonance imaging (fMRI) studies of patients in the months and years following stroke have given some insight into how the brain recovers lost functions. Initially, new pathways are recruited to compensate for the lost region, showing as a brighter blood oxygen‐level‐dependent (BOLD) signal over a larger area during a task than in healthy controls. Subsequently, activity is reduced to baseline levels as pathways become more efficient, mimicking the process of learning typically seen during development. Preclinical models of ischemic stroke aim to enhance understanding of the biology underlying recovery following stroke. However, the pattern of recruitment and focusing seen in humans has not been observed in preclinical fMRI studies that are highly variable methodologically. Resting‐state fMRI studies show more consistency; however, there are still confounding factors to address. Anesthesia and method of stroke induction are the two main sources of variability in preclinical studies; improvements here can reduce variability and increase the intensity and reproducibility of the BOLD response detected by fMRI. Differences in task or stimulus and differences in analysis method also present a source of variability. This review compares clinical and preclinical fMRI studies of recovery following stroke and focuses on how refinement of preclinical models and MRI methods may obtain more representative fMRI data in relation to human studies.

Preferential degradation of cognitive networks differentiates Alzheimer's disease from ageing

Converging evidence from structural, metabolic and functional connectivity MRI suggests that neurodegenerative diseases, such as Alzheimer's disease, target specific neural networks. However, age-related network changes commonly co-occur with neuropathological cascades, limiting efforts to disentangle disease-specific alterations in network function from those associated with normal ageing. Here we elucidate the differential effects of ageing and Alzheimer's disease pathology through simultaneous analyses of two functional connectivity MRI datasets: (i) young participants harbouring highly-penetrant mutations leading to autosomal-dominant Alzheimer's disease from the Dominantly Inherited Alzheimer's Network (DIAN), an Alzheimer's disease cohort in which age-related comorbidities are minimal and likelihood of progression along an Alzheimer's disease trajectory is extremely high; and (ii) young and elderly participants from the Harvard Aging Brain Study, a cohort in which imaging biomarkers of amyloid burden and neurodegeneration can be used to disambiguate ageing alone from preclinical Alzheimer's disease. Consonant with prior reports, we observed the preferential degradation of cognitive (especially the default and dorsal attention networks) over motor and sensory networks in early autosomal-dominant Alzheimer's disease, and found that this distinctive degradation pattern was magnified in more advanced stages of disease. Importantly, a nascent form of the pattern observed across the autosomal-dominant Alzheimer's disease spectrum was also detectable in clinically normal elderly with clear biomarker evidence of Alzheimer's disease pathology (preclinical Alzheimer's disease). At the more granular level of individual connections between node pairs, we observed that connections within cognitive networks were preferentially targeted in Alzheimer's disease (with between network connections relatively spared), and that connections between positively coupled nodes (correlations) were preferentially degraded as compared to connections between negatively coupled nodes (anti-correlations). In contrast, ageing in the absence of Alzheimer's disease biomarkers was characterized by a far less network-specific degradation across cognitive and sensory networks, of between- and within-network connections, and of connections between positively and negatively coupled nodes. We go on to demonstrate that formalizing the differential patterns of network degradation in ageing and Alzheimer's disease may have the practical benefit of yielding connectivity measurements that highlight early Alzheimer's disease-related connectivity changes over those due to age-related processes. Together, the contrasting patterns of connectivity in Alzheimer's disease and ageing add to prior work arguing against Alzheimer's disease as a form of accelerated ageing, and suggest multi-network composite functional connectivity MRI metrics may be useful in the detection of early Alzheimer's disease-specific alterations co-occurring with age-related connectivity changes. More broadly, our findings are consistent with a specific pattern of network degradation associated with the spreading of Alzheimer's disease pathology within targeted neural networks.

Modafinil treatment modulates functional connectivity in stroke survivors with severe fatigue

Post-stroke fatigue has a significant impact on stroke survivors’ mental and physical well-being. Our recent clinical trial showed significant reduction of post-stroke fatigue with modafinil treatment, however functional connectivity changes in response to modafinil have not yet been explored in stroke survivors with post-stroke fatigue. Twenty-eight participants (multidimensional fatigue inventory-20 ≥ 60) had MRI scans at baseline, and during modafinil and placebo treatment. Resting-state functional MRI data were obtained, and independent component analysis was used to extract functional networks. Resting-state functional connectivity (rsFC) was examined between baseline, modafinil and placebo treatment using permutation testing with threshold-free cluster enhancement. Overall twenty-eight participants (mean age: 62 ± 14.3, mean baseline MFI-20: 72.3 ± 9.24) were included. During modafinil treatment, increased rsFC was observed in the right hippocampus (p = 0.004, 11 voxels) compared to placebo. This coincided with lower rsFC in the left frontoparietal (inferior parietal lobule, p = 0.023, 13 voxels), somatosensory (primary somatosensory cortex; p = 0.009, 32 voxels) and mesolimbic network (temporal pole, p = 0.016, 35 voxels). In conclusion, modafinil treatment induces significant changes in rsFC in post-stroke fatigue. This modulation of rsFC may relate to a reduction of post-stroke fatigue; however, the relationship between sensory processing, neurotransmitter expression and fatigue requires further exploration.

ICA-based denoising for ASL perfusion imaging

Arterial Spin Labelling (ASL) imaging derives a perfusion image by tracing the accumulation of magnetically labeled blood water in the brain. As the image generated has an intrinsically low signal to noise ratio (SNR), multiple measurements are routinely acquired and averaged, at a penalty of increased scan duration and opportunity for motion artefact. However, this strategy alone might be ineffective in clinical settings where the time available for acquisition is limited and patient motion are increased. This study investigates the use of an Independent Component Analysis (ICA) approach for denoising ASL data, and its potential for automation.

