Factors affecting post-stroke motor recovery: Implications on neurotherapy after brain injury.
Ontology highlight
ABSTRACT:
SUBMITTER: Alawieh A
PROVIDER: S-EPMC5305670 | biostudies-literature | 2018 Mar
REPOSITORIES: biostudies-literature
Publications
Factors affecting post-stroke motor recovery: Implications on neurotherapy after brain injury.
Alawieh Ali A Zhao Jing J Feng Wuwei W
Behavioural brain research 20160813
Neurological disorders are a major cause of chronic disability globally among which stroke is a leading cause of chronic disability. The advances in the medical management of stroke patients over the past decade have significantly reduced mortality, but at the same time increased numbers of disabled survivors. Unfortunately, this reduction in mortality was not paralleled by satisfactory therapeutics and rehabilitation strategies that can improve functional recovery of patients. Motor recovery af ...[more]
Similar Datasets
Project description:Gait recovery is an important goal in stroke patients. Several studies have sought to uncover relationships between specific brain lesions and the recovery of gait, but the effects of specific brain lesions on gait remain unclear. Thus, we investigated the effects of stroke lesions on gait recovery in stroke patients.In total, 30 subjects with stroke were assessed in a retrograde longitudinal observational study. To assess gait function, the functional ambulation category (FAC) was tested four times: initially (within 2 weeks) and 1, 3, and 6 months after the onset of the stroke. Brain lesions were analyzed via overlap, subtraction, and voxel-based lesion symptom mapping (VLSM).Ambulation with FAC improved significantly with time. Subtraction analysis showed that involvement of the corona radiata, internal capsule, globus pallidus, and putamen were associated with poor recovery of gait throughout 6 months after onset. The caudate nucleus did influence poor recovery of gait at 6 months after onset. VLSM revealed that corona radiata, internal capsule, globus pallidus, putamen and cingulum were related with poor recovery of gait at 3 months after onset. Corona radiata, internal capsule, globus pallidus, putamen, primary motor cortex, and caudate nucleus were related with poor recovery of gait at 6 months after onset.Results identified several important brain lesions for gait recovery in patients with stroke. These results may be useful for planning rehabilitation strategies for gait and understanding the prognosis of gait in stroke patients.
| S-EPMC5698874 | biostudies-other
Project description:BACKGROUND:A large number of robotic or gravity-supporting devices have been developed for rehabilitation of upper extremity post-stroke. Because these devices continuously monitor performance data during training, they could potentially help to develop predictive models of the effects of motor training on recovery. However, during training with such devices, patients must become adept at using the new "tool" of the exoskeleton, including learning the new forces and visuomotor transformations associated with the device. We thus hypothesized that the changes in performance during extensive training with a passive, gravity-supporting, exoskeleton device (the Armeo Spring) will follow an initial fast phase, due to learning to use the device, and a slower phase that corresponds to reduction in overall arm impairment. Of interest was whether these fast and slow processes were related. METHODS:To test the two-process hypothesis, we used mixed-effect exponential models to identify putative fast and slow changes in smoothness of arm movements during 80 arm reaching tests performed during 20 days of exoskeleton training in 53 individuals with post-acute stroke. RESULTS:In line with our hypothesis, we found that double exponential models better fit the changes in smoothness of arm movements than single exponential models. In contrast, single exponential models better fit the data for a group of young healthy control subjects. In addition, in the stroke group, we showed that smoothness correlated with a measure of impairment (the upper extremity Fugl Meyer score - UEFM) at the end, but not at the beginning, of training. Furthermore, the improvement in movement smoothness due to the slow component, but not to the fast component, strongly correlated with the improvement in the UEFM between the beginning and end of training. There was no correlation between the change of peaks due to the fast process and the changes due to the slow process. Finally, the improvement in smoothness due to the slow, but not the fast, component correlated with the number of days since stroke at the onset of training - i.e. participants who started exoskeleton training sooner after stroke improved their smoothness more. CONCLUSIONS:Our results therefore demonstrate that at least two processes are involved in in performance improvements measured during mechanized training post-stroke. The fast process is consistent with learning to use the exoskeleton, while the slow process independently reflects the reduction in upper extremity impairment.
