Parietofrontal network upregulation after motor stroke

Identifying biomarkers related to motor function in chronic stroke: A fNIRS and TMS study

BACKGROUND

Upper limb motor impairment commonly occurs after stroke, impairing quality of life. Brain network reorganization likely differs between subgroups with differing impairment severity. This study explored differences in functional connectivity (FC) and corticospinal tract (CST) integrity between patients with mild/moderate versus severe hemiplegia poststroke to clarify the neural correlates underlying motor deficits.

METHOD

Sixty chronic stroke patients with upper limb motor impairment were categorized into mild/moderate and severe groups based on Fugl-Meyer scores. Resting-state FC was assessed using functional near-infrared spectroscopy (fNIRS) to compare connectivity patterns between groups across motor regions. CST integrity was evaluated by inducing motor evoked potentials (MEP) via transcranial magnetic stimulation.

RESULTS

Compared to the mild/moderate group, the severe group exhibited heightened premotor cortex-primary motor cortex (PMC-M1) connectivity (t = 4.56, p < 0.01). Absence of MEP was also more frequent in the severe group (χ2 = 12.31, p = 0.01). Bayesian models effectively distinguished subgroups and identified the PMC-M1 connection as highly contributory (accuracy = 91.30%, area under the receiver operating characteristic curve [AUC] = 0.86).

CONCLUSION

Distinct patterns of connectivity and corticospinal integrity exist between stroke subgroups with differing impairments. Strengthened connectivity potentially indicates recruitment of additional motor resources to compensate for damage. These findings elucidate the neural correlates underlying motor deficits poststroke and could guide personalized, network-based therapies targeting predictive biomarkers to improve rehabilitation outcomes.

Video mirror feedback induces more extensive brain activation compared to the mirror box: an fNIRS study in healthy adults

BACKGROUND

Mirror therapy (MT) has been shown to be effective for motor recovery of the upper limb after a stroke. The cerebral mechanisms of mirror therapy involve the precuneus, premotor cortex and primary motor cortex. Activation of the precuneus could be a marker of this effectiveness. MT has some limitations and video therapy (VT) tools are being developed to optimise MT. While the clinical superiority of these new tools remains to be demonstrated, comparing the cerebral mechanisms of these different modalities will provide a better understanding of the related neuroplasticity mechanisms.

METHODS

Thirty-three right-handed healthy individuals were included in this study. Participants were equipped with a near-infrared spectroscopy headset covering the precuneus, the premotor cortex and the primary motor cortex of each hemisphere. Each participant performed 3 tasks: a MT task (right hand movement and left visual feedback), a VT task (left visual feedback only) and a control task (right hand movement only). Perception of illusion was rated for MT and VT by asking participants to rate the intensity using a visual analogue scale. The aim of this study was to compare brain activation during MT and VT. We also evaluated the correlation between the precuneus activation and the illusion quality of the visual mirrored feedback.

RESULTS

We found a greater activation of the precuneus contralateral to the visual feedback during VT than during MT. We also showed that activation of primary motor cortex and premotor cortex contralateral to visual feedback was more extensive in VT than in MT. Illusion perception was not correlated with precuneus activation.

CONCLUSION

VT led to greater activation of a parieto-frontal network than MT. This could result from a greater focus on visual feedback and a reduction in interhemispheric inhibition in VT because of the absence of an associated motor task. These results suggest that VT could promote neuroplasticity mechanisms in people with brain lesions more efficiently than MT.

CLINICAL TRIAL REGISTRATION

NCT04738851.

Electroacupuncture alters brain network functional connectivity in subacute stroke: A randomised crossover trial

BACKGROUND

Electroacupuncture (EA) is a promising rehabilitation treatment for upper-limb motor recovery in stroke patients. However, the neurophysiological mechanisms underlying its clinical efficacy remain unclear. This study aimed to explore the immediate modulatory effects of EA on brain network functional connectivity and topological properties.

METHODS

The randomized, single-blinded, self-controlled two-period crossover trial was conducted among 52 patients with subacute subcortical stroke. These patients were randomly allocated to receive either EA as the initial intervention or sham electroacupuncture (SEA) as the initial intervention. After a washout period of 24 hours, participants underwent the alternate intervention (SEA or EA). Resting state electroencephalography signals were recorded synchronously throughout both phases of the intervention. The functional connectivity (FC) of the parietofrontal network and small-world (SW) property indices of the whole-brain network were compared across the entire course of the two interventions.

RESULTS

The results demonstrated that EA significantly altered ipsilesional parietofrontal network connectivity in the alpha and beta bands (alpha: F = 5.05, P = .011; beta: F = 3.295, P = .047), whereas no significant changes were observed in the SEA group. When comparing between groups, EA significantly downregulated ipsilesional parietofrontal network connectivity in both the alpha and beta bands during stimulation (alpha: t = -1.998, P = .049; beta: t = -2.342, P = .022). Significant differences were also observed in the main effects of time and the group × time interaction for the SW index (time: F = 5.516, P = .026; group × time: F = 6.892, P = .01). In terms of between-group comparisons, the EA group exhibited a significantly higher SW index than the SEA group at the post-stimulation stage (t = 2.379, P = .018).

CONCLUSION

These findings suggest that EA downregulates ipsilesional parietofrontal network connectivity and enhances SW properties, providing a potential neurophysiological mechanism for facilitating motor performance in stroke patients.

Effects of anodal tDCS on resting state eeg power and motor function in acute stroke: a randomized controlled trial

BACKGROUND

Anodal transcranial direct current stimulation (tDCS) is a beneficial adjunctive tool in stroke rehabilitation. However, only a few studies have investigated its effects on acute stroke and recruited only individuals with mild motor deficits. This study investigated the effect of five consecutive sessions of anodal tDCS and conventional physical therapy on brain activity and motor outcomes in individuals with acute stroke, with low and high motor impairments.

