Stronger prediction of motor recovery and outcome post-stroke by cortico-spinal tract integrity than functional connectivity

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.

Diffusion tensor imaging and gray matter volumetry to evaluate cerebral remodeling processes after a pure motor stroke: a longitudinal study

BACKGROUND AND OBJECTIVES

Clinical factors are not sufficient to fix a prognosis of recovery after stroke. Pyramidal tract or alternate motor fiber (aMF: reticulo-, rubrospinal pathways and transcallosal fibers) integrity and remodeling processes assessable by diffusion tensor MRI (DTI) and voxel-based morphometry (VBM) may be of interest. The primary objective was to study longitudinal cortical brain changes using VBM and longitudinal corticospinal tract changes using DTI during the first 4 months after lacunar cerebral infarction. The second objective was to determine which changes were correlated to clinical improvement.

METHODS

Twenty-one patients with deep brain ischemic infarct with pure motor deficit (NIHSS score ≥ 2) were recruited at Purpan Hospital and included. Motor deficit was measured [Nine peg hole test (NPHT), dynamometer (DYN), Hand-Tapping Test (HTT)], and a 3T MRI scan (VBM and DTI) was performed during the acute and subacute phases.

RESULTS

White matter changes: corticospinal fractional anisotropy (FACST) was significantly reduced at follow-up (approximately 4 months) on the lesion side. FAr (FA ratio in affected/unaffected hemispheres) in the corona radiata was correlated to the motor performance at the NPHT, DYN, and HTT at follow-up. The presence of aMFs was not associated with the extent of recovery. Grey matter changes: VBM showed significant increased cortical thickness in the ipsilesional premotor cortex at follow-up. VBM changes in the anterior cingulum positively correlated with improvement in motor measures between baseline and follow-up.

DISCUSSION

To our knowledge, this study is original because is a longitudinal study combining VBM and DTI during the first 4 months after stroke in a series of patients selected on pure motor deficit. Our data would suggest that good recovery relies on spared CST fibers, probably from the premotor cortex, rather than on the aMF in this group with mild motor deficit. The present study suggests that VBM and FACST could provide reliable biomarkers of post-stroke atrophy, reorganization, plasticity and recovery.

CLINICALTRIALS

GOV IDENTIFIER

NCT01862172, registered May 24, 2013.

Brain-Hand Function Relationships Based on Level of Grasp Function in Chronic Left-Hemisphere Stroke

BACKGROUND AND OBJECTIVE

The biomarkers of hand function may differ based on level of motor impairment after stroke. The objective of this study was to determine the relationship between resting state functional connectivity (RsFC) and unimanual contralesional hand function after stroke and whether brain-behavior relationships differ based on level of grasp function.

METHODS

Sixty-two individuals with chronic, left-hemisphere stroke were separated into three functional levels based on Box and Blocks Test performance with the contralesional hand: Low (moved 0 blocks), Moderate (moved >0% but <90% of blocks relative to the ipsilesional hand), and High (moved ≥90% of blocks relative to the ipsilesional hand).

RESULTS

RsFC in the ipsilesional and interhemispheric motor networks was reduced in the Low group compared to the Moderate and High groups. While interhemispheric RsFC correlated with hand function (grip strength and Stroke Impact Scale Hand) across the sample, contralesional RsFC correlated with hand function in the Low group and no measures of connectivity correlated with hand function in the Moderate and High groups. Linear regression modeling found that contralesional RsFC significantly predicted hand function in the Low group, while no measure correlated with hand function in the High group. Corticospinal tract integrity was the only predictor of hand function for the Moderate group and in an analysis across the entire sample.

CONCLUSIONS

Differences in brain-hand function relationships based on level of motor impairment may have implications for predictive models of treatment response and the development of intervention protocols aimed at improving hand function after stroke.

Mapping stroke outcomes: A review of brain connectivity atlases

The brain connectivity-based atlas is a promising tool for understanding neural communication pathways in the brain, gaining relevance in predicting personalized outcomes for various brain pathologies. This critical review examines the robustness of the brain connectivity-based atlas for predicting post-stroke outcomes. A comprehensive literature search was conducted from 2012 to May 2023 across PubMed, Scopus, EMBASE, EBSCOhost, and Medline databases. Twenty-one studies were screened, and through analysis of these studies, we identified 18 brain connectivity atlases employed by the studies for lesion analysis in their predictions. The brain atlases were assessed for study cohorts, connectivity measures, identified brain regions, atlas applications, and limitations. Based on the analysis of these studies, most atlases were based on diffusion tensor imaging and resting-state functional magnetic resonance imaging (MRI). Studies predicting post-stroke functional outcomes relied on the atlases for multivariate lesion analysis and region of interest identification, often employing atlases derived from young, healthy populations. Current brain connectivity-based atlases for stroke applications lack standardized methods to define and map brain connectivity across atlases and cover sensorimotor functional connectivity to a limited extent. In conclusion, this review highlights the need to develop more comprehensive, robust, and adaptable brain connectivity-based atlases specifically tailored to post-stroke populations.

Neuroimaging of motor recovery after ischemic stroke - functional reorganization of motor network

The long-term motor outcome of acute stroke patients may be correlated to the reorganization of brain motor network. Abundant neuroimaging studies contribute to understand the pathological changes and recovery of motor networks after stroke. In this review, we summarized how current neuroimaging studies have increased understanding of reorganization and plasticity in post stroke motor recovery. Firstly, we discussed the changes in the motor network over time during the motor-activation and resting states, as well as the overall functional integration trend of the motor network. These studies indicate that the motor network undergoes dynamic bilateral hemispheric functional reorganization, as well as a trend towards network randomization. In the second part, we summarized the current study progress in the application of neuroimaging technology to early predict the post-stroke motor outcome. In the third part, we discuss the neuroimaging techniques commonly used in the post-stroke recovery. These methods provide direct or indirect visualization patterns to understand the neural mechanisms of post-stroke motor recovery, opening up new avenues for studying spontaneous and treatment-induced recovery and plasticity after stroke.

