Upper Limb Motor Improvement after Traumatic Brain Injury: Systematic Review of Interventions

Background Traumatic brain injury (TBI) is a leading cause of adult morbidity and mortality. Individuals with TBI have impairments in both cognitive and motor domains. Motor improvements post-TBI are attributable to adaptive neuroplasticity and motor learning. Majority of the studies focus on remediation of balance and mobility issues. There is limited understanding on the use of interventions for upper limb (UL) motor improvements in this population. Objective We examined the evidence regarding the effectiveness of different interventions to augment UL motor improvement after a TBI. Methods We systematically examined the evidence published in English from 1990–2020. The modified Downs and Black checklist helped assess study quality (total score: 28). Studies were classified as excellent: 24–28, good: 19–23, fair: 14–18, and poor: ≤13 in quality. Effect sizes helped quantify intervention effectiveness. Results Twenty-three studies were retrieved. Study quality was excellent (n = 1), good (n = 5) or fair (n = 17). Interventions used included strategies to decrease muscle tone (n = 6), constraint induced movement therapy (n = 4), virtual reality gaming (n = 5), non-invasive stimulation (n = 3), arm motor ability training (n = 1), stem cell transplant (n = 1), task-oriented training (n = 2), and feedback provision (n = 1). Motor impairment outcomes included Fugl-Meyer Assessment, Modified Ashworth Scale, and kinematic outcomes (error and movement straightness). Activity limitation outcomes included Wolf Motor Function Test and Motor Activity Log (MAL). Effect sizes for majority of the interventions ranged from medium (.5-.79) to large (≥.8). Only ten studies included retention testing. Conclusion There is preliminary evidence that using some interventions may enhance UL motor improvement after a TBI. Answers to emergent questions can help select the most appropriate interventions in this population.

Effects of Cerebellar Transcranial Direct Current Stimulation on Upper Limb Motor Function After Stroke: Study Protocol for the Pilot of a Randomized Controlled Trial

Background: Transcranial direct current stimulation (tDCS) is a technique that can noninvasively modulate neural states in a targeted brain region. As cerebellar activity levels are associated with upper limb motor improvement after stroke, the cerebellum is a plausible target of tDCS. However, the effect of tDCS remains unclear. Here, we designed a pilot study to assess: 1) the feasibility of a study that aims to examine the effects of cerebellar tDCS combined with an intensive rehabilitation approach based on the concept of constraint-induced movement therapy (CIMT), and 2) the preliminary outcome of the combined approach on upper limb motor function in patients with stroke in the chronic stage.Methods: This pilot study has a double-blind randomized controlled design. Twenty-four chronic stroke patients with mild to moderate levels of upper limb motor impairment will be randomly assigned to an active or sham tDCS group. The participants will receive 20 min of active or sham tDCS to the contralesional cerebellum at the commencement of 4 hours of daily intensive training, repeatedly for 5 days per week for 2 weeks. The primary outcome is upper limb motor function which will be evaluated using the Action Research Arm Test. Secondary outcomes comprise scores of the Fugl-Meyer Assessment for the upper extremity and the Motor Activity Log. Additionally, neurophysiological and neuroanatomical assessments of the cerebellum will be performed using transcranial magnetic stimulation and magnetic resonance imaging. These assessments will be conducted before, at the middle, and after the 2-week intervention, and finally 1 month after the intervention. Any adverse events that occur during the study will be recorded.Discussion: Cerebellar tDCS combined with intensive upper limb training may increase the gains of motor improvement when compared to the sham condition. The present study should provide valuable evidence regarding the feasibility of the design and the efficacy of cerebellar tDCS for upper limb motor function in patients with stroke before a future large trial is conducted.Trial registration: This study has been registered at the Japan Registry of Clinical Trials (jRCTs042200078; https://jrct.niph.go.jp/en-latest-detail/jRCTs042200078). Registered 17 December 2020

Predicting upper extremity motor improvement following therapy using EEG-based connectivity in chronic stroke