METHODS

Thirty participants were recruited and randomly allocated to either the anodal or sham tDCS group. Five consecutive sessions of tDCS (1.5 mA anodal or sham tDCS for 20 min) were administered, followed by conventional physical therapy. Electroencephalography (EEG), Fugl-Meyer Motor Assessment (FMA), and Wolf Motor Function Test (WMFT) were performed at pre-, post-intervention (day 5), and 1-month follow-up. Sub-analyses were performed on participants with low and high motor impairments. The relationship between EEG power and changes in motor functions was assessed.

RESULTS

Linear regression showed a significant positive correlation between beta bands and the FMA score in the anodal group. Elevated high frequency bands (alpha and beta) were observed at post-intervention and follow-up in all areas of both hemispheres in the anodal group, while only in the posterior area of the non-lesioned hemisphere in the sham group; however, such elevation induced by tDCS was not greater than sham. Lower limb function assessed by FMA was improved in the anodal group compared with the sham group at post-intervention and follow-up only in those with low motor impairment. For the upper limb outcomes, no difference between groups was found.

CONCLUSIONS

Five consecutive days of anodal tDCS and physical therapy in acute stroke did not result in a superior improvement of beta bands that commonly related to stroke recovery over sham, but improved lower extremity functions with a post-effect at 1-month follow-up in low motor impairment participants. The increase of beta bands in the lesioned brain in the anodal group was associated with improvement in lower limb function.

TRIAL REGISTRATION

NCT04578080, date of first registration 10/01/2020.

Cortical effects of wrist tendon vibration during an arm tracking task in chronic stroke survivors: An EEG study

The purpose of this study was to characterize changes in cortical activity and connectivity in stroke survivors when vibration is applied to the wrist flexor tendons during a visuomotor tracking task. Data were collected from 10 chronic stroke participants and 10 neurologically-intact controls while tracking a target through a figure-8 pattern in the horizontal plane. Electroencephalography (EEG) was used to measure cortical activity (beta band desynchronization) and connectivity (beta band task-based coherence) with movement kinematics and performance error also being recorded during the task. All participants came into our lab on two separate days and performed three blocks (16 trials each, 48 total trials) of tracking, with the middle block including vibration or sham applied at the wrist flexor tendons. The order of the sessions (Vibe vs. Sham) was counterbalanced across participants to prevent ordering effects. During the Sham session, cortical activity increased as the tracking task progressed (over blocks). This effect was reduced when vibration was applied to controls. In contrast, vibration increased cortical activity during the vibration period in participants with stroke. Cortical connectivity increased during vibration, with larger effect sizes in participants with stroke. Changes in tracking performance, standard deviation of hand speed, were observed in both control and stroke groups. Overall, EEG measures of brain activity and connectivity provided insight into effects of vibration on brain control of a visuomotor task. The increases in cortical activity and connectivity with vibration improved patterns of activity in people with stroke. These findings suggest that reactivation of normal cortical networks via tendon vibration may be useful during physical rehabilitation of stroke patients.

Posterior parietal cortical areas and recovery after motor stroke: a scoping review

Brain imaging and electrophysiology have significantly enhanced our current understanding of stroke-related changes in brain structure and function and their implications for recovery processes. In the motor domain, most studies have focused on key motor areas of the frontal lobe including the primary and secondary motor cortices. Time- and recovery-dependent alterations in regional anatomy, brain activity and inter-regional connectivity have been related to recovery. In contrast, the involvement of posterior parietal cortical areas in stroke recovery is poorly understood although these regions are similarly important for important aspects of motor functioning in the healthy brain. Just in recent years, the field has increasingly started to explore to what extent posterior parietal cortical areas might undergo equivalent changes in task-related activation, regional brain structure and inter-regional functional and structural connectivity after stroke. The aim of this scoping review is to give an update on available data covering these aspects and thereby providing novel insights into parieto-frontal interactions for systems neuroscience stroke recovery research in the upper limb motor domain.

Electroencephalography-based parietofrontal connectivity modulated by electroacupuncture for predicting upper limb motor recovery in subacute stroke

BACKGROUND

Predicting motor recovery in stroke patients is essential for effective rehabilitation planning and goal setting. However, intervention-specific biomarkers for such predictions are limited. This study investigates the potential of electroacupuncture (EA) - induced brain network connectivity as a prognostic biomarker for upper limb motor recovery in stroke.

METHODS

A randomized crossover and prospective observational study was conducted involving 40 stroke patients within 30 days of onset. Patients underwent both EA and sham electroacupuncture (SEA) interventions. Simultaneously, resting electroencephalography signals were recorded to assess brain response. Patients' motor function was monitored for 3 months and categorized into Poor and proportional (Prop) recovery groups. The correlations between the targeted brain network of parietofrontal (PF) functional connectivity (FC) during the different courses of the 2 EA interventions and partial least squares regression models were constructed to predict upper limb motor recovery.

RESULTS

Before the EA intervention, only ipsilesional PF network FC in the beta band correlated with motor recovery (r = -0.37, P = .041). Post-EA intervention, significant correlations with motor recovery were found in the beta band of the contralesional PF network FC (r = -0.43, P = .018) and the delta and theta bands of the ipsilesional PF network FC (delta: r = -0.59, P = .0004; theta: r = -0.45, P = .0157). No significant correlations were observed for the SEA intervention (all P > .05). Specifically, the delta band ipsilesional PF network FC after EA stimulation significantly differed between Poor and Prop groups (t = 3.474, P = .002, Cohen's d = 1.287, Poor > Prop). Moreover, the partial least squares regression model fitted after EA stimulation exhibited high explanatory power (R2 = 0.613), predictive value (Q2 = 0.547), and the lowest root mean square error (RMSE = 0.192) for predicting upper limb proportional recovery compared to SEA.