Adaptation in the spinal cord after stroke: Implications for restoring cortical control over the final common pathway

Control of voluntary movement is predicated on integration between circuits in the brain and spinal cord. Although damage is often restricted to supraspinal or spinal circuits in cases of neurological injury, both spinal motor neurons and axons linking these cells to the cortical origins of descending motor commands begin showing changes soon after the brain is injured by stroke. The concept of 'transneuronal degeneration' is not new and has been documented in histological, imaging and electrophysiological studies dating back over a century. Taken together, evidence from these studies agrees more with a system attempting to survive rather than one passively surrendering to degeneration. There tends to be at least some preservation of fibres at the brainstem origin and along the spinal course of the descending white matter tracts, even in severe cases. Myelin-associated proteins are observed in the spinal cord years after stroke onset. Spinal motor neurons remain morphometrically unaltered. Skeletal muscle fibres once innervated by neurons that lose their source of trophic input receive collaterals from adjacent neurons, causing spinal motor units to consolidate and increase in size. Although some level of excitability within the distributed brain network mediating voluntary movement is needed to facilitate recovery, minimal structural connectivity between cortical and spinal motor neurons can support meaningful distal limb function. Restoring access to the final common pathway via the descending input that remains in the spinal cord therefore represents a viable target for directed plasticity, particularly in light of recent advances in rehabilitation medicine.

A Comprehensive Review on the Role of Resting-State Functional Magnetic Resonance Imaging in Predicting Post-Stroke Motor and Sensory Outcomes

Stroke is a major leading cause of chronic disability, often affecting patients' motor and sensory functions. Functional magnetic resonance imaging (fMRI) is the most commonly used method of functional neuroimaging, and it allows for the non-invasive study of brain activity. The time-dependent coactivation of different brain regions at rest is described as resting-state activation. As a non-invasive task-independent functional neuroimaging approach, resting-state fMRI (rs-fMRI) may provide therapeutically useful information on both the focal vascular lesion and the connectivity-based reorganization and subsequent functional recovery in stroke patients. Considering the role of a prompt and accurate prognosis in stroke survivors along with the potential of rs-fMRI in identifying patterns of neuroplasticity in different post-stroke phases, this review provides a comprehensive overview of the latest literature regarding the role of rs-fMRI in stroke prognosis in terms of motor and sensory outcomes. Our comprehensive review suggests that with the advancement of MRI acquisition and data analysis methods, rs-fMRI emerges as a promising tool to study the motor and sensory outcomes in stroke patients and evaluate the effects of different interventions.

Adaptation of the Concept of Brain Reserve for the Prediction of Stroke Outcome: Proxies, Neural Mechanisms, and Significance for Research

The prediction of stroke outcome is challenging due to the high inter-individual variability in stroke patients. We recently suggested the adaptation of the concept of brain reserve (BR) to improve the prediction of stroke outcome. This concept was initially developed alongside the one for the cognitive reserve for neurodegeneration and forms a valuable theoretical framework to capture high inter-individual variability in stroke patients. In the present work, we suggest and discuss (i) BR-proxies-quantitative brain characteristics at the time stroke occurs (e.g., brain volume, hippocampus volume), and (ii) proxies of brain pathology reducing BR (e.g., brain atrophy, severity of white matter hyperintensities), parameters easily available from a routine MRI examination that might improve the prediction of stroke outcome. Though the influence of these parameters on stroke outcome has been partly reported individually, their independent and combined impact is yet to be determined. Conceptually, BR is a continuous measure determining the amount of brain structure available to mitigate and compensate for stroke damage, thus reflecting individual differences in neural resources and a capacity to maintain performance and recover after stroke. We suggest that stroke outcome might be defined as an interaction between BR at the time stroke occurs and lesion load. BR in stroke can potentially be influenced, e.g., by modifying cardiovascular risk factors. In addition to the potential power of the BR concept in a mechanistic understanding of inter-individual variability in stroke outcome and establishing individualized therapeutic approaches, it might help to strengthen the synergy of preventive measures in stroke, neurodegeneration, and healthy aging.

Against cortical reorganisation

Neurological insults, such as congenital blindness, deafness, amputation, and stroke, often result in surprising and impressive behavioural changes. Cortical reorganisation, which refers to preserved brain tissue taking on a new functional role, is often invoked to account for these behavioural changes. Here, we revisit many of the classical animal and patient cortical remapping studies that spawned this notion of reorganisation. We highlight empirical, methodological, and conceptual problems that call this notion into doubt. We argue that appeal to the idea of reorganisation is attributable in part to the way that cortical maps are empirically derived. Specifically, cortical maps are often defined based on oversimplified assumptions of 'winner-takes-all', which in turn leads to an erroneous interpretation of what it means when these maps appear to change. Conceptually, remapping is interpreted as a circuit receiving novel input and processing it in a way unrelated to its original function. This implies that neurons are either pluripotent enough to change what they are tuned to or that a circuit can change what it computes. Instead of reorganisation, we argue that remapping is more likely to occur due to potentiation of pre-existing architecture that already has the requisite representational and computational capacity pre-injury. This architecture can be facilitated via Hebbian and homeostatic plasticity mechanisms. Crucially, our revised framework proposes that opportunities for functional change are constrained throughout the lifespan by the underlying structural 'blueprint'. At no period, including early in development, does the cortex offer structural opportunities for functional pluripotency. We conclude that reorganisation as a distinct form of cortical plasticity, ubiquitously evoked with words such as 'take-over'' and 'rewiring', does not exist.

Do kinematic measures, added to clinical measures, better predict upper extremity motor impairments at three months post-stroke?

