Motor Movements Research Articles

Mechanisms and Potential Benefits of Neuroprotective Agents in Neurological Health

The brain contains many interconnected and complex cellular and molecular mechanisms. Injury to the brain causes permanent dysfunctions in these mechanisms. So, it continues to be an area where surgical intervention cannot be performed except for the removal of tumors and the repair of some aneurysms. Some agents that can cross the blood–brain barrier and reach neurons show neuroprotective effects in the brain due to their anti-apoptotic, anti-inflammatory and antioxidant properties. In particular, some agents act by reducing or modulating the accumulation of protein aggregates in neurodegenerative diseases (Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, Amyotrophic lateral sclerosis, and prion disease) caused by protein accumulation. Substrate accumulation causes increased oxidative stress and stimulates the brain’s immune cells, microglia, and astrocytes, to secrete proinflammatory cytokines. Long-term or chronic neuroinflammatory response triggers apoptosis. Brain damage is observed with neuronal apoptosis and brain functions are impaired. This situation negatively affects processes such as motor movements, memory, perception, and learning. Neuroprotective agents prevent apoptosis by modulating molecules that play a role in apoptosis. In addition, they can improve impaired brain functions by supporting neuroplasticity and neurogenesis. Due to the important roles that these agents play in central nervous system damage or neurodegenerative diseases, it is important to elucidate many mechanisms. This review provides an overview of the mechanisms of flavonoids, which constitute a large part of the agents with neuroprotective effects, as well as vitamins, neurotransmitters, hormones, amino acids, and their derivatives. It is thought that understanding these mechanisms will enable the development of new therapeutic agents and different treatment strategies.

Functional Neuroanatomy of the Normal and Pathological Basal Ganglia.

The term "basal ganglia" refers to a group of interconnected subcortical nuclei engaged in motor planning and movement initiation, executive functions, behaviors, and emotions. Dopamine released from the substantia nigra is the underlying driving force keeping the basal ganglia network under proper equilibrium and, indeed, reduction of dopamine levels triggers basal ganglia dysfunction, setting the groundwork for several movement disorders. The canonical basal ganglia model has been instrumental for most of our current understanding of the normal and pathological functioning of this subcortical network. This model explains how cortical information flows through the basal ganglia nuclei back to the cortex by going through two pathways with opposing effects that together lead to the proper execution of a given movement. The basal ganglia model has paved the way for the standard clinical management of Parkinson's disease, where pharmacological and neurosurgical treatments in place collectively afford an impressive symptomatic alleviation. Although much of the model has remained, the canonical model has been enriched with new arrivals gathered from evidence provided in the last three decades. Here, we sought to provide a comprehensive review of the basal ganglia network, with emphasis on structure, connectivity patterns, and basic operational principles, both in normal and pathological conditions.

The Role of Visual Information Quantity in Fine Motor Performance

Background/Objectives: Fine motor movements are essential for daily activities, such as handwriting, and rely heavily on visual information to enhance motor complexity and minimize errors. Tracing tasks provide an ecological method for studying these movements and investigating sensorimotor processes. To date, our understanding of the influence of different quantities of visual information on fine motor control remains incomplete. Our study examined how variations in the amount of visual feedback affect motor performance during handwriting tasks using a graphic pen tablet projecting on a monitor. Methods: Thirty-seven right-handed young adults (20 to 35 years) performed dot-to-dot triangle tracing tasks under nine experimental conditions with varying quantities of visual cues. The conditions and triangle shape rotations were randomized to avoid motor training or learning effects. Motor performance metrics, including absolute error, time of execution, speed, smoothness, and pressure, were analyzed. Results: As visual information increased, absolute error (from 6.64 mm to 2.82 mm), speed (from 99.28 mm/s to 57.19 mm/s), and smoothness (from 4.17 mm2/s6 to 0.80 mm2/s6) decreased, while time of execution increased (from 12.68 s to 20.85 s), reflecting a trade-off between accuracy and speed. Pressure remained constant across conditions (from 70.35 a.u. to 74.39). Spearman correlation analysis demonstrated a moderate to strong correlation between absolute error and time of execution across conditions. The Friedman test showed significant effects of experimental conditions on all motor performance metrics except for pressure, with Kendall’s W values indicating a moderate to strong effect size. Conclusion: These findings deepen our understanding of sensorimotor integration processes and could potentially have implications for optimizing motor skills acquisition and training and developing effective rehabilitation strategies.