| S-EPMC6173922 | biostudies-literature
Project description:Thorough assessment of cerebral dysfunction after acute lesions is paramount to optimize predicting clinical outcomes. We here built random forest classifier-based prediction models of acute motor impairment and recovery post-stroke. Predictions relied on structural and resting-state fMRI data from 54 stroke patients scanned within the first days of symptom onset. Functional connectivity was estimated via static and dynamic approaches. Motor performance was phenotyped in the acute phase and 6 months later. A model based on the time spent in specific dynamic connectivity configurations achieved the best discrimination between patients with and without motor impairments (out-of-sample area under the curve, 95% confidence interval: 0.67 ± 0.01). In contrast, patients with moderate-to-severe impairments could be differentiated from patients with mild deficits using a model based on the variability of dynamic connectivity (0.83 ± 0.01). Here, the variability of the connectivity between ipsilesional sensorimotor cortex and putamen discriminated the most between patients. Finally, motor recovery was best predicted by the time spent in specific connectivity configurations (0.89 ± 0.01) in combination with the initial impairment. Here, better recovery was linked to a shorter time spent in a functionally integrated configuration. Dynamic connectivity-derived parameters constitute potent predictors of acute impairment and recovery, which, in the future, might inform personalized therapy regimens to promote stroke recovery.
| S-EPMC8578497 | biostudies-literature
Project description:ObjectiveMotor recovery after stroke depends on the integrity of ipsilesional motor circuits and interactions between the ipsilesional and contralesional hemispheres. In this sham-controlled randomized trial, we investigated whether noninvasive modulation of regional excitability of bilateral motor cortices in combination with physical and occupational therapy improves motor outcome after stroke.MethodsTwenty chronic stroke patients were randomly assigned to receive 5 consecutive sessions of either 1) bihemispheric transcranial direct current stimulation (tDCS) (anodal tDCS to upregulate excitability of ipsilesional motor cortex and cathodal tDCS to downregulate excitability of contralesional motor cortex) with simultaneous physical/occupational therapy or 2) sham stimulation with simultaneous physical/occupational therapy. Changes in motor impairment (Upper Extremity Fugl-Meyer) and motor activity (Wolf Motor Function Test) assessments were outcome measures while functional imaging parameters were used to identify neural correlates of motor improvement.ResultsThe improvement of motor function was significantly greater in the real stimulation group (20.7% in Fugl-Meyer and 19.1% in Wolf Motor Function Test scores) when compared to the sham group (3.2% in Fugl-Meyer and 6.0% in Wolf Motor Function Test scores). The effects outlasted the stimulation by at least 1 week. In the real-stimulation group, stronger activation of intact ipsilesional motor regions during paced movements of the affected limb were found postintervention whereas no significant activation changes were seen in the control group.ConclusionsThe combination of bihemispheric tDCS and peripheral sensorimotor activities improved motor functions in chronic stroke patients that outlasted the intervention period. This novel approach may potentiate cerebral adaptive processes that facilitate motor recovery after stroke.Classification of evidenceThis study provides Class I evidence that for adult patients with ischemic stroke treated at least 5 months after their first and only stroke, bihemispheric tDCS and simultaneous physical/occupational therapy given over 5 consecutive sessions significantly improves motor function as measured by the Upper Extremity Fugl-Meyer assessment (raw change treated 6.1 ± 3.4, sham 1.2 ± 1.0).
| S-EPMC3013585 | biostudies-literature
Project description:Clinical research based on neuroimaging data has benefited from machine learning methods, which have the ability to provide individualized predictions and to account for the interaction among units of information in the brain. Application of machine learning in structural imaging to investigate diseases that involve brain injury presents an additional challenge, especially in conditions like stroke, due to the high variability across patients regarding characteristics of the lesions. Extracting data from anatomical images in a way that translates brain damage information into features to be used as input to learning algorithms is still an open question. One of the most common approaches to capture regional information from brain injury is to obtain the lesion load per region (i.e. the proportion of voxels in anatomical structures that are considered to be damaged). However, no systematic evaluation has yet been performed to compare this approach with using patterns of voxels (i.e. considering each voxel as a single feature). In this paper we compared both approaches applying Gaussian Process Regression to decode motor scores in 50 chronic stroke patients based solely on data derived from structural MRI. For both approaches we compared different ways to delimit anatomical areas: regions of interest from an anatomical atlas, the corticospinal tract, a mask obtained from fMRI analysis with a motor task in healthy controls and regions selected using lesion-symptom mapping. Our analysis showed that extracting features through patterns of voxels that represent lesion probability produced better results than quantifying the lesion load per region. In particular, from the different ways to delimit anatomical areas compared, the best performance was obtained with a combination of a range of cortical and subcortical motor areas as well as the corticospinal tract. These results will inform the appropriate methodology for predicting long term motor outcomes from early post-stroke structural brain imaging.