72 ASL datasets (pseudo-continuous ASL; 5 different post-labeling delays: 400, 800, 1200, 1600, 2000 m s; total volumes = 60) were collected from thirty consecutive acute stroke patients. The effects of ICA-based denoising (manual and automated) where compared to two different denoising approaches, aCompCor, a Principal Component-based method, and Enhancement of Automated Blood Flow Estimates (ENABLE), an algorithm based on the removal of corrupted volumes. Multiple metrics were used to assess the changes in the quality of the data following denoising, including changes in cerebral blood flow (CBF) and arterial transit time (ATT), SNR, and repeatability. Additionally, the relationship between SNR and number of repetitions acquired was estimated before and after denoising the data.

The use of an ICA-based denoising approach resulted in significantly higher mean CBF and ATT values (p < 0.001), lower CBF and ATT variance (p < 0.001), increased SNR (p < 0.001), and improved repeatability (p < 0.05) when compared to the raw data. The performance of manual and automated ICA-based denoising was comparable. These results went beyond the effects of aCompCor or ENABLE. Following ICA-based denoising, the SNR was higher using only 50% of the ASL-dataset collected than when using the whole raw data.

The results show that ICA can be used to separate signal from noise in ASL data, improving the quality of the data collected. In fact, this study suggests that the acquisition time could be reduced by 50% without penalty to data quality, something that merits further study. Independent component classification and regression can be carried out either manually, following simple criteria, or automatically.

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ICA can be used to separate signal from noise in ASL data, improving data quality.

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Automated denoising reproduces the improvement seen by a manual approach.

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ICA based denoising is superior to PCA or volume censoring approaches.

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ASL acquisition time could be reduced by 50% without penalty to data quality.

Mind-body interactive qigong improves physical and mental aspects of quality of life in inpatients with stroke: A randomized control study

BACKGROUND

Stroke, a medical condition that causes physical disability and mental health problems, impacts negatively on quality of life. Post-stroke rehabilitation is critical to restoring quality of life in these patients.

OBJECTIVES

This study was designed to evaluate the effect of a mind-body interactive qigong intervention on the physical and mental aspects of quality of life, considering bio-physiological and mental covariates in subacute stroke inpatients.

METHODS

A randomized controlled trial with repeated measures design was used. A total of 68 participants were recruited from the medical and rehabilitation wards at a teaching hospital in northern Taiwan and then randomly assigned either to the Chan-Chuang qigong group, which received standard care plus a 10-day mind-body interactive exercise program, or to the control group, which received standard care only. Data were collected using the National Institutes of Health Stroke Scale, Hospital Anxiety and Depression Scale, Short Form-12, stroke-related neurologic deficit, muscular strength, heart rate variability and fatigue at three time points: pre-intervention, halfway through the intervention (day 5) and on the final day of the intervention (day 10).

RESULTS

The results of the mixed-effect model analysis showed that the qigong group had a significantly higher quality of life score at day 10 (p<0.05) than the control group. Among the covariates, neurologic deficit (p=0.04), muscle strength (p=0.04), low frequency to high frequency ratio (p=0.02) and anxiety (p=0.04) were significantly associated with changes in quality of life. Conversely, heart rate, heart rate variability (standard deviation of normal-to-normal intervals, low frequency and high frequency), fatigue and depression were not significantly associated with change in quality of life (p >0.05).

CONCLUSIONS

This study supports the potential benefits of a 10-day mind-body interactive exercise (Chan-Chuang qigong) program for subacute stroke inpatients and provides information that may be useful in planning adjunctive rehabilitative care for stroke inpatients.

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.

Cerebral Motor Functional Connectivity at the Acute Stage: An Outcome Predictor of Ischemic Stroke

Sixty-seven patients with first acute ischemic stroke onset between 3 to 7 days and 25 age- and sex- matched controls were analyzed for the performance of a resting-state functional MRI to investigate whether the functional connectivity (FC) of the motor network in acute ischemic stroke is independently associated with functional outcomes. The FC of cortical motor network and default mode network was analyzed. The FC was compared between controls, patients with favorable outcomes (modified Rankin Scale, mRS ≤1), and patients with unfavorable outcomes (mRS ≥2) at 3 months. Of the 67 patients, 23 (34%) exhibited unfavorable outcomes. In multivariate analysis, the FC between ipsilesional primary motor cortex (M1) and contralesional dorsal premotor area (PMd) ≤0.63, were independently associated with unfavorable outcomes (odds ratio = 6.32, P = 0.032), whereas the FC of default mode network was not different between groups. The interhemispheric FC of the motor network is an independent predictor of functional outcomes in patients with acute ischemic stroke.

Functional network connectivity is altered in patients with upper limb somatosensory impairments in the acute phase post stroke: A cross-sectional study

Background

Aberrant functional connectivity in brain networks associated with motor impairment after stroke is well described, but little is known about the association with somatosensory impairments.

Aim

The objective of this cross-sectional observational study was to investigate the relationship between brain functional connectivity and severity of somatosensory impairments in the upper limb in the acute phase post stroke.

Methods

Nineteen first-ever stroke patients underwent resting-state functional magnetic resonance imaging (rs-fMRI) and a standardized clinical somatosensory profile assessment (exteroception and higher cortical somatosensation) in the first week post stroke. Integrity of inter- and intrahemispheric (ipsilesional and contralesional) functional connectivity of the somatosensory network was assessed between patients with severe (Em-NSA< 13/32) and mild to moderate (Em-NSA> 13/32) somatosensory impairments.

