Early motor network connectivity after stroke: An interplay of general reorganization and state-specific compensation

Efficacy of combined non-invasive brain stimulation and robot-assisted gait training on lower extremity recovery post-stroke: a systematic review and meta-analysis of randomized controlled trials

Background

Lower extremity dysfunction post-stroke significantly impedes patient independence and quality of life. Non-invasive brain stimulation (NIBS) and robot-assisted gait training (RAGT) have individually shown promising outcomes in gait recovery. However, the synergistic efficacy of non-invasive brain stimulation combined with robot-assisted gait training remains uncertain. This systematic review and meta-analysis aim to evaluate the combined therapy's effectiveness on gait improvement and related motor functions in stroke patients.

Methods

Following PRISMA guidelines, a comprehensive search was conducted to identify randomized controlled trials (RCTs) published up to September 2024. The primary outcome was assessed using the 6-min walk test (6MWT), with secondary outcomes examining assessed using the Functional Ambulation Category (FAC); the Motion Index (MI) to analyze exercise intensity; the Modified Ashworth Scale (MAS) to assess spasticity; and spatiotemporal gait parameters (SPG).

Results

Six randomized controlled trials involving 191 stroke patients were included. Meta-analysis revealed that combined non-invasive brain stimulation and robot-assisted gait training significantly improved the 6-min walk test scores (mean difference [MD] = 21.81, 95% CI = 0.03-43.59), though effects on strength, activity participation, spasticity, and coordination were non-significant.

Conclusion

Non-invasive brain stimulation combined with robot-assisted gait training shows potential in enhancing gait function but provides limited additional benefits for other motor functions. This combined approach may serve as an effective rehabilitation strategy for post-stroke gait recovery, warranting further large-scale studies to refine intervention protocols.

Systematic review registration

https://www.crd.york.ac.uk/PROSPERO/view/CRD42021283890.

Differences in motor network reorganization between patients with good and poor upper extremity impairment outcomes after stroke

Changes in cortical excitability after stroke are closely associated with motor function recovery. This study aimed to clarify the motor network reorganization mechanisms corresponding to the different clinical outcomes of upper limb motor impairment in patients with subacute stroke. Motor function was assessed before rehabilitation (pre), after rehabilitation (post), and at the 1-year follow-up (follow-up) using the Fugl-Meyer assessment upper extremity scale. Further, resting-state functional magnetic resonance imaging (fMRI) data were collected in both pre- and post-conditions. Twenty patients with stroke were categorized into good and poor outcome groups based on motor impairments at the 1-year follow-up. Functional connections between motor-related regions of interest and the rest of the brain were subsequently calculated. Finally, the correlation between motor network reorganization and behavioral improvement at the 1-year follow-up was analyzed. The good outcome group exhibited a positive precondition motor function and continuous improvement, whereas the poor outcome group showed a weak precondition motor function and insignificant improvement. Contralesional hemisphere-related connections were found to be higher in the good outcome group pre-conditioning, with both groups showing minimal change post-conditioning, while no relationship with motor impairment was found. Long interhemispheric connections were decreased and increased in the good and poor outcome groups respectively, and were negatively correlated with motor impairment. Different motor network reorganizations during the subacute phase can influence the varying motor outcomes in the affected upper limb after stroke. These findings may serve as the theoretical basis for future neuromodulatory research.

Corticospinal premotor fibers facilitate complex motor control after stroke

OBJECTIVE

The corticospinal tract (CST) is considered the most important motor output pathway comprising fibers from the primary motor cortex (M1) and various premotor areas. Damage to its descending fibers after stroke commonly leads to motor impairment. While premotor areas are thought to critically support motor recovery after stroke, the functional role of their corticospinal output for different aspects of post-stroke motor control remains poorly understood.

METHODS

We assessed the differential role of CST fibers originating from premotor areas and M1 in the control of basal (single-joint muscle synergies and strength) and complex motor control (involving inter-joint coordination and visuomotor integration) using a novel diffusion imaging approach in chronic stroke patients.