CONCLUSION

EA-induced PF network FC holds potential as a robust prognostic biomarker for upper limb motor recovery, providing valuable insights for clinical decision-making.

Test-retest reliability of fNIRS in resting-state cortical activity and brain network assessment in stroke patients

Resting-state functional near infrared spectroscopy (fNIRS) scanning has attracted considerable attention in stroke rehabilitation research in recent years. The aim of this study was to quantify the reliability of fNIRS in cortical activity intensity and brain network metrics among resting-state stroke patients, and to comprehensively evaluate the effects of frequency selection, scanning duration, analysis and preprocessing strategies on test-retest reliability. Nineteen patients with stroke underwent two resting fNIRS scanning sessions with an interval of 24 hours. The haemoglobin signals were preprocessed by principal component analysis, common average reference and haemodynamic modality separation (HMS) algorithm respectively. The cortical activity, functional connectivity level, local network metrics (degree, betweenness and local efficiency) and global network metrics were calculated at 25 frequency scales × 16 time windows. The test-retest reliability of each fNIRS metric was quantified by the intraclass correlation coefficient. The results show that (1) the high-frequency band has higher ICC values than the low-frequency band, and the fNIRS metric is more reliable than at the individual channel level when averaged within the brain region channel, (2) the ICC values of the low-frequency band above the 4-minute scan time are generally higher than 0.5, the local efficiency and global network metrics reach high and excellent reliability levels after 4 min (0.5 < ICC < 0.9), with moderate or even poor reliability for degree and betweenness (ICC < 0.5), (3) HMS algorithm performs best in improving the low-frequency band ICC values. The results indicate that a scanning duration of more than 4 minutes can lead to high reliability of most fNIRS metrics when assessing low-frequency resting brain function in stroke patients. It is recommended to use the global correction method of HMS, and the reporting of degree, betweenness and single channel level should be performed with caution. This paper provides the first comprehensive reference for resting-state experimental design and analysis strategies for fNIRS in stroke rehabilitation.

Brain network characteristics between subacute and chronic stroke survivors in active, imagery, passive movement task: a pilot study

Background

The activation patterns and functional network characteristics between stroke survivors and healthy individuals based on resting-or task-state neuroimaging and neurophysiological techniques have been extensively explored. However, the discrepancy between stroke patients at different recovery stages remains unclear.

Objective

To investigate the changes in brain connectivity and network topology between subacute and chronic patients, and hope to provide a basis for rehabilitation strategies at different stages after stroke.

Methods

Fifteen stroke survivors were assigned to the subacute group (SG, N = 9) and chronic group (CG, N = 6). They were asked to perform hand grasping under active, passive, and MI conditions when recording EEG. The Fugl-Meyer Assessment Upper Extremity subscale (FMA_UE), modified Ashworth Scale (MAS), Manual Muscle Test (MMT), grip and pinch strength, modified Barthel Index (MBI), and Berg Balance Scale (BBS) were measured.

Results

Functional connectivity analyses showed significant interactions on frontal, parietal and occipital lobes connections in each frequency band, particularly in the delta band. The coupling strength of premotor cortex, M1, S1 and several connections linked to frontal, parietal, and occipital lobes in subacute subjects were lower than in chronic subjects in low alpha, high alpha, low beta, and high beta bands. Nodal clustering coefficient (CC) analyses revealed that the CC in chronic subjects was higher than in subacute subjects in the ipsilesional S1 and occipital area, contralesional dorsolateral prefrontal cortex and parietal area. Characteristic path length (CPL) analyses showed that CPL in subacute subjects was lower than in chronic subjects in low beta, high beta, and gamma bands. There were no significant differences between subacute and chronic subjects for small-world property.

Conclusion

Subacute stroke survivors were characterized by higher transfer efficiency of the entire brain network and weak local nodal effects. Transfer efficiency was reduced, the local nodal role was strengthened, and more neural resources needed to be mobilized to perform motor tasks for chronic survivors. Overall, these results may help to understand the remodeling pattern of the brain network for different post-stroke stages on task conditions and the mechanism of spontaneous recovery.

Early functional connectivity alterations in contralesional motor networks influence outcome after severe stroke: a preliminary analysis

Connectivity studies have significantly extended the knowledge on motor network alterations after stroke. Compared to interhemispheric or ipsilesional networks, changes in the contralesional hemisphere are poorly understood. Data obtained in the acute stage after stroke and in severely impaired patients are remarkably limited. This exploratory, preliminary study aimed to investigate early functional connectivity changes of the contralesional parieto-frontal motor network and their relevance for the functional outcome after severe motor stroke. Resting-state functional imaging data were acquired in 19 patients within the first 2 weeks after severe stroke. Nineteen healthy participants served as a control group. Functional connectivity was calculated from five key motor areas of the parieto-frontal network on the contralesional hemisphere as seed regions and compared between the groups. Connections exhibiting stroke-related alterations were correlated with clinical follow-up data obtained after 3-6 months. The main finding was an increase in coupling strength between the contralesional supplementary motor area and the sensorimotor cortex. This increase was linked to persistent clinical deficits at follow-up. Thus, an upregulation in contralesional motor network connectivity might be an early pattern in severely impaired stroke patients. It might carry relevant information regarding the outcome which adds to the current concepts of brain network alterations and recovery processes after severe stroke.

Effects of integrated action and sensory observation therapy based on mirror neuron and embodied cognition theory on upper limb sensorimotor function in chronic stroke: a study protocol for a randomised controlled trial

INTRODUCTION

This study protocol aims to explore the effectiveness and neural mechanism of the integration of action observation therapy (AOT) and sensory observation therapy (SOT) for post-stroke patients on upper limb sensorimotor function.