OBJECTIVE

Predicting post-stroke recovery through prediction models is crucial for choosing appropriate treatment options. However, the existing models predominantly incorporate clinical measures although measurement of movement quality using kinematic measures is essential for distinguishing various types of recovery. Thus, this study aimed at determining if, by considering varied aspects of recovery, adding kinematic measurements over clinical measures would better predict upper extremity (UE) motor impairments at three months post-stroke.

MATERIALS AND METHODS

Eighty-nine stroke survivors (58.9 ± 11.8 years) were assessed for clinical predictors between 4 and 7 days, kinematic predictors within 1 month, and the impairment outcome of the Fugl Meyer Assessment of the UE (FM-UE) at three months post-stroke. Significant predictors (p<0.05) with a variation inflation factor (VIF) <10 were selected for model development. After performing further step-wise selection, three models incorporating clinical outcomes, kinematic measurements, and a combination of these two, respectively, were formulated.

RESULTS

The clinical model (R2 = 0.70) included shoulder abduction finger extension (SAFE) scores, the National Institutes of Health Stroke Scale (NIHSS), and the Montreal Cognitive Assessment (MoCA). The kinematic model (R2 = 0.34) included total displacement, total time, and reaction time. The combined model (R2 = 0.72) comprised of SAFE score and shoulder flexion. All the models had a minimal mean squared error on cross validation, which indicated a good validity.

CONCLUSION

The performance of clinical and combined prediction models for predicting three-month post-stroke UE motor recovery was nearly similar. However, in order to detect minimal changes over time and to understand all aspects of motor recovery, there is a need to add instrument-based kinematic measures.

Clinical, Neuroimaging and Robotic Measures Predict Long-Term Proprioceptive Impairments following Stroke

Proprioceptive impairments occur in ~50% of stroke survivors, with 20-40% still impaired six months post-stroke. Early identification of those likely to have persistent impairments is key to personalizing rehabilitation strategies and reducing long-term proprioceptive impairments. In this study, clinical, neuroimaging and robotic measures were used to predict proprioceptive impairments at six months post-stroke on a robotic assessment of proprioception. Clinical assessments, neuroimaging, and a robotic arm position matching (APM) task were performed for 133 stroke participants two weeks post-stroke (12.4 ± 8.4 days). The APM task was also performed six months post-stroke (191.2 ± 18.0 days). Robotics allow more precise measurements of proprioception than clinical assessments. Consequently, an overall APM Task Score was used as ground truth to classify proprioceptive impairments at six months post-stroke. Other APM performance parameters from the two-week assessment were used as predictive features. Clinical assessments included the Thumb Localisation Test (TLT), Behavioural Inattention Test (BIT), Functional Independence Measure (FIM) and demographic information (age, sex and affected arm). Logistic regression classifiers were trained to predict proprioceptive impairments at six months post-stroke using data collected two weeks post-stroke. Models containing robotic features, either alone or in conjunction with clinical and neuroimaging features, had a greater area under the curve (AUC) and lower Akaike Information Criterion (AIC) than models which only contained clinical or neuroimaging features. All models performed similarly with regard to accuracy and F1-score (>70% accuracy). Robotic features were also among the most important when all features were combined into a single model. Predicting long-term proprioceptive impairments, using data collected as early as two weeks post-stroke, is feasible. Identifying those at risk of long-term impairments is an important step towards improving proprioceptive rehabilitation after a stroke.

Predictive Factors and Interventional Modalities of Post-stroke Motor Recovery: An Overview

Stroke is the most common cause of motor impairment worldwide. Therefore, many factors are being investigated for their predictive and facilitatory effects on recovery of motor function after stroke. Motor recovery can be predicted through several factors, such as clinical assessment, clinical biomarkers, and gene-based variations. As for interventions, many methods are under experimental investigation that aim to improve motor recovery, including different types of pharmacological interventions, non-invasive stimulation, and rehabilitation training by inducing cortical reorganization, neuroplasticity, angiogenesis, changing the levels of neurotransmitters in the brain, and altering the inflammatory and apoptotic processes occurring after stroke. Studies have shown that clinical biomarkers combined with clinical assessment and gene-based variations are reliable factors for predicting motor recovery after stroke. Moreover, different types of interventions such as pharmacological agents (selective serotonin reuptake inhibitors {SSRI}, noradrenaline reuptake inhibitors {NARIs}, levodopa, and amphetamine), non-invasive stimulation, and rehabilitation training have shown significant results in improving functional and motor recovery.

Connectomics underlying motor functional outcomes in the acute period following stroke

Objective

Stroke remains the number one cause of morbidity in many developing countries, and while effective neurorehabilitation strategies exist, it remains difficult to predict the individual trajectories of patients in the acute period, making personalized therapies difficult. Sophisticated and data-driven methods are necessary to identify markers of functional outcomes.

Methods

Baseline anatomical T1 magnetic resonance imaging (MRI), resting-state functional MRI (rsfMRI), and diffusion weighted scans were obtained from 79 patients following stroke. Sixteen models were constructed to predict performance across six tests of motor impairment, spasticity, and activities of daily living, using either whole-brain structural or functional connectivity. Feature importance analysis was also performed to identify brain regions and networks associated with performance in each test.

Results

The area under the receiver operating characteristic curve ranged from 0.650 to 0.868. Models utilizing functional connectivity tended to have better performance than those utilizing structural connectivity. The Dorsal and Ventral Attention Networks were among the top three features in several structural and functional models, while the Language and Accessory Language Networks were most commonly implicated in structural models.

Conclusions

Our study highlights the potential of machine learning methods combined with connectivity analysis in predicting outcomes in neurorehabilitation and disentangling the neural correlates of functional impairments, though further longitudinal studies are necessary.