Commentary on “An interdisciplinary approach to improve oral motor fluency and speech production: a case study”

Purpose The purpose of this paper is to explore the process applied by Schepp et al. (2024; this issue) to enhance the acquisition of speech production. It discusses its relevance to individuals with intellectual and developmental disabilities (IDD), with a particular focus on motor movements and leisure skills. The intention is to encourage practitioners to consider the scope of application possibilities and to connect further with the literature surrounding fluency of motor movements and precision teaching. Design/methodology/approach A narrative approach is applied throughout. Context of skill proficiency, performance and practices for completing component-composite analyses are described, with a practical example given. Variable and critical features of precision teaching relative to discussed aspects are emphasised. Findings Fluency in fundamental movements is foundational for developing more complex skills. A component-composite analysis is a helpful, structured approach for identifying precursor skills. These approaches are particularly beneficial for individuals with IDD, who often experience motor movement challenges and barriers in accessing leisure activities. Originality/value This paper adds to existing descriptions and discussions regarding the purpose and practical process of identifying precursor skills, then fluency building to performance criterion. Less commonly discussed is the relationship between these and critical and variable features of precision teaching, which are highlighted here. Attention is also drawn to the lesser reported scope of applying these practices to leisure-orientated goals for individuals with IDD.

Hybrid 3D Convolutional–Transformer Model for Detecting Stereotypical Motor Movements in Autistic Children During Pre-Meltdown Crisis

Computer vision using deep learning algorithms has served numerous human activity identification applications, particularly those linked to safety and security. However, even though autistic children are frequently exposed to danger as a result of their activities, many computer vision experts have shown little interest in their safety. Several autistic children show severe challenging behaviors such as the Meltdown Crisis which is characterized by hostile behaviors and loss of control. This study aims to introduce a monitoring system capable of predicting the Meltdown Crisis condition early and alerting the children’s parents or caregivers before entering more difficult settings. For this endeavor, the suggested system was constructed using a combination of a pre-trained Vision Transformer (ViT) model (Swin-3D-b) and a Residual Network (ResNet) architecture to extract robust features from video sequences to extract and learn the spatial and temporal features of the Stereotyped Motor Movements (SMMs) made by autistic children at the beginning of the Meltdown Crisis state, which is referred to as the Pre-Meltdown Crisis state. The evaluation was conducted using the MeltdownCrisis dataset, which contains realistic scenarios of autistic children’s behaviors in the Pre-Meltdown Crisis state, with data from the Normal state serving as the negative class. Our proposed model achieved great classification accuracy, at 92%.

Effect of Prednisolone on Clinical and Cytokine mRNA Profiling in Complex Regional Pain Syndrome.