RESULTS

While M1 sub-tract anisotropy was positively correlated with basal and complex motor skills, anisotropy of PMd, PMv, and SMA sub-tracts was exclusively associated with complex motor tasks. Interestingly, patients featuring persistent motor deficits showed an additional positive association between premotor sub-tract integrity and basal motor control.

INTERPRETATION

While descending M1 output seems to be a prerequisite for any form of upper limb movements, complex motor skills critically depend on output from premotor areas after stroke. The additional involvement of premotor tracts in basal motor control in patients with persistent deficits emphasizes their compensatory capacity in post-stroke motor control. In summary, our findings highlight the pivotal role of descending corticospinal output from premotor areas for motor control after stroke, which thus serve as prime candidates for future interventions to amplify motor recovery.

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.

Comparison of the activation level in the sensorimotor cortex between motor point and proximal nerve bundle electrical stimulation

Objective.Neuromuscular electrical stimulation (NMES) is widely used for motor function rehabilitation in stroke survivors. Compared with the conventional motor point (MP) stimulation, the stimulation at the proximal segment of the peripheral nerve (PN) bundles has been demonstrated to have multiple advantages. However, it is not known yet whether the PN stimulation can increase the cortical activation level, which is crucial for motor function rehabilitation.Approach.The current stimuli were delivered transcutaneously at the muscle belly of the finger flexors and the proximal segment of the median and ulnar nerves, respectively for the MP and PN stimulation. The stimulation intensity was determined to elicit the same contraction levels between the two stimulation methods in 18 healthy individuals and a stroke patient. The functional near-infrared spectroscopy and the electromyogram were recorded to compare the activation pattern of the sensorimotor regions and the target muscles.Main Results.For the healthy subjects, the PN stimulation induced significantly increased concentration of the oxygenated hemoglobin in the contralateral sensorimotor areas, and enhanced the functional connectivity between brain regions compared with the MP stimulation. Meanwhile, the compound action potentials had a smaller amplitude and the H-reflex became stronger under the PN stimulation, indicating that more sensory axons were activated in the PN stimulation. For the stroke patient, the PN stimulation can elicit finger forces and induce activation of both the contralateral and ipsilateral motor cortex.Conclusions. Compared with the MP stimulation, the PN stimulation can induce more cortical activation in the contralateral sensorimotor areas possibly via involving more activities in the central pathway.Significance.This study demonstrated the potential of the PN stimulation to facilitate functional recovery via increasing the cortical activation level, which may help to improve the outcome of the NMES-based rehabilitation for motor function recovery after stroke.

Connecting the dots: Motor and default mode network crossroads in post-stroke motor learning deficits

BACKGROUND

Strokes frequently result in long-term motor deficits, imposing significant personal and economic burdens. However, our understanding of the underlying neural mechanisms governing motor learning in stroke survivors remains limited - a fact that poses significant challenges to the development and optimisation of therapeutic strategies.

OBJECTIVE

This study investigates the diversity in motor learning aptitude and its associated neurological mechanisms. We hypothesised that stroke patients exhibit compromised overall motor learning capacity, which is associated with altered activity and connectivity patterns in the motor- and default-mode-network in the brain.

METHODS

We assessed a cohort of 40 chronic-stage, mildly impaired stroke survivors and 39 age-matched healthy controls using functional Magnetic Resonance Imaging (fMRI) and connectivity analyses. We focused on neural activity and connectivity patterns during an unilateral motor sequence learning task performed with the unimpaired or non-dominant hand. Primary outcome measures included task-induced changes in neural activity and network connectivity.

RESULTS

Compared to controls, stroke patients showed significantly reduced motor learning capacity, associated with diminished cerebral lateralization. Task induced activity modulation was reduced in the motor network but increased in the default mode network. The modulated activation strength was associated with an opposing trend in task-induced functional connectivity, with increased connectivity in the motor network and decreased connectivity in the DMN.