METHODS AND ANALYSIS

This is a single-centre, single-blind, randomised controlled trial. A total of 69 patients with upper extremity hemiparesis after stroke will be recruited and randomly divided into an AOT group, a combined action observation and somatosensory stimulation therapy (AOT+SST) group, and a combined AOT and SOT (AOT+SOT) group in a 1:1:1 ratio. Each group will receive 30 min of daily treatment, five times weekly for 4 weeks. The primary clinical outcome will be the Fugl-Meyer Assessment for Upper Extremity. Secondary clinical outcomes will include the Box and Blocks Test, modified Barthel Index and sensory assessment. All clinical assessments and resting-state functional MRI and diffusion tensor imaging data will be obtained at pre-intervention (T1), post-intervention (T2) and 8 weeks of follow-up (T3).

ETHICS AND DISSEMINATION

The trial was approved by the Ethics Committee of Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Chinese Traditional Medicine (Grant No. 2020-178). The results will be submitted to a peer-review journal or at a conference.

TRIAL REGISTRATION NUMBER

ChiCTR2000040568.

Oscillatory neurofeedback networks and poststroke rehabilitative potential in severely impaired stroke patients

Motor restoration after severe stroke is often limited. However, some of the severely impaired stroke patients may still have a rehabilitative potential. Biomarkers that identify these patients are sparse. Eighteen severely impaired chronic stroke patients with a lack of volitional finger extension participated in an EEG study. During sixty-six trials of kinesthetic motor imagery, a brain-machine interface turned event-related beta-band desynchronization of the ipsilesional sensorimotor cortex into opening of the paralyzed hand by a robotic orthosis. A subgroup of eight patients participated in a subsequent four-week rehabilitation training. Changes of the movement extent were captured with sensors which objectively quantified even discrete improvements of wrist movement. Albeit with the same motor impairment level, patients could be differentiated into two groups, i.e., with and without task-related increase of bilateral cortico-cortical phase synchronization between frontal/premotor and parietal areas. This fronto-parietal integration (FPI) was associated with a significantly higher volitional beta modulation range in the ipsilesional sensorimotor cortex. Following the four-week training, patients with FPI showed significantly higher improvement in wrist movement than those without FPI. Moreover, only the former group improved significantly in the upper extremity Fugl-Meyer-Assessment score. Neurofeedback-related long-range oscillatory coherence may differentiate severely impaired stroke patients with regard to their rehabilitative potential, a finding that needs to be confirmed in larger patient cohorts.

Structural plasticity of motor cortices assessed by voxel-based morphometry and immunohistochemical analysis following internal capsular infarcts in macaque monkeys

Compensatory plastic changes in the remaining intact brain regions are supposedly involved in functional recovery following stroke. Previously, a compensatory increase in cortical activation occurred in the ventral premotor cortex (PMv), which contributed to the recovery of dexterous hand movement in a macaque model of unilateral internal capsular infarcts. Herein, we investigated the structural plastic changes underlying functional changes together with voxel-based morphometry (VBM) analysis of magnetic resonance imaging data and immunohistochemical analysis using SMI-32 antibody in a macaque model. Unilateral internal capsular infarcts were pharmacologically induced in 5 macaques, and another 5 macaques were used as intact controls for immunohistochemical analysis. Three months post infarcts, we observed significant increases in the gray matter volume (GMV) and the dendritic arborization of layer V pyramidal neurons in the contralesional rostral PMv (F5) as well as the primary motor cortex (M1). The histological analysis revealed shrinkage of neuronal soma and dendrites in the ipsilesional M1 and several premotor cortices, despite not always detecting GMV reduction by VBM analysis. In conclusion, compensatory structural changes occur in the contralesional F5 and M1 during motor recovery following internal capsular infarcts, and the dendritic growth of pyramidal neurons is partially correlated with GMV increase.

Relation Between EEG Measures and Upper Limb Motor Recovery in Stroke Patients: A Scoping Review

Current clinical practice does not leverage electroencephalography (EEG) measurements in stroke patients, despite its potential to contribute to post-stroke recovery predictions. We review the literature on the effectiveness of various quantitative and qualitative EEG-based measures after stroke as a tool to predict upper limb motor outcome, in relation to stroke timeframe and applied experimental tasks. Moreover, we aim to provide guidance on the use of EEG in the assessment of upper limb motor recovery after stroke, suggesting a high potential for some metrics in the appropriate context. We identified relevant papers (N = 16) from databases ScienceDirect, Web of Science and MEDLINE, and assessed their methodological quality with the Joanna Briggs Institute (JBI) Critical Appraisal. We applied the Preferred Reporting Systems for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) Framework. Identified works used EEG to identify properties including event-related activation, spectral power in physiologically relevant bands, symmetry in brain dynamics, functional connectivity, cortico-muscular coherence and rhythmic coordination. EEG was acquired in resting state or in relation to behavioural conditions. Motor outcome was mainly evaluated with the Upper Limb Fugl-Meyer Assessment. Despite great variability in the literature, data suggests that the most promising EEG quantifiers for predicting post-stroke motor outcome are event-related measures. Measures of spectral power in physiologically relevant bands and measures of brain symmetry also show promise. We suggest that EEG measures may improve our understanding of stroke brain dynamics during recovery, and contribute to establishing a functional prognosis and choosing the rehabilitation approach.