Multimodal and multidomain lesion network mapping enhances prediction of sensorimotor behavior in stroke patients

Beyond the characteristics of a brain lesion, such as its etiology, size or location, lesion network mapping (LNM) has shown that similar symptoms after a lesion reflects similar dis-connectivity patterns, thereby linking symptoms to brain networks. Here, we extend LNM by using a multimodal strategy, combining functional and structural networks from 1000 healthy participants in the Human Connectome Project. We apply multimodal LNM to a cohort of 54 stroke patients with the aim of predicting sensorimotor behavior, as assessed through a combination of motor and sensory tests. Results are two-fold. First, multimodal LNM reveals that the functional modality contributes more than the structural one in the prediction of sensorimotor behavior. Second, when looking at each modality individually, the performance of the structural networks strongly depended on whether sensorimotor performance was corrected for lesion size, thereby eliminating the effect that larger lesions generally produce more severe sensorimotor impairment. In contrast, functional networks provided similar performance regardless of whether or not the effect of lesion size was removed. Overall, these results support the extension of LNM to its multimodal form, highlighting the synergistic and additive nature of different types of network modalities, and their corresponding influence on behavioral performance after brain injury.

Recovery of neural dynamics criticality in personalized whole-brain models of stroke

The critical brain hypothesis states that biological neuronal networks, because of their structural and functional architecture, work near phase transitions for optimal response to internal and external inputs. Criticality thus provides optimal function and behavioral capabilities. We test this hypothesis by examining the influence of brain injury (strokes) on the criticality of neural dynamics estimated at the level of single participants using directly measured individual structural connectomes and whole-brain models. Lesions engender a sub-critical state that recovers over time in parallel with behavior. The improvement of criticality is associated with the re-modeling of specific white-matter connections. We show that personalized whole-brain dynamical models poised at criticality track neural dynamics, alteration post-stroke, and behavior at the level of single participants.

Functional connectivity drives stroke recovery: shifting the paradigm from correlation to causation

Stroke is a leading cause of disability, with deficits encompassing multiple functional domains. The heterogeneity underlying stroke poses significant challenges in the prediction of post-stroke recovery, prompting the development of neuroimaging-based biomarkers. Structural neuroimaging measurements, particularly those reflecting corticospinal tract injury, are well-documented in the literature as potential biomarker candidates of post-stroke motor recovery. Consistent with the view of stroke as a 'circuitopathy', functional neuroimaging measures probing functional connectivity may also prove informative in post-stroke recovery. An important step in the development of biomarkers based on functional neural network connectivity is the establishment of causality between connectivity and post-stroke recovery. Current evidence predominantly involves statistical correlations between connectivity measures and post-stroke behavioural status, either cross-sectionally or serially over time. However, the advancement of functional connectivity application in stroke depends on devising experiments that infer causality. In 1965, Sir Austin Bradford Hill introduced nine viewpoints to consider when determining the causality of an association: (i) strength; (ii) consistency; (iii) specificity; (iv) temporality; (v) biological gradient; (vi) plausibility; (vii) coherence; (viii) experiment; and (ix) analogy. Collectively referred to as the Bradford Hill Criteria, these points have been widely adopted in epidemiology. In this review, we assert the value of implementing Bradford Hill's framework to stroke rehabilitation and neuroimaging. We focus on the role of neural network connectivity measurements acquired from task-oriented and resting-state functional MRI, EEG, magnetoencephalography and functional near-infrared spectroscopy in describing and predicting post-stroke behavioural status and recovery. We also identify research opportunities within each Bradford Hill tenet to shift the experimental paradigm from correlation to causation.

Relationship Between Body-Specific Attention to a Paretic Limb and Real-World Arm Use in Stroke Patients: A Longitudinal Study

Learned nonuse is a major problem in upper limb (UL) rehabilitation after stroke. Among the various factors that contribute to learned nonuse, recent studies have focused on body representation of the paretic limb in the brain. We previously developed a method to measure body-specific attention, as a marker of body representation of the paretic limb and revealed a decline in body-specific attention to the paretic limb in chronic stroke patients by a cross-sectional study. However, longitudinal changes in body-specific attention and paretic arm use in daily life (real-world arm use) from the onset to the chronic phase, and their relationship, remain unknown. Here, in a longitudinal, prospective, observational study, we sought to elucidate the longitudinal changes in body-specific attention to the paretic limb and real-world arm use, and their relationship, by using accelerometers and psychophysical methods, respectively, in 25 patients with subacute stroke. Measurements were taken at baseline (TBL), 2 weeks (T2w), 1 month (T1M), 2 months (T2M), and 6 months (T6M) after enrollment. UL function was measured using the Fugl-Meyer Assessment (FMA) and Action Research Arm Test (ARAT). Real-world arm use was measured using accelerometers on both wrists. Body-specific attention was measured using a visual detection task. The UL function and real-world arm use improved up to T6M. Longitudinal changes in body-specific attention were most remarkable at T1M. Changes in body-specific attention up to T1M correlated positively with changes in real-world arm use up to T6M, and from T1M to T6M, and the latter more strongly correlated with changes in real-world arm use. Changes in real-world arm use up to T2M correlated positively with changes in FMA up to T2M and T6M. No correlation was found between body-specific attention and FMA scores. Thus, these results suggest that improved body-specific attention to the paretic limb during the early phase contributes to increasing long-term real-world arm use and that increased real-world use is associated with the recovery of UL function. Our results may contribute to the development of rehabilitation strategies to enhance adaptive changes in body representation in the brain and increase real-world arm use after stroke.