Results

Patients with severe somatosensory impairments displayed significantly lower functional connectivity indices in terms of interhemispheric (p = 0.001) and ipsilesional intrahemispheric (p = 0.035) connectivity compared to mildly to moderately impaired patients. Significant associations were found between the perceptual threshold of touch assessment and interhemispheric (r = -0.63) and ipsilesional (r = -0.51) network indices. Additional significant associations were found between the index of interhemispheric connectivity and light touch (r = 0.55) and stereognosis (r = 0.64) evaluation.

Conclusion

Patients with more severe somatosensory impairments have lower inter- and ipsilesional intrahemispheric connectivity of the somatosensory network. Lower connectivity indices are related to more impaired exteroception and higher cortical somatosensation. This study highlights the importance of network integrity in terms of inter- and ipsilesional intrahemispheric connectivity for somatosensory function. Further research is needed investigating the effect of therapy on the re-establishment of these networks.

Shaping neuroplasticity by using powered exoskeletons in patients with stroke: a randomized clinical trial

BACKGROUND

The use of neurorobotic devices may improve gait recovery by entraining specific brain plasticity mechanisms, which may be a key issue for successful rehabilitation using such approach. We assessed whether the wearable exoskeleton, Ekso™, could get higher gait performance than conventional overground gait training (OGT) in patients with hemiparesis due to stroke in a chronic phase, and foster the recovery of specific brain plasticity mechanisms.

METHODS

We enrolled forty patients in a prospective, pre-post, randomized clinical study. Twenty patients underwent Ekso™ gait training (EGT) (45-min/session, five times/week), in addition to overground gait therapy, whilst 20 patients practiced an OGT of the same duration. All individuals were evaluated about gait performance (10 m walking test), gait cycle, muscle activation pattern (by recording surface electromyography from lower limb muscles), frontoparietal effective connectivity (FPEC) by using EEG, cortico-spinal excitability (CSE), and sensory-motor integration (SMI) from both primary motor areas by using Transcranial Magnetic Stimulation paradigm before and after the gait training.

RESULTS

A significant effect size was found in the EGT-induced improvement in the 10 m walking test (d = 0.9, p < 0.001), CSE in the affected side (d = 0.7, p = 0.001), SMI in the affected side (d = 0.5, p = 0.03), overall gait quality (d = 0.8, p = 0.001), hip and knee muscle activation (d = 0.8, p = 0.001), and FPEC (d = 0.8, p = 0.001). The strengthening of FPEC (r = 0.601, p < 0.001), the increase of SMI in the affected side (r = 0.554, p < 0.001), and the decrease of SMI in the unaffected side (r = - 0.540, p < 0.001) were the most important factors correlated with the clinical improvement.

CONCLUSIONS

Ekso™ gait training seems promising in gait rehabilitation for post-stroke patients, besides OGT. Our study proposes a putative neurophysiological basis supporting Ekso™ after-effects. This knowledge may be useful to plan highly patient-tailored gait rehabilitation protocols.

TRIAL REGISTRATION

ClinicalTrials.gov , NCT03162263 .

Changes in Resting-State Connectivity following Melody-Based Therapy in a Patient with Aphasia

Melody-based treatments for patients with aphasia rely on the notion of preserved musical abilities in the RH, following left hemisphere damage. However, despite evidence for their effectiveness, the role of the RH is still an open question. We measured changes in resting-state functional connectivity following melody-based intervention, to identify lateralization of treatment-related changes. A patient with aphasia due to left frontal and temporal hemorrhages following traumatic brain injuries (TBI) more than three years earlier received 48 sessions of melody-based intervention. Behavioral measures improved and were maintained at the 8-week posttreatment follow-up. Resting-state fMRI data collected before and after treatment showed an increase in connectivity between motor speech control areas (bilateral supplementary motor areas and insulae) and RH language areas (inferior frontal gyrus pars triangularis and pars opercularis). This change, which was specific for the RH, was greater than changes in a baseline interval measured before treatment. No changes in RH connectivity were found in a matched control TBI patient scanned at the same intervals. These results are compatible with a compensatory role for RH language areas following melody-based intervention. They further suggest that this therapy intervenes at the level of the interface between language areas and speech motor control areas necessary for language production.

Decreased integration and information capacity in stroke measured by whole brain models of resting state activity

While several studies have shown that focal lesions affect the communication between structurally normal regions of the brain, and that these changes may correlate with behavioural deficits, their impact on brain's information processing capacity is currently unknown. Here we test the hypothesis that focal lesions decrease the brain's information processing capacity, of which changes in functional connectivity may be a measurable correlate. To measure processing capacity, we turned to whole brain computational modelling to estimate the integration and segregation of information in brain networks. First, we measured functional connectivity between different brain areas with resting state functional magnetic resonance imaging in healthy subjects (n = 26), and subjects who had suffered a cortical stroke (n = 36). We then used a whole-brain network model that coupled average excitatory activities of local regions via anatomical connectivity. Model parameters were optimized in each healthy or stroke participant to maximize correlation between model and empirical functional connectivity, so that the model's effective connectivity was a veridical representation of healthy or lesioned brain networks. Subsequently, we calculated two model-based measures: 'integration', a graph theoretical measure obtained from functional connectivity, which measures the connectedness of brain networks, and 'information capacity', an information theoretical measure that cannot be obtained empirically, representative of the segregative ability of brain networks to encode distinct stimuli. We found that both measures were decreased in stroke patients, as compared to healthy controls, particularly at the level of resting-state networks. Furthermore, we found that these measures, especially information capacity, correlate with measures of behavioural impairment and the segregation of resting-state networks empirically measured. This study shows that focal lesions affect the brain's ability to represent stimuli and task states, and that information capacity measured through whole brain models is a theory-driven measure of processing capacity that could be used as a biomarker of injury for outcome prediction or target for rehabilitation intervention.