CONCLUSIONS

Stroke patients demonstrate altered neural activity and connectivity patterns during motor learning with their unaffected hand, potentially contributing to globally impaired motor learning skills. The reduced ability to lateralize cerebral activation, along with the enhanced connectivity between the right and left motor cortices in these patients, may signify maladaptive neural processes that impede motor adaptation, possibly affecting long-term rehabilitation post-stroke. The contrasting pattern of activity modulation and connectivity alteration in the default mode network suggests a nuanced role of this network in post-stroke motor learning. These insights could have significant implications for the development of customised rehabilitation strategies for stroke patients.

The effects of rTMS on motor recovery after stroke: a systematic review of fMRI studies

Repetitive transcranial magnetic stimulation (rTMS) has been widely used in motor rehabilitation after stroke, and functional magnetic resonance imaging (fMRI) has been used to investigate the neural mechanisms of motor recovery during stroke therapy. However, there is no review on the mechanism of rTMS intervention for motor recovery after stroke based on fMRI explicitly. We aim to reveal and summarize the neural mechanism of the effects of rTMS on motor function after stroke as measured by fMRI. We carefully performed a literature search using PubMed, EMBASE, Web of Science, and Cochrane Library databases from their respective inceptions to November 2022 to identify any relevant randomized controlled trials. Researchers independently screened the literature, extracted data, and qualitatively described the included studies. Eleven studies with a total of 420 poststroke patients were finally included in this systematic review. A total of 338 of those participants received fMRI examinations before and after rTMS intervention. Five studies reported the effects of rTMS on activation of brain regions, and four studies reported results related to brain functional connectivity (FC). Additionally, five studies analyzed the correlation between fMRI and motor evaluation. The neural mechanism of rTMS in improving motor function after stroke may be the activation and FCs of motor-related brain areas, including enhancement of the activation of motor-related brain areas in the affected hemisphere, inhibition of the activation of motor-related brain areas in the unaffected hemisphere, and changing the FCs of intra-hemispheric and inter-hemispheric motor networks.

Variation in brain connectivity during motor imagery and motor execution in stroke patients based on electroencephalography

Objective

The objective of this study was to analyze the changes in connectivity between motor imagery (MI) and motor execution (ME) in the premotor area (PMA) and primary motor cortex (MA) of the brain, aiming to explore suitable forms of treatment and potential therapeutic targets.

Methods

Twenty-three inpatients with stroke were selected, and 21 right-handed healthy individuals were recruited. EEG signal during hand MI and ME (synergy and isolated movements) was recorded. Correlations between functional brain areas during MI and ME were compared.

Results

PMA and MA were significantly and positively correlated during hand MI in all participants. The power spectral density (PSD) values of PMA EEG signals were greater than those of MA during MI and ME in both groups. The functional connectivity correlation was higher in the stroke group than in healthy people during MI, especially during left-handed MI. During ME, functional connectivity correlation in the brain was more enhanced during synergy movements than during isolated movements. The regions with abnormal functional connectivity were in the 18th lead of the left PMA area.

Conclusion

Left-handed MI may be crucial in MI therapy, and the 18th lead may serve as a target for non-invasive neuromodulation to promote further recovery of limb function in patients with stroke. This may provide support for the EEG theory of neuromodulation therapy for hemiplegic patients.

Uncovering the Neural Mechanisms of Inter-Hemispheric Balance Restoration in Chronic Stroke Through EMG-Driven Robot Hand Training: Insights From Dynamic Causal Modeling