BACKGROUND: Uncertain prognosis presents a challenge for therapists in determining the most efficient course of rehabilitation treatment for individual patients. Cortical Sensorimotor network connectivity may have prognostic utility for upper extremity motor improvement because the integrity of the communication within the sensorimotor network forms the basis for neuroplasticity and recovery. OBJECTIVE: To investigate if pre-intervention sensorimotor connectivity predicts post-stroke upper extremity motor improvement following therapy. METHODS: Secondary analysis of a pilot triple-blind randomized controlled trial. Twelve chronic stroke survivors underwent 2-week task-practice therapy, while receiving vibratory stimulation for the treatment group and no stimulation for the control group. EEG connectivity was obtained pre-intervention. Motor improvement was quantified as change in the Box and Block Test from pre to post-therapy. The association between ipsilesional sensorimotor connectivity and motor improvement was examined using regression, controlling for group. For negative control, contralesional/interhemispheric connectivity and conventional predictors (initial clinical motor score, age, time post-stroke, lesion volume) were examined. RESULTS: Greater ipsilesional sensorimotor alpha connectivity was associated with greater upper extremity motor improvement following therapy for both groups (p < 0.05). Other factors were not significant. CONCLUSION: EEG connectivity may have a prognostic utility for individual patients’ upper extremity motor improvement following therapy in chronic stroke.

Machine Learning for Predicting Motor Improvement After Acute Subcortical Infarction Using Baseline Whole Brain Volumes

Background. Neuroimaging biomarkers are valuable predictors of motor improvement after stroke, but there is a gap between published evidence and clinical usage. Objective. In this work, we aimed to investigate whether machine learning techniques, when applied to a combination of baseline whole brain volumes and clinical data, can accurately predict individual motor outcome after stroke. Methods. Upper extremity Fugl-Meyer Assessments (FMA-UE) were conducted 1 week and 12 weeks, and structural MRI was performed 1 week, after onset in 56 patients with subcortical infarction. Proportional recovery model residuals were employed to assign patients to proportional and poor recovery groups (34 vs 22). A sophisticated machine learning scheme, consisting of conditional infomax feature extraction, synthetic minority over-sampling technique for nominal and continuous, and bagging classification, was employed to predict motor outcomes, with the input features being a combination of baseline whole brain volumes and clinical data (FMA-UE scores). Results. The proposed machine learning scheme yielded an overall balanced accuracy of 87.71% in predicting proportional vs poor recovery outcomes, a sensitivity of 93.77% in correctly identifying poor recovery outcomes, and a ROC AUC of 89.74%. Compared with only using clinical data, adding whole brain volumes can significantly improve the classification performance, especially in terms of the overall balanced accuracy (from 80.88% to 87.71%) and the sensitivity (from 92.23% to 93.77%). Conclusions. Experimental results suggest that a combination of baseline whole brain volumes and clinical data, when equipped with appropriate machine learning techniques, may provide valuable information for personalized rehabilitation planning after subcortical infarction.

The Analysis of Fine Motor Skills and Early Childhood Creativity through Weaving Activities

Fine motor improvement is exceptionally critical for a child's in general advancement. Early childhood still frequently have trouble moving their fingers for exercises such as cutting, drawing, coloring, tearing, collapsing, orchestrating and weaving. This consider points to portray the capacity of fine motor abilities and inventiveness of early childhood through weaving exercises. The investigate strategy utilized may be a writing survey conducted by collecting information or based on logical papers that interface investigate with existing writing to unravel a issue. The strategy of collecting library information is by perusing and taking notes and overseeing inquire about materials and after that concluding the investigate materials. The comes about appeared that the improvement of fine motor abilities and imagination in early childhood requires eye and hand coordination, such as performing manipulative developments, and communicating themselves through craftsmanship with weaving exercises.