Neuroplastic Changes Following Brain Ischemia and their Contribution to Stroke Recovery: Novel Approaches in Neurorehabilitation

Ischemic damage to the brain triggers substantial reorganization of spared areas and pathways, which is associated with limited, spontaneous restoration of function. A better understanding of this plastic remodeling is crucial to develop more effective strategies for stroke rehabilitation. In this review article, we discuss advances in the comprehension of post-stroke network reorganization in patients and animal models. We first focus on rodent studies that have shed light on the mechanisms underlying neuronal remodeling in the perilesional area and contralesional hemisphere after motor cortex infarcts. Analysis of electrophysiological data has demonstrated brain-wide alterations in functional connectivity in both hemispheres, well beyond the infarcted area. We then illustrate the potential use of non-invasive brain stimulation (NIBS) techniques to boost recovery. We finally discuss rehabilitative protocols based on robotic devices as a tool to promote endogenous plasticity and functional restoration.

Recovery of functional connectivity of the sensorimotor network after surgery for diffuse low-grade gliomas involving the supplementary motor area

OBJECTIVE The supplementary motor area (SMA) syndrome is a well-studied lesional model of brain plasticity involving the sensorimotor network. Patients with diffuse low-grade gliomas in the SMA may exhibit this syndrome after resective surgery. They experience a temporary loss of motor function, which completely resolves within 3 months. The authors used functional MRI (fMRI) resting state analysis of the sensorimotor network to investigate large-scale brain plasticity between the immediate postoperative period and 3 months' follow-up. METHODS Resting state fMRI was performed preoperatively, during the immediate postoperative period, and 3 months postoperatively in 6 patients with diffuse low-grade gliomas who underwent partial surgical excision of the SMA. Correlation analysis within the sensorimotor network was carried out on those 3 time points to study modifications of its functional connectivity. RESULTS The results showed a large-scale reorganization of the sensorimotor network. Interhemispheric connectivity was decreased in the postoperative period, and increased again during the recovery process. Connectivity between the lesion side motor area and the contralateral SMA rose to higher values than in the preoperative period. Intrahemispheric connectivity was decreased during the immediate postoperative period and had returned to preoperative values at 3 months after surgery. CONCLUSIONS These results confirm the findings reported in the existing literature on the plasticity of the SMA, showing large-scale modifications of the sensorimotor network, at both inter- and intrahemispheric levels. They suggest that interhemispheric connectivity might be a correlate of SMA syndrome recovery.

Laser acupuncture as an adjunctive therapy for spastic cerebral palsy in children

Laser acupuncture is widely used as an alternative line of treatment in several chronic pediatric diseases. To investigate whether biostimulation by low-level laser on acupuncture points adds a clinical benefit to conventional physiotherapy in hemiplegic spastic cerebral palsy (CP) children. Forty spastic hemiplegic cerebral palsy children by age 1-4 years were chosen from the pediatric outpatient clinic of the National Institute of Laser Enhanced Sciences (NILES), Cairo University, and Menofyia University hospitals. They were randomly divided into control and study groups; 20 children each. Both groups received physiotherapy for 3 months, while only the study group also received laser acupuncture (low-level laser 650 nm with 50 mW power was applied at each acupoint for 30 s giving an energy density of 1.8 J/cm(2)). Preassessment and postassessment of muscle tone, the range of motion (ROM), and gross motor function measurements (GMFMs) were obtained, and the results were statistically analyzed. Comparison between posttreatment measures for the control vs. study groups showed significant difference in muscle tone (wrist flexors and plantar flexors) in favor of the study group, while range of motion showed no significant differences. GMFM showed no significant difference in total score while there was a significant difference in goal total score (sum of % scores for each dimension identified as goal area divided by number of goal areas) in favor of the study group. Laser acupuncture has a beneficial effect on reducing spasticity in spastic cerebral palsy and may be helpful in improving their movement.

Effect of a Task-Oriented Rehabilitation Program on Upper Extremity Recovery Following Motor Stroke: The ICARE Randomized Clinical Trial

IMPORTANCE

Clinical trials suggest that higher doses of task-oriented training are superior to current clinical practice for patients with stroke with upper extremity motor deficits.

OBJECTIVE

To compare the efficacy of a structured, task-oriented motor training program vs usual and customary occupational therapy (UCC) during stroke rehabilitation.

DESIGN, SETTING, AND PARTICIPANTS

Phase 3, pragmatic, single-blind randomized trial among 361 participants with moderate motor impairment recruited from 7 US hospitals over 44 months, treated in the outpatient setting from June 2009 to March 2014.

INTERVENTIONS

Structured, task-oriented upper extremity training (Accelerated Skill Acquisition Program [ASAP]; n = 119); dose-equivalent occupational therapy (DEUCC; n = 120); or monitoring-only occupational therapy (UCC; n = 122). The DEUCC group was prescribed 30 one-hour sessions over 10 weeks; the UCC group was only monitored, without specification of dose.