EMG-driven robot hand training can facilitate motor recovery in chronic stroke patients by restoring the interhemispheric balance between motor networks. However, the underlying mechanisms of reorganization between interhemispheric regions remain unclear. This study investigated the effective connectivity (EC) between the ventral premotor cortex (PMv), supplementary motor area (SMA), and primary motor cortex (M1) using Dynamic Causal Modeling (DCM) during motor tasks with the paretic hand. Nineteen chronic stroke subjects underwent 20 sessions of EMG-driven robot hand training, and their Action Reach Arm Test (ARAT) showed significant improvement ( β =3.56, [Formula: see text]). The improvement was correlated with the reduction of inhibitory coupling from the contralesional M1 to the ipsilesional M1 (r=0.58, p=0.014). An increase in the laterality index was only observed in homotopic M1, but not in the premotor area. Additionally, we identified an increase in resting-state functional connectivity (FC) between bilateral M1 ( β =0.11, p=0.01). Inter-M1 FC demonstrated marginal positive relationships with ARAT scores (r=0.402, p=0.110), but its changes did not correlate with ARAT improvements. These findings suggest that the improvement of hand functions brought about by EMG-driven robot hand training was driven explicitly by task-specific reorganization of motor networks. Particularly, the restoration of interhemispheric balance was induced by a reduction in interhemispheric inhibition from the contralesional M1 during motor tasks of the paretic hand. This finding sheds light on the mechanistic understanding of interhemispheric balance and functional recovery induced by EMG-driven robot training.

Disrupted Effective Connectivity within the Fronto-Thalamic Circuit in Pontine Infarction: A Spectral Dynamic Causal Modeling Study

This study aims to investigate alterations in effective connectivity (EC) within the fronto-thalamic circuit and their associations with motor and cognitive declines in pontine infarction (PI). A total of 33 right PI patients (RPIs), 38 left PI patients (LPIs), and 67 healthy controls (HCs) were recruited. The spectral dynamic causal modeling (spDCM) approach was used for EC analysis within the fronto-thalamic circuit, including the thalamus, caudate, supplementary motor area (SMA), medial prefrontal cortex (mPFC), and anterior cingulate cortex (ACC). The EC differences between different sides of the patients and HCs were assessed, and their correlations with motor and cognitive dysfunctions were analyzed. The LPIs showed increased EC from the mPFC to the R-SMA and decreased EC from the L-thalamus to the ACC, the L-SMA to the R-SMA, the R-caudate to the R-thalamus, and the R-thalamus to the ACC. For RPIs, the EC of the R-caudate to the mPFC, the L-thalamus and L-caudate to the L-SMA, and the L-caudate to the ACC increased obviously, while a lower EC strength was shown from the L-thalamus to the mPFC, the LSMA to the R-caudate, and the R-SMA to the L-thalamus. The EC from the R-caudate to the mPFC was negatively correlated with the MoCA score for RPIs, and the EC from the R-caudate to the R-thalamus was negatively correlated with the FMA score for LPIs. The results demonstrated EC within the fronto-thalamic circuit in PI-related functional impairments and reveal its potential as a novel imaging marker.

Interhemispheric Structural Connectivity Underlies Motor Recovery after Stroke

OBJECTIVE

Although ample evidence highlights that the ipsilesional corticospinal tract (CST) plays a crucial role in motor recovery after stroke, studies on cortico-cortical motor connections remain scarce and provide inconclusive results. Given their unique potential to serve as structural reserve enabling motor network reorganization, the question arises whether cortico-cortical connections may facilitate motor control depending on CST damage.

METHODS

Diffusion spectrum imaging (DSI) and a novel compartment-wise analysis approach were used to quantify structural connectivity between bilateral cortical core motor regions in chronic stroke patients. Basal and complex motor control were differentially assessed.

RESULTS

Both basal and complex motor performance were correlated with structural connectivity between bilateral premotor areas and ipsilesional primary motor cortex (M1) as well as interhemispheric M1 to M1 connectivity. Whereas complex motor skills depended on CST integrity, a strong association between M1 to M1 connectivity and basal motor control was observed independent of CST integrity especially in patients who underwent substantial motor recovery. Harnessing the informational wealth of cortico-cortical connectivity facilitated the explanation of both basal and complex motor control.