Predicting Clinically Significant Improvement After Robot-Assisted Upper Limb Rehabilitation in Subacute and Chronic Stroke

Prior studies examining predictors of favorable clinical outcomes after upper limb robot-assisted therapy (RT) have many shortcomings. Therefore, the aim of this study was to identify meaningful predictors and a prediction model for clinically significant motor improvement in upper limb impairment after RT for each stroke phase. This retrospective, single-center study enrolled patients with stroke who received RT using InMotion2 along with conventional therapy (CT) from January 2015 to September 2019. Demographic characteristics, clinical measures, and robotic kinematic measures were evaluated. The primary outcome measure was the Fugl-Meyer Assessment-Upper Extremity (FMA-UE) and we classified patients with improvement more than the minimal clinically important difference as responders for each stroke phase. Univariable and multivariable logistic regression analyses were performed to assess the relationship between potential predictors and RT responders and determine meaningful predictors. Subsequently, meaningful predictors were included in the final prediction model. One hundred forty-four patients were enrolled. The Hand Movement Scale and time since onset were significant predictors of clinically significant improvement in upper limb impairment (P = 0.045 and 0.043, respectively), as represented by the FMA-UE score after RT along with CT, in patients with subacute stroke. These variables were also meaningful predictors with borderline statistical significance in patients with chronic stroke (P = 0.076 and 0.066, respectively). Better hand movement and a shorter time since onset can be used as realistic predictors of clinically significant motor improvement in upper limb impairment after RT with InMotion2 alongside CT in patients with subacute and chronic stroke. This information may help healthcare professionals discern optimal patients for RT and accurately inform patients and caregivers about outcomes of RT.

Deep brain electrical neurofeedback allows Parkinson patients to control pathological oscillations and quicken movements

Parkinsonian motor symptoms are linked to pathologically increased beta-oscillations in the basal ganglia. While pharmacological treatment and deep brain stimulation (DBS) reduce these pathological oscillations concomitantly with improving motor performance, we set out to explore neurofeedback as an endogenous modulatory method. We implemented real-time processing of pathological subthalamic beta oscillations through implanted DBS electrodes to provide deep brain electrical neurofeedback. Patients volitionally controlled ongoing beta-oscillatory activity by visual neurofeedback within minutes of training. During a single one-hour training session, the reduction of beta-oscillatory activity became gradually stronger and we observed improved motor performance. Lastly, endogenous control over deep brain activity was possible even after removing visual neurofeedback, suggesting that neurofeedback-acquired strategies were retained in the short-term. Moreover, we observed motor improvement when the learnt mental strategies were applied 2 days later without neurofeedback. Further training of deep brain neurofeedback might provide therapeutic benefits for Parkinson patients by improving symptom control using strategies optimized through neurofeedback.

Periinfarct rewiring supports recovery after primary motor cortex stroke

After stroke restricted to the primary motor cortex (M1), it is uncertain whether network reorganization associated with recovery involves the periinfarct or more remote regions. We studied 16 patients with focal M1 stroke and hand paresis. Motor function and resting-state MRI functional connectivity (FC) were assessed at three time points: acute (<10 days), early subacute (3 weeks), and late subacute (3 months). FC correlates of recovery were investigated at three spatial scales, (i) ipsilesional non-infarcted M1, (ii) core motor network (M1, premotor cortex (PMC), supplementary motor area (SMA), and primary somatosensory cortex), and (iii) extended motor network including all regions structurally connected to the upper limb representation of M1. Hand dexterity was impaired only in the acute phase ( P = 0.036). At a small spatial scale, clinical recovery was more frequently associated with connections involving ipsilesional non-infarcted M1 (Odds Ratio = 6.29; P = 0.036). At a larger scale, recovery correlated with increased FC strength in the core network compared to the extended motor network (rho = 0.71; P = 0.006). These results suggest that FC changes associated with motor improvement involve the perilesional M1 and do not extend beyond the core motor network. Core motor regions, and more specifically ipsilesional non-infarcted M1, could hence become primary targets for restorative therapies.