The cardinal clinical features of complex regional pain syndrome type I (CRPS-I) are pain, edema, autonomic changes, and limitation of motoric movement, which may indicate the role of inflammation and cytokines. We report the effect of prednisolone on the clinical severity and mRNA profiling of proinflammatory (tumor necrosis factor (TNF)-α and interleukin (IL)-2) and anti-inflammatory cytokines (IL-10 and transforming growth factor (TGF)-β) in the patient with CRPS-I. Thirty-nine patients with CRPS-I of shoulder joint were enrolled. Their CRPS, Visual Analog Scale (VAS) and Daily Sleep Interference Scale (DSIS) scores were recorded. TNF-α, IL-2, IL-10, and TGF-β gene expressions at mRNA of whole blood were measured by reverse transcriptase polymerase chain reaction. Patients were randomized to prednisolone 20mg or 40mg using 1: 1 randomization. The primary outcome was change in VAS score, and secondary outcomes were change in CRPS and DSIS scores at 1month. Side effects were noted. The patients had increased expressions of TNF-α (p < 0.001) and IL-2 (p < 0.001) and reduced IL-10 (p < 0.01) mRNA compared to the healthy controls. The baseline characteristics were matched between the two treatment arms. At 1month, CRPS, VAS, and DSIS scores improved significantly compared to baseline, which paralleled with improvement in IL-10 (p < 0.032) and reduction in TNF-α (p = 0.046). The improvement in clinical and biomarkers was similar in prednisolone 20mg and 40mg arms. None had to be withdrawn due to severe side effects. Future study in larger cohort may validate these findings.

Mu down regulation EEG-neurofeedback training combined to motor imagery facilitates early consolidation in a sequential finger tapping task

Objective.Motor imagery (MI) has demonstrated positive effects on motor performance and triggers activation in the motor cortex (MC). EEG-Neurofeedback (EEG-NF) is a neuromodulation technique that provides real-time feedback on one's brain activity, enabling self-regulation of brain states. While there is increasing evidence of humans controlling the activity of various brain networks, including the MC, through EEG-NF, the tangible benefits of this self-regulation on motor performance remain uncertain. This study investigates the potential benefits of EEG-NF training in explicit learning of a sequential movement, in comparison to MI training and to a combined EEG-NF and MI training.Approach.Ninety-one right-handed healthy adults were randomly assigned to one of four groups (a)NF(n= 24), (b)MI(n= 22), (c)MI + NF(n= 23) and (d)control(n= 22). Participants performed a sequential finger tapping task before and after (immediately, 20 min and 24 h) a single 30 min training session. Motor performance, movement speed and event related desynchronization data were analyzed.Main results.MI training led to a better motor performance compared to control condition immediately after training that was sustained at the 20 min retest time point (p= 0.02 and 0.05). In contrast, EEG-NF training alone did not yield better motor performance compared to control condition at any time-point (p> .05). Remarkably, only the combination of both trainings led to superior motor performance 24 h after training in comparison to control group (p= 0.02). Additionally, all experimental groups successfully decreased mu rhythm amplitude throughout most of the training.Significance.Combined EEG-NF and MI training appears particularly promising for enhancing motor consolidation holding the potential to advance rehabilitation approaches.

Correlation Analysis Approach Between Features and Motor Movement Stimulus for Stroke Severity Classification of EEG Signal Based on Time Domain, Frequency Domain, and Signal Decomposition Domain

The healing process of a stroke necessitates tools for measuring relevant parameters to facilitate monitoring, evaluation, and medical rehabilitation. Accurate parameter measures can be observed in stroke patients' severity to ascertain suitable interventions by identifying components pertinent to monitoring, evaluation, and medical rehabilitation. The components are derived from the observation collection process utilizing an EEG device, accompanied by a motor stimulus, to ensure the acquisition of EEG signals for monitoring, evaluation, and medical rehabilitation while preventing any loss of information during data collection. The acquired information encounters challenges due to the signal's unstable, nonlinear, and non-stationary characteristics, necessitating efforts to stabilize, render stationary, and linearize it through suitable signal processing and feature extraction techniques to achieve a pertinent feature composition. The subsequent difficulty is achieving the objectives of medical monitoring, evaluation, and rehabilitation, necessitating the correlation between EEG signal characteristics and motor movement stimuli, ensuring that the process adheres to appropriate parameter identification and scheduling per the established plan. In response to this difficulty, a correlation analysis methodology is established, incorporating normalcy tests, significance tests, and correlation analysis to ensure that the relevant factors for identifying stroke severity categorization patterns are precisely identified beforehand. The correlation analysis strategy employs raw data situations, preprocessing, feature extraction, feature selection, and correlation analysis for classification purposes. Our experimental findings indicate that the correlation analysis approach for assessing stroke severity classification patterns is evident in the Hajorth Complexity feature, utilizing the Shoulder motor movement stimulus and the SVM classification type, achieving an accuracy significant value of 98%. These findings confirm the efficacy of correlation analysis between EEG signal features and motor movement stimuli in identifying the optimal parameters within a reduced dimensional space to assess stroke severity effectively.