INTERPRETATION

We demonstrate for the first time that distinct aspects of cortical structural reserve enable basal and complex motor control after stroke. In particular, recovery of basal motor control may be supported via an alternative route through contralesional M1 and non-crossing fibers of the contralesional CST. Our findings help to explain previous conflicting interpretations regarding the functional role of the contralesional M1 and highlight the potential of cortico-cortical structural connectivity as a future biomarker for motor recovery post-stroke. ANN NEUROL 2023;94:785-797.

Altered habenular connectivity in chronic low back pain: An fMRI and machine learning study

The habenula has been implicated in the pathogenesis of pain and analgesia, while evidence concerning its function in chronic low back pain (cLBP) is sparse. This study aims to investigate the resting-state functional connectivity (rsFC) and effective connectivity of the habenula in 52 patients with cLBP and 52 healthy controls (HCs) and assess the feasibility of distinguishing cLBP from HCs based on connectivity by machine learning methods. Our results indicated significantly enhanced rsFC of the habenula-left superior frontal cortex (SFC), habenula-right thalamus, and habenula-bilateral insular pathways as well as decreased rsFC of the habenula-pons pathway in cLBP patients compared to HCs. Dynamic causal modelling revealed significantly enhanced effective connectivity from the right thalamus to right habenula in cLBP patients compared with HCs. RsFC of the habenula-SFC was positively correlated with pain intensities and Hamilton Depression scores in the cLBP group. RsFC of the habenula-right insula was negatively correlated with pain duration in the cLBP group. Additionally, the combination of the rsFC of the habenula-SFC, habenula-thalamus, and habenula-pons pathways could reliably distinguish cLBP patients from HCs with an accuracy of 75.9% by support vector machine, which was validated in an independent cohort (N = 68, accuracy = 68.8%, p = .001). Linear regression and random forest could also distinguish cLBP and HCs in the independent cohort (accuracy = 73.9 and 55.9%, respectively). Overall, these findings provide evidence that cLBP may be associated with abnormal rsFC and effective connectivity of the habenula, and highlight the promise of machine learning in chronic pain discrimination.

Recombination of the right cerebral cortex in patients with left side USN after stroke: fNIRS evidence from resting state

Objective

Unilateral spatial neglect (USN) is an impaired contralesional stimulus detection, response, or action, causing functional disability. After a stroke, the right hemisphere experiences USN more noticeably, severely, and persistently than the left. However, few studies using fNIRS have been reported in cases of USN. This study aimed to confirm weaker RSFC in USN and investigate the potential inherent features in hemodynamic fluctuations that may be associated with USN. Furthermore, these features were combined into a mathematical model for more accurate classification.

Methods

A total of 33 stroke patients with right-sided brain damage were chosen, of whom 12 had non-USN after stroke, and 21 had USN after stroke (the USN group). Graph theory was used to evaluate the hemodynamic signals of the brain's right cerebral cortex during rest. Furthermore, a support vector machine model was built to categorize the subjects into two groups based on the chosen network properties.

Results

First, mean functional connectivity was lower in the USN group (0.745 ± 0.239) than in the non-USN group (0.843 ± 0.254) (t = -4.300, p < 0.001). Second, compared with the non-USN group, USN patients had a larger clustering coefficient (C) (t = 3.145, p < 0.001), local efficiency (LE) (t = 3.189, p < 0.001), and smaller global efficiency (GE) (t = 3.047, p < 0.001). Notably, there were differences in characteristic path length (L) and small worldness (σ) values between the two groups at certain thresholds, mainly as higher L (t = 3.074, p < 0.001) and lower small worldness (σ) values (t = 2.998, p < 0.001) in USN patients compared with non-USN patients. Finally, the classification accuracy of the SVM model based on AUC aC (t = -2.259, p = 0.031) and AUC aLE (t = -2.063, p = 0.048) was 85%, the sensitivity was 75%, and the specificity was 89%.

Conclusion

The functional network architecture of the right cerebral cortex exhibits significant topological alterations in individuals with USN following stroke, and the sensitivity index based on the small-world property AUC may be utilized to identify these patients accurately.