No evidence for motor recovery-related cortical connectivity changes after stroke using resting-state fMRI

It has been proposed that a form of cortical reorganization (changes in functional connectivity between brain areas) can be assessed with resting-state (rs) fMRI. Here we report a longitudinal data-set collected from 19 patients with subcortical stroke and 11 controls. Patients were imaged up to five times over one year. We found no evidence, using rs-fMRI, for post-stroke cortical connectivity changes despite substantial behavioral recovery. These results could be construed as questioning the value of resting-state imaging. Here we argue instead that they are consistent with other emerging reasons to challenge the idea of motor recovery-related cortical reorganization post-stroke when conceived of as changes in connectivity between cortical areas.

Connectivity Measures Differentiate Cortical and Subcortical Sub-Acute Ischemic Stroke Patients

Brain lesions caused by cerebral ischemia lead to network disturbances in both hemispheres, causing a subsequent reorganization of functional connectivity both locally and remotely with respect to the injury. Quantitative electroencephalography (qEEG) methods have long been used for exploring brain electrical activity and functional connectivity modifications after stroke. However, results obtained so far are not univocal. Here, we used basic and advanced EEG methods to characterize how brain activity and functional connectivity change after stroke. Thirty-three unilateral post stroke patients in the sub-acute phase and ten neurologically intact age-matched right-handed subjects were enrolled. Patients were subdivided into two groups based on lesion location: cortico-subcortical (CS, n = 18) and subcortical (S, n = 15), respectively. Stroke patients were evaluated in the period ranging from 45 days since the acute event (T0) up to 3 months after stroke (T1) with both neurophysiological (resting state EEG) and clinical assessment (Barthel Index, BI) measures, while healthy subjects were evaluated once. Brain power at T0 was similar between the two groups of patients in all frequency bands considered (δ, θ, α, and β). However, evolution of θ-band power over time was different, with a normalization only in the CS group. Instead, average connectivity and specific network measures (Integration, Segregation, and Small-worldness) in the β-band at T0 were significantly different between the two groups. The connectivity and network measures at T0 also appear to have a predictive role in functional recovery (BI T1-T0), again group-dependent. The results obtained in this study showed that connectivity measures and correlations between EEG features and recovery depend on lesion location. These data, if confirmed in further studies, on the one hand could explain the heterogeneity of results so far observed in previous studies, on the other hand they could be used by researchers as biomarkers predicting spontaneous recovery, to select homogenous groups of patients for the inclusion in clinical trials.

White matter integrity of contralesional and transcallosal tracts may predict response to upper limb task-specific training in chronic stroke

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Increase in upper limb function post task specific training in chronic stroke.

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Motor improvements were not accompanied by changes in white matter integrity.

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Integrity in contralesional fibers predicted larger motor recovery in Responders.

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Non-responders had more severe damage of transcallosal fibers than Responders.

Objective

To investigate white matter (WM) plasticity induced by intensive upper limb (UL) task specific training (TST) in chronic stroke.

Methods

Diffusion tensor imaging data and UL function measured by the Action Research Arm Test (ARAT) were collected in 30 individuals with chronic stroke prior to and after intensive TST. ANOVAs tested the effects of training on the entire sample and on the Responders [ΔARAT ≥ 5.8, N = 13] and Non-Responders [ΔARAT < 5.8, N = 17] groups. Baseline fractional anisotropy (FA) values were correlated with ARATpost TST controlling for baseline ARAT and age to identify voxels predictive of response to TST. Results.

While ARAT scores increased following training (p < 0.0001), FA changes within major WM tracts were not significant at p < 0.05. In the Responder group, larger baseline FA of both contralesional (CL) and transcallosal tracts predicted larger ARAT scores post-TST. Subcortical lesions and more severe damage to transcallosal tracts were more pronounced in the Non-Responder than in the Responder group.

Conclusions

The motor improvements post-TST in the Responder group may reflect the engagement of interhemispheric processes not available to the Non-Responder group. Future studies should clarify differences in the role of CL and transcallosal pathways as biomarkers of recovery in response to training for individuals with cortical and subcortical stroke. This knowledge may help to identify sources of heterogeneity in stroke recovery, which is necessary for the development of customized rehabilitation interventions.

Comparing cortico-motor hotspot identification methods in the lower extremities post-stroke: MEP amplitude vs. latency

Transcranial magnetic stimulation (TMS) is a technique used to probe and measure cortico-motor responses of the nervous system. However, lower extremity (LE) specific methodology has been slow to develop. In this retrospective analysis, we investigated what motor evoked potential metric, amplitude (MEP_amp) or latency (MEP_lat), best distinguished the motor-cortical target, i.e. hotspot, of the tibialis anterior and soleus post-stroke. Twenty-three participants with stroke were included in this investigation. Neuronavigation was used to map hotspots, derived via MEP_amp and MEP_lat, over a 3cm × 5cm grid. Distances between points with the greatest response within a session and between days were compared. Both criterion, amplitude and latency, provided poor identification of locations between trials within a session, and between multiple visits. Identified hotspots were similar only 15 % and 8% of the time between two assessments within the same session, for amplitude and latency respectively. However, MEP_amp was more consistent in identifying hotspots, evidenced by locations being less spatially distant from each other (Amplitude: 1.4 cm (SD 0.10) Latency: 1.7 (SD 1.04), P = 0.008) within a session and between days (Amplitude: 1.3 cm (SD 0.95), Latency 1.9 cm (SD 1.14), P = 0.004). While more work is needed to develop LE specific methodology for TMS, especially as it applies to investigating gait impairments, MEP_amp appears to be a more consistent criterion for hotspot identification when compared to MEP_lat. It is recommended that future works continue to use MEP_amp when identifying tibialis anterior and soleus hotspots using neuronavigation.