MAIN OUTCOMES AND MEASURES

The primary outcome was 12-month change in log-transformed Wolf Motor Function Test time score (WMFT, consisting of a mean of 15 timed arm movements and hand dexterity tasks). Secondary outcomes were change in WMFT time score (minimal clinically important difference [MCID] = 19 seconds) and proportion of patients improving ≥25 points on the Stroke Impact Scale (SIS) hand function score (MCID = 17.8 points).

RESULTS

Among the 361 randomized patients (mean age, 60.7 years; 56% men; 42% African American; mean time since stroke onset, 46 days), 304 (84%) completed the 12-month primary outcome assessment; in intention-to-treat analysis, mean group change scores (log WMFT, baseline to 12 months) were, for the ASAP group, 2.2 to 1.4 (difference, 0.82); DEUCC group, 2.0 to 1.2 (difference, 0.84); and UCC group, 2.1 to 1.4 (difference, 0.75), with no significant between-group differences (ASAP vs DEUCC: 0.14; 95% CI, -0.05 to 0.33; P = .16; ASAP vs UCC: -0.01; 95% CI, -0.22 to 0.21; P = .94; and DEUCC vs UCC: -0.14; 95% CI, -0.32 to 0.05; P = .15). Secondary outcomes for the ASAP group were WMFT change score, -8.8 seconds, and improved SIS, 73%; DEUCC group, WMFT, -8.1 seconds, and SIS, 72%; and UCC group, WMFT, -7.2 seconds, and SIS, 69%, with no significant pairwise between-group differences (ASAP vs DEUCC: WMFT, 1.8 seconds; 95% CI, -0.8 to 4.5 seconds; P = .18; improved SIS, 1%; 95% CI, -12% to 13%; P = .54; ASAP vs UCC: WMFT, -0.6 seconds, 95% CI, -3.8 to 2.6 seconds; P = .72; improved SIS, 4%; 95% CI, -9% to 16%; P = .48; and DEUCC vs UCC: WMFT, -2.1 seconds; 95% CI, -4.5 to 0.3 seconds; P = .08; improved SIS, 3%; 95% CI, -9% to 15%; P = .22). A total of 168 serious adverse events occurred in 109 participants, resulting in 8 patients withdrawing from the study.

CONCLUSIONS AND RELEVANCE

Among patients with motor stroke and primarily moderate upper extremity impairment, use of a structured, task-oriented rehabilitation program did not significantly improve motor function or recovery beyond either an equivalent or a lower dose of UCC upper extremity rehabilitation. These findings do not support superiority of this program among patients with motor stroke and primarily moderate upper extremity impairment.

TRIAL REGISTRATION

clinicaltrials.gov Identifier: NCT00871715.

Neuroplastic Sensorimotor Resting State Network Reorganization in Children With Hemiplegic Cerebral Palsy Treated With Constraint-Induced Movement Therapy

Using resting state functional magnetic resonance imaging (MRI), we aim to understand the neurologic basis of improved function in children with hemiplegic cerebral palsy treated with constraint-induced movement therapy. Eleven children including 4 untreated comparison subjects diagnosed with hemiplegic cerebral palsy were recruited from 3 clinical centers. MRI and clinical data were gathered at baseline and 1 month for both groups, and 6 months later for the case group only. After constraint therapy, the sensorimotor resting state network became more bilateral, with balanced contributions from each hemisphere, which was sustained 6 months later. Sensorimotor resting state network reorganization after therapy was correlated with a change in the Quality of Upper Extremity Skills Test score at 1 month (r = 0.79, P = .06), and Canadian Occupational Performance Measure scores at 6 months (r = 0.82, P = .05). This clinically correlated resting state network reorganization provides further evidence of the neuroplastic mechanisms underlying constraint-induced movement therapy.

Post-Stroke Longitudinal Alterations of Inter-Hemispheric Correlation and Hemispheric Dominance in Mouse Pre-Motor Cortex

Purpose

Limited restoration of function is known to occur spontaneously after an ischemic injury to the primary motor cortex. Evidence suggests that Pre-Motor Areas (PMAs) may “take over” control of the disrupted functions. However, little is known about functional reorganizations in PMAs. Forelimb movements in mice can be driven by two cortical regions, Caudal and Rostral Forelimb Areas (CFA and RFA), generally accepted as primary motor and pre-motor cortex, respectively. Here, we examined longitudinal changes in functional coupling between the two RFAs following unilateral photothrombotic stroke in CFA (mm from Bregma: +0.5 anterior, +1.25 lateral).

Methods

Local field potentials (LFPs) were recorded from the RFAs of both hemispheres in freely moving injured and naïve mice. Neural signals were acquired at 9, 16 and 23 days after surgery (sub-acute period in stroke animals) through one bipolar electrode per hemisphere placed in the center of RFA, with a ground screw over the occipital bone. LFPs were pre-processed through an efficient method of artifact removal and analysed through: spectral,cross-correlation, mutual information and Granger causality analysis.

Results

Spectral analysis demonstrated an early decrease (day 9) in the alpha band power in both the RFAs. In the late sub-acute period (days 16 and 23), inter-hemispheric functional coupling was reduced in ischemic animals, as shown by a decrease in the cross-correlation and mutual information measures. Within the gamma and delta bands, correlation measures were already reduced at day 9. Granger analysis, used as a measure of the symmetry of the inter-hemispheric causal connectivity, showed a less balanced activity in the two RFAs after stroke, with more frequent oscillations of hemispheric dominance.

Conclusions

These results indicate robust electrophysiological changes in PMAs after stroke. Specifically, we found alterations in transcallosal connectivity, with reduced inter-hemispheric functional coupling and a fluctuating dominance pattern. These reorganizations may underlie vicariation of lost functions following stroke.