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.

Characterising stationary and dynamic effective connectivity changes in the motor network during and after tDCS

The exact mechanisms behind the effects of transcranial direct current stimulation (tDCS) at a network level are still poorly understood, with most studies to date focusing on local (cortical) effects and changes in motor-evoked potentials or BOLD signal. Here, we explored stationary and dynamic effective connectivity across the motor network at rest in two experiments where we applied tDCS over the primary motor cortex (M1-tDCS) or the cerebellum (cb-tDCS) respectively. Two cohorts of healthy volunteers (n = 21 and n = 22) received anodal, cathodal, and sham tDCS sessions (counterbalanced) during 20 min of resting-state functional magnetic resonance imaging (fMRI). We used spectral Dynamic Causal Modelling (DCM) and hierarchical Parametrical Empirical Bayes (PEB) to analyze data after (compared to a pre-tDCS baseline) and during stimulation. We also implemented a novel dynamic (sliding windows) DCM/PEB approach to model the nature of network reorganisation across time. In both experiments we found widespread effects of tDCS that extended beyond the targeted area and modulated effective connectivity between cortex, thalamus, and cerebellum. These changes were characterised by unique nonlinear temporal fingerprints across connections and polarities. Our results support growing research challenging the classic notion of anodal and cathodal tDCS as excitatory and inhibitory respectively, as well as the idea of a cumulative effect of tDCS over time. Instead, they described a rich set of changes with specific spatial and temporal patterns. Our work provides a starting point for advancing our understanding of network-level tDCS effects and may guide future work to optimise its cognitive and clinical applications.

Predicting poststroke dyskinesia with resting-state functional connectivity in the motor network

SIGNIFICANCE

Motor function evaluation is essential for poststroke dyskinesia rehabilitation. Neuroimaging techniques combined with machine learning help decode a patient's functional status. However, more research is needed to investigate how individual brain function information predicts the dyskinesia degree of stroke patients.

AIM

We investigated stroke patients' motor network reorganization and proposed a machine learning-based method to predict the patients' motor dysfunction.

APPROACH

Near-infrared spectroscopy (NIRS) was used to measure hemodynamic signals of the motor cortex in the resting state (RS) from 11 healthy subjects and 31 stroke patients, 15 with mild dyskinesia (Mild), and 16 with moderate-to-severe dyskinesia (MtS). The graph theory was used to analyze the motor network characteristics.

RESULTS

The small-world properties of the motor network were significantly different between groups: (1) clustering coefficient, local efficiency, and transitivity: MtS > Mild > Healthy and (2) global efficiency: MtS < Mild < Healthy. These four properties linearly correlated with patients' Fugl-Meyer Assessment scores. Using the small-world properties as features, we constructed support vector machine (SVM) models that classified the three groups of subjects with an accuracy of 85.7%.

CONCLUSIONS

Our results show that NIRS, RS functional connectivity, and SVM together constitute an effective method for assessing the poststroke dyskinesia degree at the individual level.

The role of corticospinal and extrapyramidal pathways in motor impairment after stroke