Sensorimotor, Attentional, and Neuroanatomical Predictors of Upper Limb Motor Deficits and Rehabilitation Outcome after Stroke

The rehabilitation of motor deficits following stroke relies on both sensorimotor and cognitive abilities, thereby involving large-scale brain networks. However, few studies have investigated the integration between motor and cognitive domains, as well as its neuroanatomical basis. In this retrospective study, upper limb motor responsiveness to technology-based rehabilitation was examined in a sample of 29 stroke patients (18 with right and 11 with left brain damage). Pretreatment sensorimotor and attentional abilities were found to influence motor recovery. Training responsiveness increased as a function of the severity of motor deficits, whereas spared attentional abilities, especially visuospatial attention, supported motor improvements. Neuroanatomical analysis of structural lesions and white matter disconnections showed that the poststroke motor performance was associated with putamen, insula, corticospinal tract, and frontoparietal connectivity. Motor rehabilitation outcome was mainly associated with the superior longitudinal fasciculus and partial involvement of the corpus callosum. The latter findings support the hypothesis that motor recovery engages large-scale brain networks that involve cognitive abilities and provides insight into stroke rehabilitation strategies.

A connectome-based approach to assess motor outcome after neonatal arterial ischemic stroke

Objective

Studies of motor outcome after Neonatal Arterial Ischemic Stroke (NAIS) often rely on lesion mapping using MRI. However, clinical measurements indicate that motor deficit can be different than what would solely be anticipated by the lesion extent and location. Because this may be explained by the cortical disconnections between motor areas due to necrosis following the stroke, the investigation of the motor network can help in the understanding of visual inspection and outcome discrepancy. In this study, we propose to examine the structural connectivity between motor areas in NAIS patients compared to healthy controls in order to define the cortical and subcortical connections that can reflect the motor outcome.

Methods

Thirty healthy controls and 32 NAIS patients with and without Cerebral Palsy (CP) underwent MRI acquisition and manual assessment. The connectome of all participants was obtained from T1‐weighted and diffusion‐weighted imaging.

Results

Significant disconnections in the lesioned and contra‐lesioned hemispheres of patients were found. Furthermore, significant correlations were detected between the structural connectivity metric of specific motor areas and manuality assessed by the Box and Block Test (BBT) scores in patients.

Interpretation

Using the connectivity measures of these links, the BBT score can be estimated using a multiple linear regression model. In addition, the presence or not of CP can also be predicted using the KNN classification algorithm. According to our results, the structural connectome can be an asset in the estimation of gross manual dexterity and can help uncover structural changes between brain regions related to NAIS.

Lesion Quantification Toolkit: A MATLAB software tool for estimating grey matter damage and white matter disconnections in patients with focal brain lesions

Lesion studies are an important tool for cognitive neuroscientists and neurologists. However, while brain lesion studies have traditionally aimed to localize neurological symptoms to specific anatomical loci, a growing body of evidence indicates that neurological diseases such as stroke are best conceptualized as brain network disorders. While researchers in the fields of neuroscience and neurology are therefore increasingly interested in quantifying the effects of focal brain lesions on the white matter connections that form the brain's structural connectome, few dedicated tools exist to facilitate this endeavor. Here, we present the Lesion Quantification Toolkit, a publicly available MATLAB software package for quantifying the structural impacts of focal brain lesions. The Lesion Quantification Toolkit uses atlas-based approaches to estimate parcel-level grey matter lesion loads and multiple measures of white matter disconnection severity that include tract-level disconnection measures, voxel-wise disconnection maps, and parcel-wise disconnection matrices. The toolkit also estimates lesion-induced increases in the lengths of the shortest structural paths between parcel pairs, which provide information about changes in higher-order structural network topology. We describe in detail each of the different measures produced by the toolkit, discuss their applications and considerations relevant to their use, and perform example analyses using real behavioral data collected from sub-acute stroke patients. We show that analyses performed using the different measures produced by the toolkit produce results that are highly consistent with results that have been reported in the prior literature, and we demonstrate the consistency of results obtained from analyses conducted using the different disconnection measures produced by the toolkit. We anticipate that the Lesion Quantification Toolkit will empower researchers to address research questions that would be difficult or impossible to address using traditional lesion analyses alone, and ultimately, lead to advances in our understanding of how white matter disconnections contribute to the cognitive, behavioral, and physiological consequences of focal brain lesions.

Dynamic Structural and Functional Reorganizations Following Motor Stroke

Background

The combined effects of bilateral corticospinal tract (CST) reorganization and interhemispheric functional connectivity (FC) reorganization on motor recovery of upper and lower limbs after stroke remain unknown.

Material/Methods

A total of 34 patients underwent magnetic resonance imaging (MRI) examination at weeks 1, 4, and 12 after stroke, with a control group of 34 healthy subjects receiving 1 MRI examination. Interhemispheric FC in the somatomotor network (SMN) was calculated using the resting-state functional MRI (rs-fMRI). Fractional anisotropy (FA) of bilateral CST was recorded as a measure of reorganization obtained from diffusion tensor imaging (DTI). After intergroup comparisons, multiple linear regression analysis was used to explore the effects of altered FA and interhemispheric FC on motor recovery.

Results

Interhemispheric FC restoration mostly occurred within 4 weeks after stroke, and FA in ipsilesional remained CST consistently elevated within 12 weeks. Multivariate linear regression analysis showed that the increase in both interhemispheric FC and ipsilesional CST-FA were significantly correlated with greater motor recovery from week 1 to week 4 following stroke. Moreover, only increased FA of ipsilesional CST was significantly correlated with greater motor recovery during weeks 4 to 12 after stroke compared to interhemispheric FC.

Conclusions

Our results show dynamic structural and functional reorganizations following motor stroke, and structure reorganization may be more related to motor recovery at the late subacute phase. These results may play a role in guiding neurological rehabilitation.

Kinematic Measures of Bimanual Performance are Associated With Callosum White Matter Change in People With Chronic Stroke

Objectives

To investigate the relationship between bimanual performance deficits measured using kinematics and callosum (CC) white matter changes that occur in people with chronic stroke.

Design

Cross-sectional, observational study of participants with chronic stroke and age-matched controls.

