Altered functional networks of alpha and low-beta bands during upper limb movement and association with motor impairment in chronic stroke

Background. Stroke is a leading cause of adult disability owing largely to motor impairment and loss of function. After stroke, there may be abnormalities in γ-aminobutyric acid (GABA)-mediated inhibitory function within primary motor cortex (M1), which may have implications for residual motor impairment and the potential for functional improvements at the chronic stage. Objective. To quantify GABA neurotransmission and concentration within ipsilesional and contralesional M1 and determine if they relate to upper limb impairment and function at the chronic stage of stroke. Methods. Twelve chronic stroke patients and 16 age-similar controls were recruited for the study. Upper limb impairment and function were assessed with the Fugl-Meyer Upper Extremity Scale and Action Research Arm Test. Threshold tracking paired-pulse transcranial magnetic stimulation protocols were used to examine short- and long-interval intracortical inhibition and late cortical disinhibition. Magnetic resonance spectroscopy was used to evaluate GABA concentration. Results. Short-interval intracortical inhibition was similar between patients and controls ( P = .10). Long-interval intracortical inhibition was greater in ipsilesional M1 compared with controls ( P < .001). Patients who did not exhibit late cortical disinhibition in ipsilesional M1 were those with greater upper limb impairment and worse function ( P = .002 and P = .017). GABA concentration was lower within ipsilesional ( P = .009) and contralesional ( P = .021) M1 compared with controls, resulting in an elevated excitation-inhibition ratio for patients. Conclusion. These findings indicate that ipsilesional and contralesional M1 GABAergic inhibition are altered in this small cohort of chronic stroke patients. Further study is warranted to determine how M1 inhibitory networks might be targeted to improve motor function.

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Relationship Between Clinical Measures of Upper Limb Movement Quality and Activity Poststroke

Neurorehabilitation and Neural Repair ◽

10.1177/1545968319847969 ◽

2019 ◽

Vol 33 (6) ◽

pp. 432-441 ◽

Cited By ~ 1

Author(s):

Mindy F. Levin ◽

Vimonwan Hiengkaew ◽

Yongchai Nilanont ◽

Donna Cheung ◽

David Dai ◽

...

Keyword(s):

Upper Limb ◽

Controlled Trial ◽

Motor Impairment ◽

Limb Movement ◽

Reach To Grasp ◽

Cross Sectional ◽

Movement Quality ◽

Performance Time ◽

Multicenter Randomized Controlled Trial ◽

The Relationship

Background. Understanding the relationship between movement quality (impairment) and performance (activity) in poststroke patients is important for rehabilitation intervention studies. This has led to an interest in kinematic characterization of upper limb motor impairment. Since instrumented motion analysis is not readily clinically available, observational kinematics may be a viable alternative. Objective. To determine if upper limb movement quality during a reach-to-grasp task identified by observation could be used to describe the relationship between motor impairments and the time to perform functional tasks. Methods. Cross-sectional, secondary analysis of baseline data from 141 participants with stroke, age 18 to 85 years, who participated in a multicenter randomized controlled trial. Clinical assessment of movement quality using the Reaching Performance Scale for Stroke (RPSS–Close and Far targets) and of performance (activity) from the Wolf Motor Function Test (WMFT–7 items) was assessed. The degree to which RPSS component scores explained scores on WMFT items was determined by multivariable regression. Results. Clinically significant decreases (>2 seconds) in performance time for some of the more complex WMFT tasks involving prehension were predicted from RPSS–Close and Far target components. Trunk compensatory movements did not predict either increases or decreases in performance time for the WMFT tasks evaluated. Overall, the strength of the regression models was low. Conclusions. In lieu of kinematic analysis, observational clinical movement analysis may be a valid and accessible method to determine relationships between motor impairment, compensations and upper limb function in poststroke patients. Specific relationships are unlikely to generalize to all tasks due to kinematic redundancy and task specificity.

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Functional differences in upper limb movement after early and chronic stroke based on kinematic motion indicators

Biomedical Papers ◽

10.5507/bp.2018.061 ◽

2018 ◽

Vol 162 (4) ◽

pp. 294-303 ◽

Cited By ~ 2

Author(s):

Monika Blaszczyszyn ◽

Agnieszka Szczesna ◽

Jozef Opara ◽

Mariusz Konieczny ◽

Pawel Pakosz ◽

...

Keyword(s):

Upper Limb ◽

Limb Movement ◽

Chronic Stroke ◽

Functional Differences ◽

Kinematic Motion

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The Effect of Bilateral Training with Contextual Interference on Upper Limb Movement Function in Patients with Chronic Stroke

Korean Journal of Sport Studies ◽

10.23949/kjpe.2019.01.58.1.6 ◽

2019 ◽

Vol 58 (01) ◽

pp. 73-82

Author(s):

Young-Hoon Song

Keyword(s):

Upper Limb ◽

Limb Movement ◽

Chronic Stroke ◽

Contextual Interference ◽

Bilateral Training ◽

Movement Function

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Machine Learning Methods Predict Individual Upper-Limb Motor Impairment Following Therapy in Chronic Stroke

Neurorehabilitation and Neural Repair ◽

10.1177/1545968320909796 ◽

2020 ◽

Vol 34 (5) ◽

pp. 428-439 ◽

Cited By ~ 2

Author(s):

Ceren Tozlu ◽

Dylan Edwards ◽

Aaron Boes ◽

Douglas Labar ◽

K. Zoe Tsagaris ◽

...