Anisotropy of descending motor pathways has repeatedly been linked to the severity of motor impairment following stroke-related damage to the corticospinal tract. Despite promising findings consistently tying anisotropy of the ipsilesional corticospinal tract to motor outcome, anisotropy is not yet utilized as a biomarker for motor recovery in clinical practice as several methodological constraints hinder a conclusive understanding of degenerative processes in the ipsilesional corticospinal tract and compensatory roles of other descending motor pathways. These constraints include estimating anisotropy in voxels with multiple fibre directions, sampling biases and confounds due to ageing-related atrophy. The present study addressed these issues by combining diffusion spectrum imaging with a novel compartmentwise analysis approach differentiating voxels with one dominant fibre direction (one-directional voxels) from voxels with multiple fibre directions. Compartmentwise anisotropy for bihemispheric corticospinal and extrapyramidal tracts was compared between 25 chronic stroke patients, 22 healthy age-matched controls, and 24 healthy young controls and its associations with motor performance of the upper and lower limbs were assessed. Our results provide direct evidence for Wallerian degeneration along the entire length of the ipsilesional corticospinal tract reflected by decreased anisotropy in descending fibres compared with age-matched controls, while ageing-related atrophy was observed more ubiquitously across compartments. Anisotropy of descending ipsilesional corticospinal tract voxels showed highly robust correlations with various aspects of upper and lower limb motor impairment, highlighting the behavioural relevance of Wallerian degeneration. Moreover, anisotropy measures of two-directional voxels within bihemispheric rubrospinal and reticulospinal tracts were linked to lower limb deficits, while anisotropy of two-directional contralesional rubrospinal voxels explained gross motor performance of the affected hand. Of note, the relevant extrapyramidal structures contained fibres crossing the midline, fibres potentially mitigating output from brain stem nuclei, and fibres transferring signals between the extrapyramidal system and the cerebellum. Thus, specific parts of extrapyramidal pathways seem to compensate for impaired gross arm and leg movements incurred through stroke-related corticospinal tract lesions, while fine motor control of the paretic hand critically relies on ipsilesional corticospinal tract integrity. Importantly, our findings suggest that the extrapyramidal system may serve as a compensatory structural reserve independent of post-stroke reorganization of extrapyramidal tracts. In summary, compartment-specific anisotropy of ipsilesional corticospinal tract and extrapyramidal tracts explained distinct aspects of motor impairment, with both systems representing different pathophysiological mechanisms contributing to motor control post-stroke. Considering both systems in concert may help to develop diffusion imaging biomarkers for specific motor functions after stroke.

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.

Contralaterally controlled neuromuscular electrical stimulation-induced changes in functional connectivity in patients with stroke assessed using functional near-infrared spectroscopy

Contralaterally controlled neuromuscular electrical stimulation (CCNMES) is an innovative therapy in stroke rehabilitation which has been verified in clinical studies. However, the underlying mechanism of CCNMES are yet to be comprehensively revealed. The main purpose of this study was to apply functional near-infrared spectroscopy (fNIRS) to compare CCNMES-related changes in functional connectivity (FC) within a cortical network after stroke with those induced by neuromuscular electrical stimulation (NMES) when performing wrist extension with hemiplegic upper extremity. Thirty-one stroke patients with right hemisphere lesion were randomly assigned to CCNMES (n = 16) or NMES (n = 15) groups. Patients in both groups received two tasks: 10-min rest and 10-min electrical stimulation task. In each task, the cerebral oxygenation signals in the prefrontal cortex (PFC), bilateral primary motor cortex (M1), and primary sensory cortex (S1) were measured by a 35-channel fNIRS. Compared with NMES, FC between ipsilesional M1 and contralesional M1/S1 were significantly strengthened during CCNMES. Additionally, significantly higher coupling strengths between ipsilesional PFC and contralesional M1/S1 were observed in the CCNMES group. Our findings suggest that CCNMES promotes the regulatory functions of ipsilesional prefrontal and motor areas as well as contralesional sensorimotor areas within the functional network in patients with stroke.

Reorganization of prefrontal network in stroke patients with dyskinesias: evidence from resting-state functional near-infrared spectroscopy

Stroke usually causes multiple functional disability. To develop novel rehabilitation strategies, it is quite necessary to improve the understanding of post-stroke brain plasticity. Here, we use functional near-infrared spectroscopy to investigate the prefrontal cortex (PFC) network reorganization in stroke patients with dyskinesias. The PFC hemodynamic signals in the resting state from 16 stroke patients and 10 healthy subjects are collected and analyzed with the graph theory. The PFC networks for both groups show small-world attributes. The stroke patients have larger clustering coefficient and transitivity and smaller global efficiency and small-worldness than healthy subjects. Based on the selected network features, the established support vector machine model classifies the two groups of subjects with an accuracy rate of 88.5%. Besides, the clustering coefficient and local efficiency negatively correlate with patients' motor function. This study suggests that the PFC of stroke patients with dyskinesias undergoes specific network reorganization.