Recovered grasping performance after stroke depends on interhemispheric frontoparietal connectivity

Activity changes in the ipsi- and contralesional parietal cortex and abnormal interhemispheric connectivity between these regions are commonly observed after stroke, however, their significance for motor recovery remains poorly understood. We here assessed the contribution of ipsilesional and contralesional anterior intraparietal cortex (aIPS) for hand motor function in 18 recovered chronic stroke patients and 18 healthy control subjects using a multimodal assessment consisting of resting-state functional MRI, motor task functional MRI, online-repetitive transcranial magnetic stimulation (rTMS) interference, and 3D movement kinematics. Effects were compared against two control stimulation sites, i.e. contralesional M1 and a sham stimulation condition. We found that patients with good motor outcome compared to patients with more substantial residual deficits featured increased resting-state connectivity between ipsilesional aIPS and contralesional aIPS as well as between ipsilesional aIPS and dorsal premotor cortex. Moreover, interhemispheric connectivity between ipsilesional M1 and contralesional M1 as well as ipsilesional aIPS and contralesional M1 correlated with better motor performance across tasks. TMS interference at individual aIPS and M1 coordinates led to differential effects depending on the motor task that was tested, i.e. index finger-tapping, rapid pointing movements, or a reach-grasp-lift task. Interfering with contralesional aIPS deteriorated the accuracy of grasping, especially in patients featuring higher connectivity between ipsi- and contralesional aIPS. In contrast, interference with the contralesional M1 led to impaired grasping speed in patients featuring higher connectivity between bilateral M1. These findings suggest differential roles of contralesional M1 and aIPS for distinct aspects of recovered hand motor function, depending on the reorganization of interhemispheric connectivity.

Effective brain network analysis in unilateral and bilateral upper limb exercise training in subjects with stroke

PURPOSE

Knowing the patterns of brain activation that occur and networks involved under different interventions is important for motor recovery in subjects with stroke. This study aimed to study the patterns of brain activation and networks in two interventions, affected upper limb side and bilateral exercise training, using concurrent functional near-infrared spectroscopy (fNIRS) imaging.

METHODS

Thirty-two patients in the early subacute stage were randomly divided into two groups: unilateral and bilateral groups. The patients in the unilateral group underwent isokinetic muscle strength training on the affected upper limb side and patients in the bilateral group underwent bilateral upper limb training. Oxyhemoglobin and deoxyhemoglobin concentration changes (ΔHbO₂ and ΔHbR, respectively) were recorded in the ipsilateral and contralateral prefrontal cortex (IPFC and CPFC, respectively) and ipsilateral and contralateral motor cortex (IMC and CMC, respectively) by fNIRS equipment in the resting state and training conditions. The phase information of a 0.01-0.08 Hz fNIRS signal was extracted by the wavelet transform method. Dynamic Bayesian inference was adopted to calculate the coupling strength and direction of effective connectivity. The network threshold was determined by surrogate signal method, the global (weighted clustering coefficient, global efficiency and small-worldness) and local (degree, betweenness centrality and local efficiency) network metrics were calculated. The degree of cerebral lateralization was also compared between the two groups.

RESULTS

The results of covariance analysis showed that, compared with bilateral training, the coupling effect of CMC→IMC was significantly enhanced (p = 0.03); also, the local efficiency of the IMC (p = 0.01), IPFC (p<0.001), and CPFC (p = 0.006) and the hemispheric autonomy index of IPFC (p = 0.007) were significantly increased in unilateral training. In addition, there was a significant positive correlation between the coupling intensity of the inter-hemispheric motor area and the shifted local efficiency.

CONCLUSIONS

The results indicated that unilateral upper limb training could more effectively promote the interaction and balance of bilateral motor hemispheres and help brain reorganization in the IMC and prefrontal cortex in stroke patients. The method provided in this study could be used to evaluate dynamic brain activation and network reorganization under different interventions, thus improving the strategy of rehabilitation intervention in a timely manner and resulting in better motor recovery. This article is protected by copyright. All rights reserved.

Electroencephalogram (EEG) With or Without Transcranial Magnetic Stimulation (TMS) as Biomarkers for Post-stroke Recovery: A Narrative Review

Stroke is one of the leading causes of death and disability. Despite the high prevalence of stroke, characterizing the acute neural recovery patterns that follow stroke and predicting long-term recovery remains challenging. Objective methods to quantify and characterize neural injury are still lacking. Since neuroimaging methods have a poor temporal resolution, EEG has been used as a method for characterizing post-stroke recovery mechanisms for various deficits including motor, language, and cognition as well as predicting treatment response to experimental therapies. In addition, transcranial magnetic stimulation (TMS), a form of non-invasive brain stimulation, has been used in conjunction with EEG (TMS-EEG) to evaluate neurophysiology for a variety of indications. TMS-EEG has significant potential for exploring brain connectivity using focal TMS-evoked potentials and oscillations, which may allow for the system-specific delineation of recovery patterns after stroke. In this review, we summarize the use of EEG alone or in combination with TMS in post-stroke motor, language, cognition, and functional/global recovery. Overall, stroke leads to a reduction in higher frequency activity (≥8 Hz) and intra-hemispheric connectivity in the lesioned hemisphere, which creates an activity imbalance between non-lesioned and lesioned hemispheres. Compensatory activity in the non-lesioned hemisphere leads mostly to unfavorable outcomes and further aggravated interhemispheric imbalance. Balanced interhemispheric activity with increased intrahemispheric coherence in the lesioned networks correlates with improved post-stroke recovery. TMS-EEG studies reveal the clinical importance of cortical reactivity and functional connectivity within the sensorimotor cortex for motor recovery after stroke. Although post-stroke motor studies support the prognostic value of TMS-EEG, more studies are needed to determine its utility as a biomarker for recovery across domains including language, cognition, and hemispatial neglect. As a complement to MRI-based technologies, EEG-based technologies are accessible and valuable non-invasive clinical tools in stroke neurology.