Decoupling of motor cortex to movement in Parkinson's dyskinesia rescued by sub-anaesthetic ketamine.

Gamma band and single-unit neural activity in primary motor cortex (M1) are involved in the control of movement. This activity is disrupted in Parkinson's disease (PD) and levodopa-induced dyskinesia (LID), a debilitating consequence of dopamine replacement therapy for PD. Physiological features of LID include pathological narrowband gamma oscillations, finely tuned gamma (FTG), and altered M1 firing activity. Since most studies characterize LID through visual scoring, little is known about the relationships between ongoing dyskinetic movements, gamma, and neuronal activity at fast (sub-second) and slow (seconds) timescales. Here, we investigate how motor cortex activity changes with movement at multiple timescales in animal models of PD and LID. Furthermore, sub-anesthetic ketamine has emerged as a possible therapy for LID. How ketamine may reduce LID is not fully understood. Consequently, we investigate how ketamine affects the relationship between motor cortex activity and movement. To investigate these questions, local-field and single-unit activity from >3000 motor cortex neurons was acquired using a standard model of PD/LID (n = 10 male rats). Data in LID and sham animals was acquired following levodopa (L-DOPA; 12 mg/kg, i.p.) and ketamine (20 mg/kg, i.p.) administration. Movement was assessed using traditional abnormal involuntary movements (AIMs) scores and head-mounted inertial sensors sampled at 200 Hz. While correlations between movement, gamma, and single-unit activity were high in all animals during control conditions, correlations decreased considerably in animal models of LID following L-DOPA administration. This suggests that M1 can become functionally decoupled from ongoing movements in LID. Interestingly, this effect was observed in both the dopamine depleted and non-depleted hemispheres. Ketamine disrupted FTG, decreased LID, and moderately increased single-unit correlations to movement during LID. Ketamine, however, did not enhance the correlation between gamma-band activity and movement. Finally, ketamine exerted a selective effect on neuronal interactions and ensemble activity in LID animals. Specifically, analysis of cell-pair firing-rate correlations showed that ketamine induced a distinct neural ensemble state in LID by reorganizing the pattern of cell-pair interactions. These findings provide insight into the role that motor cortex neurons and gamma-band activity play during healthy movement and LID. Results suggest that primary motor cortex does not directly trigger specific dyskinetic movements during LID but, instead, dysregulated motor cortex activity may permit aberrant movements to spontaneously emerge in downstream circuits. These data further support the anti-dyskinetic properties of ketamine and suggest that ketamine acts to reduce LID by disrupting pathological interactions between motor cortex neurons during dyskinesia.

Classification of motor imagery EEG with ensemble RNCA model

Motor Imagery (MI) based brain-computer interface (BCI) systems are used for regaining the motor functions of neurophysiologically affected persons. But the performance of MI tasks is degraded due to the presence of redundant EEG channels. Hence, a novel ensemble regulated neighborhood component analysis (ERNCA) method provides a perfect identification of neural region that stimulate motor movements. Domains of statistical, frequency, spatial and transform-based features narrowed down the misclassification rate. The gradient boosting method selects the relevant features thereby reduces the computational complexity. Finally, Bayesian optimized ensemble classifier finetuned the classification accuracies of 97.22 % and 91.62 % for Datasets IIIa and IVa respectively. This approach is further strengthened by analyzing real-time data with the accuracy of 93.75 %. This method qualifies out of four benchmark methods with significant percent of improvement in accuracy for these three datasets. As per the spatial distribution of refined EEG channels, majority of the brain's motor functions concentrates on frontal and central cortex regions of brain.