Not Only in Sensorimotor Network: Local and Distant Cerebral Inherent Activity of Chronic Ankle Instability—A Resting-State fMRI Study

Background

Increasing evidence has proved that chronic ankle instability (CAI) is highly related to the central nervous system (CNS). However, it is still unclear about the inherent cerebral activity among the CAI patients.

Purpose

To investigate the differences of intrinsic functional cerebral activity between the CAI patients and healthy controls (HCs) and further explore its correlation with clinical measurement in CAI patients.

Materials and Methods

A total of 25 CAI patients and 39 HCs were enrolled in this study. Resting-state functional magnetic resonance imaging (rs-fMRI) was used to detect spontaneous cerebral activity. The metrics of amplitude of low-frequency fluctuation (ALFF), fractional ALFF (fALFF), and regional homogeneity (ReHo) of the two groups were compared by two-sample t-test. The brain regions that demonstrated altered functional metrics were selected as the regions of interest (ROIs). The functional connectivity (FC) was analyzed based on the ROIs. The Spearman correlation was calculated between rs-fMRI metrics and clinical scale scores.

Results

Compared with HCs, CAI patients showed higher ALFF and ReHo values in the right postcentral gyrus, the right precentral gyrus, and the right middle frontal gyrus, while lower fALFF values in the orbital-frontal cortex (OFC, p &lt; 0.01 after correction). Increasing FC between the right precentral gyrus and the right postcentral gyrus while decreasing FC between the right precentral gyrus and the anterior cingulum cortex (ACC), the right middle frontal gyrus and the left middle temporal gyrus, and the OFC and left inferior parietal lobule (IPL) was observed. In addition, in the CAI group, the ReHo value negatively correlated with the Cumberland Ankle Instability Tool score in the right middle frontal gyrus (r = −0.52, p = 0.007).

Conclusion

The CAI patients exhibited enhanced and more coherent regional inherent neuronal activity within the sensorimotor network while lower regional inherent activity in pain/emotion modulation related region. In addition, the information exchanges were stronger within the sensorimotor network while weaker between distant interhemispheric regions. Besides, the increased inherent activity in the right middle frontal gyrus was related to clinical severity. These findings may provide insights into the pathophysiological alteration in CNS among CAI patients.

Altered Amygdala-prefrontal Connectivity in Chronic Nonspecific Low Back Pain: Resting-state fMRI and Dynamic Causal Modelling Study

Chronic nonspecific low back pain (cNLBP) is a leading contributor to disease burden worldwide that is difficult to treat due to its nonspecific aetiology and complexity. The amygdala is a complex of structurally and functionally heterogeneous nuclei that serve as a key neural substrate for the interactions between pain and negative affective states. However, whether the functions of amygdalar subcomponents are differentially altered in cNLBP remains unknown. Little attention has focused on effective connectivity of the amygdala with the cortex in cNLBP. In this study, thirty-three patients with cNLBP and 33 healthy controls (HCs) were included. Resting-state functional connectivity (rsFC) and effective connectivity of the amygdala and its subregions were examined. Our results showed that the patient group exhibited significantly greater rsFC between the left amygdala and left dorsal medial prefrontal cortex (mPFC), which was negatively correlated with pain intensity ratings. Subregional analyses suggested a difference located at the superficial nuclei of the amygdala. Dynamic causal modelling revealed significantly lower effective connectivity from the left amygdala to the dorsal mPFC in patients with cNLBP than in HCs. Both groups exhibited stronger effective connectivity from the left amygdala to the right amygdala. In summary, these findings not only suggested altered rsFC of the amygdala-mPFC pathway in cNLBP but also implicated an abnormal direction of information processing between the amygdala and mPFC in these patients. Our results further highlight the involvement of the amygdala in the neuropathology of cNLBP.