Setting

Recruitment and assessments occurred at a stroke recovery research center. Behavioral assessments were performed in a controlled laboratory setting. Magnetic resonance imaging scans were performed at the Center for Biomedical Imaging.

Participants

Individuals were enrolled and completed the study (N=39; 21 participants with chronic stroke; 18 age-matched controls with at least 2 stroke risk factors).

Main Outcome Measures

Diffusion imaging metrics were obtained for each individual’s CC and corticospinal tract (CST), including mean kurtosis (MK) and fractional anisotropy (FA). A battery of motor assessments, including bimanual kinematics, were collected from individuals while performing bimanual reaching.

Results

Participants with stroke had lower FA and MK in the CST of the lesioned hemisphere when compared with the non-lesioned hemisphere. The FA and MK values in the CST were correlated with measures of unimanual hand performance. In addition, participants with stroke had significantly lower FA and MK in the CC than matched controls. CC diffusion metrics positively correlated with hand asymmetry and trunk displacement during bimanual performance, even when correcting for age and lesion volume.

Conclusions

These data confirm previous studies that linked CST integrity to unimanual performance and provide new data demonstrating a link between CC integrity and both bimanual motor deficits and compensatory movements.

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Fractional anisotropy and mean kurtosis in the corpus callosum are lower in participants with stroke.

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Hand position symmetry and trunk displacement are disrupted during bimanual tasks.

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Corpus callosum white matter correlated with bimanual kinematics in participants with stroke.

Outcome prediction in patients with putaminal hemorrhage at admission to a convalescent rehabilitation ward based on hemorrhage volume assessed with computed tomography during acute care

[Purpose] The aim of this study was to assess the usefulness of computed tomography for outcome prediction in patients with putaminal hemorrhage at admission to a convalescent rehabilitation ward. [Participants and Methods] Patients admitted to our convalescent rehabilitation ward after transfer from acute care hospitals were included in this study. Multiple regression analyses were performed using the score in the motor component of the Functional Independence Measure at discharge as the target value. Hemorrhage volume assessed with computed tomography during acute care and age were set as the explanatory variables. The motor component of the Functional Independence Measure score at admission and the time (days) from onset were also recorded. Correlation analyses between all the possible pairs of explanatory variables were then performed. [Results] Hemorrhage volume and age were both significant contributors to the motor component of the Functional Independence Measure score at discharge. However, the contribution of hemorrhage volume disappeared when the time from onset and motor component of the Functional Independence Measure score at admission were added. Hemorrhage volume significantly correlated with the time from onset and motor component of the Functional Independence Measure score at admission. [Conclusion] The present findings suggest that computed tomography may be useful for outcome prediction from the acute stage in stroke patients with putaminal hemorrhage. However, because of multicollinearity, its predictive power was reduced when the patients were transferred to a convalescent rehabilitation ward.

Corticospinal Fibers With Different Origins Impact Motor Outcome and Brain After Subcortical Stroke

BACKGROUND AND PURPOSE

Motor deficit is the most common disability after stroke, and early prediction of motor outcome is critical for early interventions. Here, we constructed a fine map of the corticospinal tract (CST) for early prediction of motor outcome and for understanding the secondary brain changes after subcortical stroke.

METHODS

Diffusion spectrum imaging data from 50 healthy adults were used to reconstruct fine maps of CST with different origins, including primary motor area (M1), primary sensory area (S1), premotor cortex, and supplementary motor area (SMA). Their diffusion properties correlated with motor functions in healthy adults. The impacts of the impairments of different CST on motor outcomes and on structural and functional changes of brain were investigated in 136 patients with subcortical stroke by combining CST damage-symptom association study and voxel-based lesion-symptom mapping.

RESULTS

In healthy adults, the isotropy of M1 fiber correlated with walking endurance and that of SMA fiber with motor dexterity. In chronic stroke patients, the integrity of M1 and SMA fibers showed the most significant correlation with motor deficits. The percentage of early damage of M1 and SMA fibers correlated with that of chronic motor deficits. Voxel-based lesion-symptom mapping revealed that acute stroke lesions in the bilateral M1 and right SMA fibers were associated with chronic motor deficits. The early damage of M1 fiber negatively correlated with the integrity of M1-M1 fiber, and the early damage of SMA fiber negatively correlated with gray matter volume of the contralateral cerebellum in the chronic stage.

CONCLUSIONS

The CST that originated from the M1 and SMA are closely associated with motor outcomes and brain structural changes, and the fine maps of CST from these 2 cortical areas are useful in assessing and predicting long-term motor outcome in patients with subcortical stroke.

Resting State Functional Connectivity Is Associated With Motor Pathway Integrity and Upper-Limb Behavior in Chronic Stroke

Background. Resting state functional connectivity (RSFC) is a developmental priority for stroke recovery. Objective. To determine whether (1) RSFC differs between stroke survivors based on integrity of descending motor pathways; (2) RSFC is associated with upper-limb behavior in chronic stroke; and (3) the relationship between interhemispheric RSFC and upper-limb behavior differs based on descending motor pathway integrity. Methods. A total of 36 people with stroke (aged 64.4 ± 11.1 years, time since stroke 4.0 ± 2.8 years) and 25 healthy adults (aged 67.3 ± 6.7 years) participated in this study. RSFC was estimated from electroencephalography (EEG) recordings. Integrity of descending motor pathways was ascertained using transcranial magnetic stimulation to determine motor-evoked potential (MEP) status and magnetic resonance imaging to determine lesion overlap and fractional anisotropy of the corticospinal tract (CST). For stroke participants, upper-limb motor behavior was assessed using the Fugl-Meyer test, Action Research Arm Test and grip strength. Results. β-Frequency interhemispheric sensorimotor RSFC was greater for MEP+ stroke participants compared with MEP- (P = .020). There was a significant positive correlation between β RSFC and upper-limb behavior (P = .004) that appeared to be primarily driven by the MEP+ group. A hierarchical regression identified that the addition of β RSFC to measures of CST integrity explained greater variance in upper-limb behavior (R² change = 0.13; P = .01). Conclusions. This study provides insight to understand the role of EEG-based measures of interhemispheric network activity in chronic stroke. Resting state interhemispheric connectivity was positively associated with upper-limb behavior for stroke survivors where residual integrity of descending motor pathways was maintained.