A survey of brain network analysis by electroencephalographic signals

Brain network analysis is one efficient tool in exploring human brain diseases and can differentiate the alterations from comparative networks. The alterations account for time, mental states, tasks, individuals, and so forth. Furthermore, the changes determine the segregation and integration of functional networks that lead to network reorganization (or reconfiguration) to extend the neuroplasticity of the brain. Exploring related brain networks should be of interest that may provide roadmaps for brain research and clinical diagnosis. Recent electroencephalogram (EEG) studies have revealed the secrets of the brain networks and diseases (or disorders) within and between subjects and have provided instructive and promising suggestions and methods. This review summarized the corresponding algorithms that had been used to construct functional or effective networks on the scalp and cerebral cortex. We reviewed EEG network analysis that unveils more cognitive functions and neural disorders of the human and then explored the relationship between brain science and artificial intelligence which may fuel each other to accelerate their advances, and also discussed some innovations and future challenges in the end.

Coherent neural oscillations inform early stroke motor recovery

Neural oscillations may contain important information pertaining to stroke rehabilitation. This study examined the predictive performance of electroencephalography‐derived neural oscillations following stroke using a data‐driven approach. Individuals with stroke admitted to an inpatient rehabilitation facility completed a resting‐state electroencephalography recording and structural neuroimaging around the time of admission and motor testing at admission and discharge. Using a lasso regression model with cross‐validation, we determined the extent of motor recovery (admission to discharge change in Functional Independence Measurement motor subscale score) prediction from electroencephalography, baseline motor status, and corticospinal tract injury. In 27 participants, coherence in a 1–30 Hz band between leads overlying ipsilesional primary motor cortex and 16 leads over bilateral hemispheres predicted 61.8% of the variance in motor recovery. High beta (20–30 Hz) and alpha (8–12 Hz) frequencies contributed most to the model demonstrating both positive and negative associations with motor recovery, including high beta leads in supplementary motor areas and ipsilesional ventral premotor and parietal regions and alpha leads overlying contralesional temporal–parietal and ipsilesional parietal regions. Electroencephalography power, baseline motor status, and corticospinal tract injury did not significantly predict motor recovery during hospitalization (R² = 0–6.2%). Findings underscore the relevance of oscillatory synchronization in early stroke rehabilitation while highlighting contributions from beta and alpha frequency bands and frontal, parietal, and temporal–parietal regions overlooked by traditional hypothesis‐driven prediction models.

Reorganization of Brain Functional Connectivity Network and Vision Restoration Following Combined tACS-tDCS Treatment After Occipital Stroke

Objective: Non-invasive brain stimulation (NIBS) is already known to improve visual field functions in patients with optic nerve damage and partially restores the organization of brain functional connectivity networks (FCNs). However, because little is known if NIBS is effective also following brain damage, we now studied the correlation between visual field recovery and FCN reorganization in patients with stroke of the central visual pathway.

Method: In a controlled, exploratory trial, 24 patients with hemianopia were randomly assigned to one of three brain stimulation groups: transcranial direct current stimulation (tDCS)/transcranial alternating current stimulation (tACS) (ACDC); sham tDCS/tACS (AC); sham tDCS/sham tACS (Sham), which were compared to age-matched controls (n = 24). Resting-state electroencephalogram (EEG) was collected at baseline, after 10 days stimulation and at 2 months follow-up. EEG recordings were analyzed for FCN measures using graph theory parameters, and FCN small worldness of the network and long pairwise coherence parameter alterations were then correlated with visual field performance.

Result: ACDC enhanced alpha-band FCN strength in the superior occipital lobe of the lesioned hemisphere at follow-up. A negative correlation (r = −0.80) was found between the intact visual field size and characteristic path length (CPL) after ACDC with a trend of decreased alpha-band centrality of the intact middle occipital cortex. ACDC also significantly decreased delta band coherence between the lesion and the intact occipital lobe, and coherence was enhanced between occipital and temporal lobe of the intact hemisphere in the low beta band. Responders showed significantly higher strength in the low alpha band at follow-up in the intact lingual and calcarine cortex and in the superior occipital region of the lesioned hemisphere.

Conclusion: While ACDC decreases delta band coherence between intact and damaged occipital brain areas indicating inhibition of low-frequency neural oscillations, ACDC increases FCN connectivity between the occipital and temporal lobe in the intact hemisphere. When taken together with the lower global clustering coefficient in responders, these findings suggest that FCN reorganization (here induced by NIBS) is adaptive in stroke. It leads to greater efficiency of neural processing, where the FCN requires fewer connections for visual processing.

Corticospinal Tract Microstructure Correlates With Beta Oscillatory Activity in the Primary Motor Cortex After Stroke

BACKGROUND AND PURPOSE

Cortical beta oscillations are reported to serve as robust measures of the integrity of the human motor system. Their alterations after stroke, such as reduced movement-related beta desynchronization in the primary motor cortex, have been repeatedly related to the level of impairment. However, there is only little data whether such measures of brain function might directly relate to structural brain changes after stroke.

METHODS

This multimodal study investigated 18 well-recovered patients with stroke (mean age 65 years, 12 males) by means of task-related EEG and diffusion-weighted structural MRI 3 months after stroke. Beta power at rest and movement-related beta desynchronization was assessed in 3 key motor areas of the ipsilesional hemisphere that are the primary motor cortex (M1), the ventral premotor area and the supplementary motor area. Template trajectories of corticospinal tracts (CST) originating from M1, premotor cortex, and supplementary motor area were used to quantify the microstructural state of CST subcomponents. Linear mixed-effects analyses were used to relate tract-related mean fractional anisotropy to EEG measures.

RESULTS

In the present cohort, we detected statistically significant reductions in ipsilesional CST fractional anisotropy but no alterations in EEG measures when compared with healthy controls. However, in patients with stroke, there was a significant association between both beta power at rest (P=0.002) and movement-related beta desynchronization (P=0.003) in M1 and fractional anisotropy of the CST specifically originating from M1. Similar structure-function relationships were neither evident for ventral premotor area and supplementary motor area, particularly with respect to their CST subcomponents originating from premotor cortex and supplementary motor area, in patients with stroke nor in controls.