Wavelet-based clustering of resting state MRI data in the rat

While functional connectivity has typically been calculated over the entire length of the scan (5-10min), interest has been growing in dynamic analysis methods that can detect changes in connectivity on the order of cognitive processes (seconds). Previous work with sliding window correlation has shown that changes in functional connectivity can be observed on these time scales in the awake human and in anesthetized animals. This exciting advance creates a need for improved approaches to characterize dynamic functional networks in the brain. Previous studies were performed using sliding window analysis on regions of interest defined based on anatomy or obtained from traditional steady-state analysis methods. The parcellation of the brain may therefore be suboptimal, and the characteristics of the time-varying connectivity between regions are dependent upon the length of the sliding window chosen. This manuscript describes an algorithm based on wavelet decomposition that allows data-driven clustering of voxels into functional regions based on temporal and spectral properties. Previous work has shown that different networks have characteristic frequency fingerprints, and the use of wavelets ensures that both the frequency and the timing of the BOLD fluctuations are considered during the clustering process. The method was applied to resting state data acquired from anesthetized rats, and the resulting clusters agreed well with known anatomical areas. Clusters were highly reproducible across subjects. Wavelet cross-correlation values between clusters from a single scan were significantly higher than the values from randomly matched clusters that shared no temporal information, indicating that wavelet-based analysis is sensitive to the relationship between areas.

Neuroplastic changes in resting-state functional connectivity after stroke rehabilitation

Most neuroimaging research in stroke rehabilitation mainly focuses on the neural mechanisms underlying the natural history of post-stroke recovery. However, connectivity mapping from resting-state fMRI is well suited for different neurological conditions and provides a promising method to explore plastic changes for treatment-induced recovery from stroke. We examined the changes in resting-state functional connectivity (RS-FC) of the ipsilesional primary motor cortex (M1) in 10 post-acute stroke patients before and immediately after 4 weeks of robot-assisted bilateral arm therapy (RBAT). Motor performance, functional use of the affected arm, and daily function improved in all participants. Reduced interhemispheric RS-FC between the ipsilesional and contralesional M1 (M1-M1) and the contralesional-lateralized connections were noted before treatment. In contrast, greater M1-M1 functional connectivity and disturbed resting-state networks were observed after RBAT relative to pre-treatment. Increased changes in M1-M1 RS-FC after RBAT were coupled with better motor and functional improvements. Mediation analysis showed the pre-to-post difference in M1-M1 RS-FC was a significant mediator for the relationship between motor and functional recovery. These results show neuroplastic changes and functional recoveries induced by RBAT in post-acute stroke survivors and suggest that interhemispheric functional connectivity in the motor cortex may be a neurobiological marker for recovery after stroke rehabilitation.

Brain effective connectivity during motor-imagery and execution following stroke and rehabilitation

Brain areas within the motor system interact directly or indirectly during motor-imagery and motor-execution tasks. These interactions and their functionality can change following stroke and recovery. How brain network interactions reorganize and recover their functionality during recovery and treatment following stroke are not well understood. To contribute to answering these questions, we recorded blood oxygenation-level dependent (BOLD) functional magnetic resonance imaging (fMRI) signals from 10 stroke survivors and evaluated dynamical causal modeling (DCM)-based effective connectivity among three motor areas: primary motor cortex (M1), pre-motor cortex (PMC) and supplementary motor area (SMA), during motor-imagery and motor-execution tasks. We compared the connectivity between affected and unaffected hemispheres before and after mental practice and combined mental practice and physical therapy as treatments. The treatment (intervention) period varied in length between 14 to 51 days but all patients received the same dose of 60 h of treatment. Using Bayesian model selection (BMS) approach in the DCM approach, we found that, after intervention, the same network dominated during motor-imagery and motor-execution tasks but modulatory parameters suggested a suppressive influence of SM A on M1 during the motor-imagery task whereas the influence of SM A on M1 was unrestricted during the motor-execution task. We found that the intervention caused a reorganization of the network during both tasks for unaffected as well as for the affected hemisphere. Using Bayesian model averaging (BMA) approach, we found that the intervention improved the regional connectivity among the motor areas during both the tasks. The connectivity between PMC and M1 was stronger in motor-imagery tasks whereas the connectivity from PMC to M1, SM A to M1 dominated in motor-execution tasks. There was significant behavioral improvement (p = 0.001) in sensation and motor movements because of the intervention as reflected by behavioral Fugl-Meyer (FMA) measures, which were significantly correlated (p = 0.05) with a subset of connectivity. These findings suggest that PMC and M1 play a crucial role during motor-imagery as well as during motor-execution task. In addition, M1 causes more exchange of causal information among motor areas during a motor-execution task than during a motor-imagery task due to its interaction with SM A. This study expands our understanding of motor network involved during two different tasks, which are commonly used during rehabilitation following stroke. A clear understanding of the effective connectivity networks leads to a better treatment in helping stroke survivors regain motor ability.

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Brain motor effective connectivity can change due to stroke and during recovery.

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Rehabilitative treatments caused significant changes in motor and sensation scores.

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Behavioral improvements were accompanied by specific changes in brain connectivity.

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SMA exerted a suppressive driving to M1 during motor imagery.

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SMA-to-M1connectivity was positively modulated during actual motor execution.