| S-EPMC4995603 | biostudies-literature
Project description:Post-stroke depression (PSD) affects approximately one-third of stroke patients. PSD not only impairs recovery and lowers quality of life, but has also serious neurological consequences, high mortality, and stroke recurrence risks. Studies on PSD-related prognostic factors are still lacking, especially environmental factors. Moreover, relieving factors after PSD in stroke patients has not been reported. This study aimed to investigate (study design 1) risk factors for PSD diagnosis after three months, and (study design 2) related factors for the relieving of early PSD after three months. This retrospective study included 227 patients hospitalized for acute ischemic stroke within three days at Jeonbuk National University Hospital from January to December 2019. The depressive status was assessed using the Hamilton Depression Rating Scale (HDRS) at admission and after three months. Clinical and laboratory data were analyzed for relevant prognostic factors. (Study design 1) HDRS score at admission (adjusted odds ratio (aOR) 1.22, 95% confidence interval (CI) 1.14-1.31; p < 0.001) and hospitalization period (aOR 1.11, 95% CI 1.02-1.20; p = 0.013) were confirmed as prognostic factors of PSD after three months. (Study design 2) The National Institute of Health Stroke Scale (NIHSS) score at discharge (aOR 0.80, 95% CI 0.68-0.94; p = 0.006) and HDRS score at admission (aOR 0.80, 95% CI 0.71-0.89; p < 0.001) were confirmed as prognostic factors of depression improvement after three months. In conclusion, environmental factors such as hospitalization period could be important in managing PSD. Factors related to PSD improvement are expected to be helpful in establishing a strategy for PSD recovery.
| S-EPMC8618912 | biostudies-literature
Project description:Functional electrical stimulation (FES) can support functional restoration of a paretic limb post-stroke. Hebbian plasticity depends on temporally coinciding pre- and post-synaptic activity. A tight temporal relationship between motor cortical (MC) activity associated with attempted movement and FES-generated visuo-proprioceptive feedback is hypothesized to enhance motor recovery. Using a brain-computer interface (BCI) to classify MC spectral power in electroencephalographic (EEG) signals to trigger FES-delivery with detection of movement attempts improved motor outcomes in chronic stroke patients. We hypothesized that heightened neural plasticity earlier post-stroke would further enhance corticomuscular functional connectivity and motor recovery. We compared subcortical non-dominant hemisphere stroke patients in BCI-FES and Random-FES (FES temporally independent of MC movement attempt detection) groups. The primary outcome measure was the Fugl-Meyer Assessment, Upper Extremity (FMA-UE). We recorded high-density EEG and transcranial magnetic stimulation-induced motor evoked potentials before and after treatment. The BCI group showed greater: FMA-UE improvement; motor evoked potential amplitude; beta oscillatory power and long-range temporal correlation reduction over contralateral MC; and corticomuscular coherence with contralateral MC. These changes are consistent with enhanced post-stroke motor improvement when movement is synchronized with MC activity reflecting attempted movement.
| S-EPMC11319604 | biostudies-literature
Project description:BackgroundBiomarkers derived from neural activity of the brain present a vital tool for the prediction and evaluation of post-stroke motor recovery, as well as for real-time biofeedback opportunities.MethodsIn order to encapsulate recovery-related reorganization of brain networks into such biomarkers, we have utilized the generalized measure of association (GMA) and graph analyses, which include global and local efficiency, as well as hemispheric interdensity and intradensity. These methods were applied to electroencephalogram (EEG) data recorded during a study of 30 stroke survivors (21 male, mean age 57.9 years, mean stroke duration 22.4 months) undergoing 12 weeks of intensive therapeutic intervention.ResultsWe observed that decreases of the intradensity of the unaffected hemisphere are correlated (r s =-0.46;p<0.05) with functional recovery, as measured by the upper-extremity portion of the Fugl-Meyer Assessment (FMUE). In addition, high initial values of local efficiency predict greater improvement in FMUE (R 2=0.16;p<0.05). In a subset of 17 subjects possessing lesions of the cerebral cortex, reductions of global and local efficiency, as well as the intradensity of the unaffected hemisphere are found to be associated with functional improvement (r s =-0.60,-0.66,-0.75;p<0.05). Within the same subgroup, high initial values of global and local efficiency, are predictive of improved recovery (R 2=0.24,0.25;p<0.05). All significant findings were specific to the 12.5-25 Hz band.ConclusionsThese topological measures show promise for prognosis and evaluation of therapeutic outcomes, as well as potential application to BCI-enabled biofeedback.