CONCLUSIONS

These data suggest there might be a link connecting microstructure of the CST originating from M1 pyramidal neurons and beta oscillatory activity, measures which have already been related to motor impairment in patients with stroke by previous reports.

The structural connectome and motor recovery after stroke: predicting natural recovery

Stroke patients vary considerably in terms of outcomes: some patients present 'natural' recovery proportional to their initial impairment (fitters), while others do not (non-fitters). Thus, a key challenge in stroke rehabilitation is to identify individual recovery potential to make personalized decisions for neuro-rehabilitation, obviating the 'one-size-fits-all' approach. This goal requires (i) the prediction of individual courses of recovery in the acute stage; and (ii) an understanding of underlying neuronal network mechanisms. 'Natural' recovery is especially variable in severely impaired patients, underscoring the special clinical importance of prediction for this subgroup. Fractional anisotropy connectomes based on individual tractography of 92 patients were analysed 2 weeks after stroke (TA) and their changes to 3 months after stroke (TC - TA). Motor impairment was assessed using the Fugl-Meyer Upper Extremity (FMUE) scale. Support vector machine classifiers were trained to separate patients with natural recovery from patients without natural recovery based on their whole-brain structural connectomes and to define their respective underlying network patterns, focusing on severely impaired patients (FMUE < 20). Prediction accuracies were cross-validated internally, in one independent dataset and generalized in two independent datasets. The initial connectome 2 weeks after stroke was capable of segregating fitters from non-fitters, most importantly among severely impaired patients (TA: accuracy = 0.92, precision = 0.93). Secondary analyses studying recovery-relevant network characteristics based on the selected features revealed (i) relevant differences between networks contributing to recovery at 2 weeks and network changes over time (TC - TA); and (ii) network properties specific to severely impaired patients. Important features included the parietofrontal motor network including the intraparietal sulcus, premotor and primary motor cortices and beyond them also attentional, somatosensory or multimodal areas (e.g. the insula), strongly underscoring the importance of whole-brain connectome analyses for better predicting and understanding recovery from stroke. Computational approaches based on structural connectomes allowed the individual prediction of natural recovery 2 weeks after stroke onset, especially in the difficult to predict group of severely impaired patients, and identified the relevant underlying neuronal networks. This information will permit patients to be stratified into different recovery groups in clinical settings and will pave the way towards personalized precision neurorehabilitative treatment.

Early parietofrontal network upregulation relates to future persistent deficits after severe stroke-a prospective cohort study

Recent brain imaging has evidenced that parietofrontal networks show alterations after stroke which also relate to motor recovery processes. There is converging evidence for an upregulation of parietofrontal coupling between parietal brain regions and frontal motor cortices. The majority of studies though have included only moderately to mildly affected patients, particularly in the subacute or chronic stage. Whether these network alterations will also be present in severely affected patients and early after stroke and whether such information can improve correlative models to infer motor recovery remains unclear. In this prospective cohort study, 19 severely affected first-ever stroke patients (mean age 74 years, 12 females) were analysed which underwent resting-state functional MRI and clinical testing during the initial week after the event. Clinical evaluation of neurological and motor impairment as well as global disability was repeated after three and six months. Nineteen healthy participants of similar age and gender were also recruited. MRI data were used to calculate functional connectivity values between the ipsilesional primary motor cortex, the ventral premotor cortex, the supplementary motor area and the anterior and caudal intraparietal sulcus of the ipsilesional hemisphere. Linear regression models were estimated to compare parietofrontal functional connectivity between stroke patients and healthy controls and to relate them to motor recovery. The main finding was a significant increase in ipsilesional parietofrontal coupling between anterior intraparietal sulcus and the primary motor cortex in severely affected stroke patients (P < 0.003). This upregulation significantly contributed to correlative models explaining variability in subsequent neurological and global disability as quantified by National Institute of Health Stroke Scale and modified Rankin Scale, respectively. Patients with increased parietofrontal coupling in the acute stage showed higher levels of persistent deficits in the late subacute stage of recovery (P < 0.05). This study provides novel insights that parietofrontal networks of the ipsilesional hemisphere undergo neuroplastic alteration already very early after severe motor stroke. The association between early parietofrontal upregulation and future levels of persistent functional deficits and dependence from help in daily living might be useful in models to enhance clinical neurorehabilitative decision making.

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.

Fronto-parietal involvement in chronic stroke motor performance when corticospinal tract integrity is compromised

BACKGROUND

Preserved integrity of the corticospinal tract (CST) is a marker of good upper-limb behavior and recovery following stroke. However, there is less understanding of neural mechanisms that might help facilitate upper-limb motor recovery in stroke survivors with extensive CST damage.

OBJECTIVE

The purpose of this study was to investigate resting state functional connectivity in chronic stroke survivors with different levels of CST damage and to explore neural correlates of greater upper-limb motor performance in stroke survivors with compromised ipsilesional CST integrity.

METHODS

Thirty chronic stroke survivors (24 males, aged 64.7 ± 10.8 years) participated in this study. Three experimental sessions were conducted to: 1) obtain anatomical (T1, T2) structural (diffusion) and functional (resting state) MRI sequences, 2) determine CST integrity with transcranial magnetic stimulation (TMS) and conduct assessments of upper-limb behavior, and 3) reconfirm CST integrity status. Participants were divided into groups according to the extent of CST damage. Those in the extensive CST damage group did not show TMS evoked responses and had significantly lower ipsilesional fractional anisotropy.