Connectivity measures are robust biomarkers of cortical function and plasticity after stroke

Valid biomarkers of motor system function after stroke could improve clinical decision-making. Electroencephalography-based measures are safe, inexpensive, and accessible in complex medical settings and so are attractive candidates. This study examined specific electroencephalography cortical connectivity measures as biomarkers by assessing their relationship with motor deficits across 28 days of intensive therapy. Resting-state connectivity measures were acquired four times using dense array (256 leads) electroencephalography in 12 hemiparetic patients (7.3 ± 4.0 months post-stroke, age 26-75 years, six male/six female) across 28 days of intensive therapy targeting arm motor deficits. Structural magnetic resonance imaging measured corticospinal tract injury and infarct volume. At baseline, connectivity with leads overlying ipsilesional primary motor cortex (M1) was a robust and specific marker of motor status, accounting for 78% of variance in impairment; ipsilesional M1 connectivity with leads overlying ipsilesional frontal-premotor (PM) regions accounted for most of this (R(2) = 0.51) and remained significant after controlling for injury. Baseline impairment also correlated with corticospinal tract injury (R(2) = 0.52), though not infarct volume. A model that combined a functional measure of connectivity with a structural measure of injury (corticospinal tract injury) performed better than either measure alone (R(2) = 0.93). Across the 28 days of therapy, change in connectivity with ipsilesional M1 was a good biomarker of motor gains (R(2) = 0.61). Ipsilesional M1-PM connectivity increased in parallel with motor gains, with greater gains associated with larger increases in ipsilesional M1-PM connectivity (R(2) = 0.34); greater gains were also associated with larger decreases in M1-parietal connectivity (R(2) = 0.36). In sum, electroencephalography measures of motor cortical connectivity-particularly between ipsilesional M1 and ipsilesional premotor-are strongly related to motor deficits and their improvement with therapy after stroke and so may be useful biomarkers of cortical function and plasticity. Such measures might provide a biological approach to distinguishing patient subgroups after stroke.

Functional organization and restoration of the brain motor-execution network after stroke and rehabilitation

Multiple cortical areas of the human brain motor system interact coherently in the low frequency range (<0.1 Hz), even in the absence of explicit tasks. Following stroke, cortical interactions are functionally disturbed. How these interactions are affected and how the functional organization is regained from rehabilitative treatments as people begin to recover motor behaviors has not been systematically studied. We recorded the intrinsic functional magnetic resonance imaging (fMRI) signals from 30 participants: 17 young healthy controls and 13 aged stroke survivors. Stroke participants underwent mental practice (MP) or both mental practice and physical therapy (MP+PT) within 14-51 days following stroke. We investigated the network activity of five core areas in the motor-execution network, consisting of the left primary motor area (LM1), the right primary motor area (RM1), the left pre-motor cortex (LPMC), the right pre-motor cortex (RPMC) and the supplementary motor area (SMA). We discovered that (i) the network activity dominated in the frequency range 0.06-0.08 Hz for all the regions, and for both able-bodied and stroke participants (ii) the causal information flow between the regions: LM1 and SMA, RPMC and SMA, RPMC and LM1, SMA and RM1, SMA and LPMC, was reduced significantly for stroke survivors (iii) the flow did not increase significantly after MP alone and (iv) the flow among the regions during MP+PT increased significantly. We also found that sensation and motor scores were significantly higher and correlated with directed functional connectivity measures when the stroke-survivors underwent MP+PT but not MP alone. The findings provide evidence that a combination of mental practice and physical therapy can be an effective means of treatment for stroke survivors to recover or regain the strength of motor behaviors, and that the spectra of causal information flow can be used as a reliable biomarker for evaluating rehabilitation in stroke survivors.

Altered resting-state network connectivity in stroke patients with and without apraxia of speech

Motor speech disorders, including apraxia of speech (AOS), account for over 50% of the communication disorders following stroke. Given its prevalence and impact, and the need to understand its neural mechanisms, we used resting state functional MRI to examine functional connectivity within a network of regions previously hypothesized as being associated with AOS (bilateral anterior insula (aINS), inferior frontal gyrus (IFG), and ventral premotor cortex (PM)) in a group of 32 left hemisphere stroke patients and 18 healthy, age-matched controls. Two expert clinicians rated severity of AOS, dysarthria and nonverbal oral apraxia of the patients. Fifteen individuals were categorized as AOS and 17 were AOS-absent. Comparison of connectivity in patients with and without AOS demonstrated that AOS patients had reduced connectivity between bilateral PM, and this reduction correlated with the severity of AOS impairment. In addition, AOS patients had negative connectivity between the left PM and right aINS and this effect decreased with increasing severity of non-verbal oral apraxia. These results highlight left PM involvement in AOS, begin to differentiate its neural mechanisms from those of other motor impairments following stroke, and help inform us of the neural mechanisms driving differences in speech motor planning and programming impairment following stroke.

Connectomics and new approaches for analyzing human brain functional connectivity

Estimating the functional interactions between brain regions and mapping those connections to corresponding inter-individual differences in cognitive, behavioral and psychiatric domains are central pursuits for understanding the human connectome. The number and complexity of functional interactions within the connectome and the large amounts of data required to study them position functional connectivity research as a “big data” problem. Maximizing the degree to which knowledge about human brain function can be extracted from the connectome will require developing a new generation of neuroimaging analysis algorithms and tools. This review describes several outstanding problems in brain functional connectomics with the goal of engaging researchers from a broad spectrum of data sciences to help solve these problems. Additionally it provides information about open science resources consisting of raw and preprocessed data to help interested researchers get started.