Prediction of Motor Recovery in Patients with Basal Ganglia Hemorrhage Using Diffusion Tensor Imaging

Predicting prognosis in patients with basal ganglia hemorrhage is difficult. This study aimed to investigate the usefulness of diffusion tensor imaging in predicting motor outcome after basal ganglia hemorrhage. A total of 12 patients with putaminal hemorrhage were included in the study (aged 50 ± 12 years), 8 patients were male (aged 46 ± 11 years) and 4 were female (aged 59 ± 9 years). We performed diffusion tensor imaging and measured clinical outcome at baseline (pre) and 3 weeks (post1), 3 months (post2), and 6 months (post3) after the initial treatment. In the affected side of the brain, the mean fractional anisotropy (FA) value on pons was significantly higher in the good outcome group than that in the poor outcome group at pre (p = 0.004) and post3 (p = 0.025). Pearson correlation analysis showed that mean FA value at pre significantly correlated with the sum of the Brunnstrom motor recovery stage scores at post3 (R = 0.8, p = 0.002). Change in the FA ratio on diffusion tractography can predict motor recovery after hemorrhagic stroke.

Advanced Neurotechnologies for the Restoration of Motor Function

Stroke is one of the leading causes of long-term disability. Advanced technological solutions ("neurotechnologies") exploiting robotic systems and electrodes that stimulate the nervous system can increase the efficacy of stroke rehabilitation. Recent studies on these approaches have shown promising results. However, a paradigm shift in the development of new approaches must be made to significantly improve the clinical outcomes of neurotechnologies compared with those of traditional therapies. An "evolutionary" change can occur only by understanding in great detail the basic mechanisms of natural stroke recovery and technology-assisted neurorehabilitation. In this review, we first describe the results achieved by existing neurotechnologies and highlight their current limitations. In parallel, we summarize the data available on the mechanisms of recovery from electrophysiological, behavioral, and anatomical studies in humans and rodent models. Finally, we propose new approaches for the effective use of neurotechnologies in stroke survivors, as well as in people with other neurological disorders.

Estimation of Motor Impairment and Usage of Upper Extremities during Daily Living Activities in Poststroke Hemiparesis Patients by Observation of Time Required to Accomplish Hand Dexterity Tasks

Aim. This study evaluated whether specific actual performance could accurately predict body function levels and upper limb use in the real-life functioning of poststroke hemiparesis patients to aid in choosing the most appropriate rehabilitation exercises. Methods. We measured the time taken for poststroke patients to move small objects with the paralyzed hand and investigated how the measurement could estimate upper extremity motor impairment and hand usage during activities of daily living (ADL). We examined 86 stroke patients (age 66 ± 16 years) whose upper extremity motor paralysis was measured using the Fugl-Meyer assessment (FMA) and Southampton Hand Assessment Procedure (SHAP), and patient-reported ADL was investigated using the Jikei Assessment Scale for Motor Impairment in Daily Living (JASMID). To identify the time required to perform each SHAP item, we employed a linear regression analysis. The prediction formula was used in the linear regression analysis, and the coefficient of determination (R2) was applied to compare each component item score that was obtained with the predicted values derived from the linear regression analysis. Results. The most easily accomplished task was Heavy Power in the SHAP. The R2 between the SHAP Heavy Power item score and the FMA scores was moderate (R2 = 0.344, P<0.0001), whereas the R2 with the JASMID score was low (R2 = 0.126, P<0.001). Conclusions. By measuring the time it takes for poststroke hemiparesis patients to hold and move an object, we developed a prediction formula for upper extremity motor function and hand dexterity.

Structural and functional reorganization following unilateral internal capsule infarction contribute to neurological function recovery

PURPOSE

To investigate proliferative reorganization in the bilateral corticospinal tract (CST) and functional reorganization in the sensorimotor network (SMN) after internal capsule stroke, and to examine the significance of this reorganization.

METHODS

We recruited 17 patients with first-onset acute stroke (16 male, 1 female, mean age 52 ± 10 years) and 17 age- and sex-matched healthy controls. We excluded patients aged < 18 or > 65 years and those with lesions outside the unilateral internal capsule. All subjects underwent diffusion tensor imaging and resting-state functional MRI on days 7, 30, and 90 from symptom onset. We measured fractional anisotropy (FA) in the CST, interhemispheric functional connectivity (FC) within the SMN, and pre-MRI clinical scores, including the National Institutes of Health Stroke Scale (NIHSS), Barthel Index (BI), and Fugl-Meyer (FM). Correlations among the changes in FA, FC, and clinical scores were analyzed.

RESULTS

From day 7 to 90 after stroke, FA in the bilateral CST increased (ipsilesional side, Pinternal capsule = 0.009, Pcentrum semiovale = 0.001; contralesional side, Pinternal capsule = 0.006, Pcentrum semiovale = 0.017), as did FC (P < 0.05); NIHSS scores decreased (P < 0.05), while FM and BI progressively increased (P < 0.05). Increased FA in bilateral CST was negatively correlated with decreased NIHSS scores. Increased FA in only the ipsilesional side was positively correlated with increased FM. Increased FC was positively correlated only with increased BI.

CONCLUSION

Proliferative reorganization in the CST and functional reorganization in the SMN support and promote neurological functional recovery after internal capsule infarction.