RESULTS

Of the 30 chronic stroke survivors, 12 were categorized as having extensive CST damage. Stroke survivors with extensive CST damage had weaker functional connectivity in the ipsilesional sensorimotor network and greater functional connectivity in the ipsilesional fronto-parietal network compared to those with preserved CST integrity. For participants with extensive CST damage, improved motor performance was associated with greater functional connectivity of the ipsilesional fronto-parietal network and higher fractional anisotropy of the ipsilesional rostral superior longitudinal fasciculus.

CONCLUSIONS

Stroke survivors with extensive CST damage have greater resting state functional connectivity of an ipsilesional fronto-parietal network that appears to be a behaviorally relevant neural mechanism that improves upper-limb motor performance.

Neural Correlates of Age-Related Changes in Precise Grip Force Regulation: A Combined EEG-fNIRS Study

Motor control is associated with suppression of oscillatory activity in alpha (8–12 Hz) and beta (12–30 Hz) ranges and elevation of oxygenated hemoglobin levels in motor-cortical areas. Aging leads to changes in oscillatory and hemodynamic brain activity and impairments in motor control. However, the relationship between age-related changes in motor control and brain activity is not yet fully understood. Therefore, this study aimed to investigate age-related and task-complexity-related changes in grip force control and the underlying oscillatory and hemodynamic activity. Sixteen younger [age (mean ± SD) = 25.4 ± 1.9, 20–30 years] and 16 older (age = 56.7 ± 4.7, 50–70 years) healthy men were asked to use a power grip to perform six trials each of easy and complex force tracking tasks (FTTs) with their right dominant hand in a randomized within-subject design. Grip force control was assessed using a sensor-based device. Brain activity in premotor and primary motor areas of both hemispheres was assessed by electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS). Older adults showed significantly higher inaccuracies and higher hemodynamic activity in both FTTs than did young adults. Correlations between grip force control owing to task complexity and beta activity were different in the contralateral premotor cortex (PMC) between younger and older adults. Collectively, these findings suggest that aging leads to impairment of grip force control and an increase in hemodynamic activity independent of task complexity. EEG beta oscillations may represent a task-specific neurophysiological marker for age-related decline in complex grip force control and its underlying compensation strategies. Further EEG-fNIRS studies are necessary to determine neurophysiological markers of dysfunctions underlying age-related motor disabilities for the improvement of individual diagnosis and therapeutic approaches.

Age of onset determines intrinsic functional brain architecture in Friedreich ataxia

OBJECTIVE

Friedreich ataxia (FRDA) is the commonest hereditary ataxia in Caucasians. Most patients are homozygous for expanded GAA triplet repeats in the first intron of the frataxin (FXN) gene, involved in mitochondrial iron metabolism. Here, we used magnetoencephalography (MEG) to characterize the main determinants of FRDA-related changes in intrinsic functional brain architecture.

METHODS

Five minutes of MEG signals were recorded at rest from 18 right-handed FRDA patients (mean age 27 years, 9 females; mean SARA score: 21.4) and matched healthy individuals. The MEG connectome was estimated as resting-state functional connectivity (rsFC) matrices involving 37 nodes from six major resting state networks and the cerebellum. Source-level rsFC maps were computed using leakage-corrected broad-band (3-40 Hz) envelope correlations. Post hoc median-split was used to contrast rsFC in FRDA patients with different clinical characteristics. Nonparametric permutations and Spearman rank correlation test were used for statistics.

RESULTS

High rank correlation levels were found between rsFC and age of symptoms onset in FRDA mostly between the ventral attention, the default-mode, and the cerebellar networks; patients with higher rsFC developing symptoms at an older age. Increased rsFC was found in FRDA with later age of symptoms onset compared to healthy subjects. No correlations were found between rsFC and other clinical parameters.

CONCLUSION

Age of symptoms onset is a major determinant of FRDA patients' intrinsic functional brain architecture. Higher rsFC in FRDA patients with later age of symptoms onset supports compensatory mechanisms for FRDA-related neural network dysfunction and position neuromagnetic rsFC as potential marker of FRDA neural reserve.

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.

Low-Frequency Brain Oscillations Track Motor Recovery in Human Stroke

OBJECTIVE

The majority of patients with stroke survive the acute episode and live with enduring disability. Effective therapies to support recovery of motor function after stroke are yet to be developed. Key to this development is the identification of neurophysiologic signals that mark recovery and are suitable and susceptible to interventional therapies. Movement preparatory low-frequency oscillations (LFOs) play a key role in cortical control of movement. Recent animal data point to a mechanistic role of motor cortical LFOs in stroke motor deficits and demonstrate neuromodulation intervention with therapeutic benefit. Their relevance in human stroke pathophysiology is unknown.

METHODS

We studied the relationship between movement-preparatory LFOs during the performance of a visuomotor grip task and motor function in a longitudinal (<5 days, 1 and 3 months) cohort study of 33 patients with motor stroke and in 19 healthy volunteers.

RESULTS

Acute stroke-lesioned brains fail to generate the LFO signal. Whereas in healthy humans, a transient occurrence of LFOs preceded movement onset at predominantly contralateral frontoparietal motor regions, recordings in patients revealed that movement-preparatory LFOs were substantially diminished to a level of 38% after acute stroke. LFOs progressively increased at 1 and 3 months. This re-emergence closely tracked the recovery of motor function across several movement qualities including grip strength, fine motor skills, and synergies and was frequency band specific.

INTERPRETATION

Our results provide the first human evidence for a link between movement-preparatory LFOs and functional recovery after stroke, promoting their relevance for movement control. These results suggest that it may be interesting to explore targeted, LFOs-restorative brain stimulation therapy in human stroke patients. ANN NEUROL 2019;86:853-865.

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

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

Compressibility of High-Density EEG Signals in Stroke Patients

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