| S-EPMC5501348 | biostudies-literature
Project description:Promoting the recovery of motor function and optimizing rehabilitation strategies for stroke patients is closely associated with the challenge of individual prediction. To date, stroke research has identified critical pathophysiological neural underpinnings at the cellular level as well as with regard to network reorganization. However, in order to generate reliable readouts at the level of individual patients and thereby realize translation from bench to bedside, we are still in a need for innovative methods. The combined use of transcranial magnetic stimulation (TMS) and EEG has proven powerful to record both local and network responses at an individual's level. To elucidate the potential of TMS-EEG to assess motor recovery after stroke, we used neuronavigated TMS-EEG over ipsilesional primary motor cortex (M1) in 28 stroke patients in the first days after stroke. Twenty-five of these patients were reassessed after >3 months post-stroke. In the early post-stroke phase (6.7 ± 2.5 days), the TMS-evoked EEG responses featured two markedly different response morphologies upon TMS to ipsilesional M1. In the first group of patients, TMS elicited a differentiated and sustained EEG response with a series of deflections sequentially involving both hemispheres. This response type resembled the patterns of bilateral activation as observed in the healthy comparison group. By contrast, in a subgroup of severely affected patients, TMS evoked a slow and simplified local response. Quantifying the TMS-EEG responses in the time and time-frequency domain revealed that stroke patients exhibited slower and simple responses with higher amplitudes compared to healthy controls. Importantly, these patterns of activity changes after stroke were not only linked to the initial motor deficit, but also to motor recovery after >3 months post-stroke. Thus, the data revealed a substantial impairment of local effects as well as causal interactions within the motor network early after stroke. Additionally, for severely affected patients with absent motor evoked potentials and identical clinical phenotype, TMS-EEG provided differential response patterns indicative of the individual potential for recovery of function. Thereby, TMS-EEG extends the methodological repertoire in stroke research by allowing the assessment of individual response profiles.
| S-EPMC7296846 | biostudies-literature
Project description:Background and Purpose- Injury to the corticospinal tract (CST) has been shown to have a major effect on upper extremity motor recovery after stroke. This study aimed to examine how well CST injury, measured from neuroimaging acquired during the acute stroke workup, predicts upper extremity motor recovery. Methods- Patients with upper extremity weakness after ischemic stroke were assessed using the upper extremity Fugl-Meyer during the acute stroke hospitalization and again at 3-month follow-up. CST injury was quantified and compared, using 4 different methods, from images obtained as part of the stroke standard-of-care workup. Logistic and linear regression were performed using CST injury to predict ΔFugl-Meyer. Injury to primary motor and premotor cortices were included as potential modifiers of the effect of CST injury on recovery. Results- N=48 patients were enrolled 4.2±2.7 days poststroke and completed 3-month follow-up (median 90-day modified Rankin Scale score, 3; interquartile range, 1.5). CST injury distinguished patients who reached their recovery potential (as predicted from initial impairment) from those who did not, with area under the curve values ranging from 0.70 to 0.8. In addition, CST injury explained ≈20% of the variance in the magnitude of upper extremity recovery, even after controlling for the severity of initial impairment. Results were consistent when comparing 4 different methods of measuring CST injury. Extent of injury to primary motor and premotor cortices did not significantly influence the predictive value that CST injury had for recovery. Conclusions- Structural injury to the CST, as estimated from standard-of-care imaging available during the acute stroke hospitalization, is a robust way to distinguish patients who achieve their predicted recovery potential and explains a significant amount of the variance in poststroke upper extremity motor recovery.
| S-EPMC6878199 | biostudies-literature