Keyword(s):

Machine Learning ◽

Upper Extremity ◽

Upper Limb ◽

Motor Impairment ◽

Chronic Stroke ◽

Response To Therapy ◽

Stroke Patients ◽

Learning Methods ◽

Machine Learning Methods ◽

The Difference

Background. Accurate prediction of clinical impairment in upper-extremity motor function following therapy in chronic stroke patients is a difficult task for clinicians but is key in prescribing appropriate therapeutic strategies. Machine learning is a highly promising avenue with which to improve prediction accuracy in clinical practice. Objectives. The objective was to evaluate the performance of 5 machine learning methods in predicting postintervention upper-extremity motor impairment in chronic stroke patients using demographic, clinical, neurophysiological, and imaging input variables. Methods. A total of 102 patients (female: 31%, age 61 ± 11 years) were included. The upper-extremity Fugl-Meyer Assessment (UE-FMA) was used to assess motor impairment of the upper limb before and after intervention. Elastic net (EN), support vector machines, artificial neural networks, classification and regression trees, and random forest were used to predict postintervention UE-FMA. The performances of methods were compared using cross-validated R2. Results. EN performed significantly better than other methods in predicting postintervention UE-FMA using demographic and baseline clinical data (median [Formula: see text] P < .05). Preintervention UE-FMA and the difference in motor threshold (MT) between the affected and unaffected hemispheres were the strongest predictors. The difference in MT had greater importance than the absence or presence of a motor-evoked potential (MEP) in the affected hemisphere. Conclusion. Machine learning methods may enable clinicians to accurately predict a chronic stroke patient’s postintervention UE-FMA. Interhemispheric difference in the MT is an important predictor of chronic stroke patients’ response to therapy and, therefore, could be included in prospective studies.

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Quantifying upper limb motor impairment in chronic stroke: a physiological profiling approach

Journal of Applied Physiology ◽

10.1152/japplphysiol.00078.2021 ◽

2021 ◽

Author(s):

Lewis Anthony Ingram ◽

Annie A. Butler ◽

Matthew Andrew Dalhousie Brodie ◽

Stephen Ronald Lord ◽

Simon C. Gandevia

Keyword(s):

Upper Limb ◽

Test Performance ◽

Motor Impairment ◽

Chronic Stroke ◽

Anatomical Location ◽

Sensorimotor Function ◽

Upper Limbs ◽

Motor Impairments ◽

Upper Limb Function ◽

Stroke Population

Upper limb motor impairments, such as muscle weakness, loss of dexterous movement and reduced sensation are common following a stroke. The extent and severity of these impairments differs among individuals, depending on the anatomical location and size of lesions. Identifying impairments specific to the individual is critical to optimize their functional recovery. The upper limb Physiological Profile Assessment (PPA) provides quantitative measures of key physiological domains required for adequate function in the upper limbs. The current study investigates the use of the upper limb PPA in a chronic stroke population. 50 participants with chronic stroke completed all tests of the upper limb PPA; both with their affected and less affected upper limbs. Performance in each test was compared to 50 age- and sex matched controls with no history of a stroke. Correlations between test performance and validated measures of stroke, sensorimotor function and disability were examined. Compared to controls, people with stroke demonstrated substantially impaired upper limb PPA performance for both their affected and less affected limbs. Performance in the upper limb PPA was associated with validated measures of sensorimotor function specific to the stroke population (Fugl-Meyer Assessment), and stroke-related disability (Stroke Impact Scale). The upper limb PPA shows good concurrent validity as a means of to quantify upper limb function in a chronic stroke population. These tests identify domain-specific deficits and could be further tailored to an individual patient by the clinician to inform rehabilitation and track recovery.

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Baseline Motor Impairment Predicts Transcranial Direct Current Stimulation Combined with Physical Therapy-Induced Improvement in Individuals with Chronic Stroke

Neural Plasticity ◽

10.1155/2020/8859394 ◽

2020 ◽

Vol 2020 ◽

pp. 1-8

Author(s):

Adriana Baltar ◽

Daniele Piscitelli ◽

Déborah Marques ◽

Lívia Shirahige ◽

Kátia Monte-Silva

Keyword(s):

Physical Therapy ◽

Upper Limb ◽

Direct Current ◽

Transcranial Direct Current Stimulation ◽

Brain Lesion ◽

Motor Impairment ◽

Chronic Stroke ◽

Stroke Severity ◽

Direct Current Stimulation ◽

Before And After

Transcranial direct current stimulation (tDCS) can enhance the effect of conventional therapies in post-stroke neurorehabilitation. The ability to predict an individual’s potential for tDCS-induced recovery may permit rehabilitation providers to make rational decisions about who will be a good candidate for tDCS therapy. We investigated the clinical and biological characteristics which might predict tDCS plus physical therapy effects on upper limb motor recovery in chronic stroke patients. A cohort of 80 chronic stroke individuals underwent ten to fifteen sessions of tDCS plus physical therapy. The sensorimotor function of the upper limb was assessed by means of the upper extremity section of the Fugl-Meyer scale (UE-FM), before and after treatment. A backward stepwise regression was used to assess the effect of age, sex, time since stroke, brain lesion side, and basal level of motor function on UE-FM improvement after treatment. Following the intervention, UE-FM significantly improved ( p < 0.05 ), and the magnitude of the change was clinically important (mean 6.2 points, 95% CI: 5.2–7.4). The baseline level of UE-FM was the only significant predictor ( R 2 = 0.90 , F 1 , 76 = 682.80 , p < 0.001 ) of tDCS response. These findings may help to guide clinical decisions according to the profile of each patient. Future studies should investigate whether stroke severity affects the effectiveness of tDCS combined with physical therapy.

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