Translating the science into practice: shaping rehabilitation practice to enhance recovery after brain damage

The revolution in neuroscience provided strong evidence for learning-dependent neuroplasticity and presaged the role of motor learning as essential for restorative therapies after stroke and other disabling neurological conditions. The scientific basis of motor learning has continued to evolve from a dominance of cognitive or information processing perspectives to a blend with neural science and contemporary social-cognitive-psychological science, which includes the neural and psychological underpinnings of motivation. This transformation and integration across traditionally separate domains is timely now that clinician scientists are developing novel, evidence-based therapies to maximize motor recovery in the place of suboptimal solutions. We will review recent evidence pertaining to therapeutic approaches that spring from an integrated framework of learning-dependent neuroplasticity along with the growing awareness of protocols that directly address the patient's fundamental psychological needs. Of importance, there is mounting evidence that when the individual's needs are considered in the context of instructions or expectations, the learning/rehabilitation process is accelerated.

Stroke and the connectome: how connectivity guides therapeutic intervention

Connections between neurons are affected within 3 min of stroke onset by massive ischemic depolarization and then delayed cell death. Some connections can recover with prompt reperfusion; others associated with the dying infarct do not. Disruption in functional connectivity is due to direct tissue loss and indirect disconnections of remote areas known as diaschisis. Stroke is devastating, yet given the brain's redundant design, collateral surviving networks and their connections are well-positioned to compensate. Our perspective is that new treatments for stroke may involve a rational functional and structural connections-based approach. Surviving, affected, and at-risk networks can be identified and targeted with scenario-specific treatments. Strategies for recovery may include functional inhibition of the intact hemisphere, rerouting of connections, or setpoint-mediated network plasticity. These approaches may be guided by brain imaging and enabled by patient- and injury-specific brain stimulation, rehabilitation, and potential molecule-based strategies to enable new connections.

Infusing motor learning research into neurorehabilitation practice: a historical perspective with case exemplar from the accelerated skill acquisition program

: This special interest article provides a historical framework with a contemporary case example that traces the infusion of the science of motor learning into neurorehabilitation practice. The revolution in neuroscience provided the first evidence for learning-dependent neuroplasticity and presaged the role of motor learning as critical for restorative therapies after stroke. The scientific underpinnings of motor learning have continued to evolve from a dominance of cognitive or information processing perspectives to a blend with neural science and contemporary social-cognitive psychological science. Furthermore, advances in the science of behavior change have contributed insights into influences on sustainable and generalizable gains in motor skills and associated behaviors, including physical activity and other recovery-promoting habits. For neurorehabilitation, these insights have tremendous relevance for the therapist-patient interactions and relationships. We describe a principle-based intervention for neurorehabilitation termed the Accelerated Skill Acquisition Program that we developed. This approach emphasizes integration from a broad set of scientific lines of inquiry including the contemporary fields of motor learning, neuroscience, and the psychological science of behavior change. Three overlapping essential elements-skill acquisition, impairment mitigation, and motivational enhancements-are integrated.

VIDEO ABSTRACT AVAILABLE

(See Video, Supplemental Digital Content 1, http://links.lww.com/JNPT/A71) for more insights from the authors.

Modulation of effective connectivity in the default mode network at rest and during a memory task

It is known that the default mode network (DMN) may be modulated by a cognitive task and by performance level. Changes in the DMN have been examined by investigating resting-state activation levels, but there have been very few studies examining the modulation of effective connectivity of the DMN during a task in healthy older subjects. In this study, the authors examined how effective connectivity changed in the DMN between rest and during a memory task. The authors also investigated whether there was any relationship between effective connectivity modulation in the DMN and memory performance, to establish whether variations in cognitive performance are related to neural network effective connectivity, either at rest or during task performance. Twenty-eight healthy older participants underwent a resting-state functional magnetic resonance imaging scan and an emotional face-name encoding task. Effective connectivity analyses were performed on the DMN to examine the effective connectivity modulation in these two different conditions. During the resting state, there was strong self-influence in the regions of the DMN, while the main regions with statistically significant cross-regional effective connectivity were the posterior cingulate cortex (PCC) and the hippocampus (HP). During the memory task, the self-influence effective connectivities remained statistically significant across the DMN, and there were statistically significant effective connectivities from the PCC, HP, amygdala (AM), and parahippocampal region to other DMN regions. The authors found that effective connectivities from PCC, HP, and AM (in both resting state and during task) were linearly correlated to memory performance. The results suggest that superior memory ability in this older cohort was associated with effective connectivity both at rest and during the memory task of three DMN regions, which are also known to be important for memory function.

Network measures predict neuropsychological outcome after brain injury

Hubs are network components that hold positions of high importance for network function. Previous research has identified hubs in human brain networks derived from neuroimaging data; however, there is little consensus on the localization of such hubs. Moreover, direct evidence regarding the role of various proposed hubs in network function (e.g., cognition) is scarce. Regions of the default mode network (DMN) have been frequently identified as "cortical hubs" of brain networks. On theoretical grounds, we have argued against some of the methods used to identify these hubs and have advocated alternative approaches that identify different regions of cortex as hubs. Our framework predicts that our proposed hub locations may play influential roles in multiple aspects of cognition, and, in contrast, that hubs identified via other methods (including salient regions in the DMN) might not exert such broad influence. Here we used a neuropsychological approach to directly test these predictions by studying long-term cognitive and behavioral outcomes in 30 patients, 19 with focal lesions to six "target" hubs identified by our approaches (high system density and participation coefficient) and 11 with focal lesions to two "control" hubs (high degree centrality). In support of our predictions, we found that damage to target locations produced severe and widespread cognitive deficits, whereas damage to control locations produced more circumscribed deficits. These findings support our interpretation of how neuroimaging-derived network measures relate to cognition and augment classic neuroanatomically based predictions about cognitive and behavioral outcomes after focal brain injury.