Subtle bradykinesia features are easier to identify and more prevalent than questionable dystonia in essential tremor.

Essential tremor (ET) is characterized by upper limbs action tremor, sometimes extending to other body parts. However, ET can present with additional neurological features known as "soft signs." These signs of uncertain clinical significance are not sufficient to suggest an alternative neurological diagnosis, and include, among others, questionable dystonia and subtle voluntary movement alterations, i.e., bradykinesia and related features. This study aimed to explore the prevalence and relationship between questionable dystonia and subtle bradykinesia features in ET. Forty ET patients were video-recorded during clinical examination. Five movement disorder experts reviewed the videos to identify soft motor signs, i.e., dystonia and movement alterations during finger-tapping namely, (i) bradykinesia (reduced velocity), (ii) dysrhythmia, and (iii) sequence effect. Inter-rater agreement was quantified using the Fleiss' Kappa index. Data analysis was performed using nonparametric tests. We found a fair inter-rater agreement for upper limb dystonia (Fleiss' K = 0.27). Inter-rater agreement was higher (moderate) for head dystonia (Fleiss' K = 0.49) and finger-tapping assessment (Fleiss' K = 0.45). Upper limb dystonia was identified in 70% of patients, head dystonia in 35%, and finger-tapping alterations (in variable combinations) were observed in 95% of individuals (P < 0.001 by Fisher's exact test), including subtle bradykinesia and related features. No significant concordance or correlation was found between the soft signs. Subtle bradykinesia and related features are the most easily identifiable and frequent soft signs in ET, appearing in a higher percentage of patients than subtle dystonia. These findings provide insights into the clinical and pathophysiological understanding of ET.

Gender Based Variation in the Prevalence of Cerebral Palsy in Pakistan

Cerebral palsy (CP) is a neurological disorder that affects motor movement, posture, and tone as a result of a persistent encephalopathy acquired during fetal, infancy, or early childhood development. This review aimed to gather the pooled prevalence to assess the gender-based variation of CP in different cities of Pakistan. A comprehensive literature review was conducted in July. 2023 to Nov. 2023, and search terms ‘Cerebral Palsy’ or ‘CP’, ‘gender’ or ‘sex’, ‘Prevalence’, and ‘Pakistan’ were utilized. Published literature from different databases including Google Scholar, PakMediNet, PubMed, and ScienceDirect were employed to retrieve articles. From a total of 6,560 articles published during 2000-2022, 8 were selected. Titles and abstracts of all studies were reviewed, and full texts of relevant studies were obtained from cohort, chain referral, cross-sectional, descriptive retro-prospective, and survey studies. The majority of studies reported a greater male-to-female ratio of CP and a few reasons for this disparity are discussed.

Is hyperactivity in children with attention deficit/hyperactivity disorder (ADHD) a functional response to demands on specific executive functions or cognitive demands in general?

Hyperactivity is a core and impairing deficit in the clinical model of attention-deficit/hyperactivity disorder (ADHD). However, the extent to which hyperactivity in ADHD is evoked by cognitively challenging tasks in general or by demands on specific executive functions remains unclear. A clinically evaluated and carefully phenotyped community-referred sample of 184 children ages 8-13 (M = 10.40, SD = 1.50; 61 girls) with ADHD (n = 119) and without ADHD (neurotypical children and children with psychiatric disorders other than ADHD) were administered multiple, counterbalanced executive (working memory, inhibitory control, set shifting) and nonexecutive tests. Objective measures of gross motor movement (hyperactivity) were obtained using actigraphy. Using bifactor s-1 modeling, results indicate that children with ADHD demonstrate moderately elevated levels of motor movement relative to non-ADHD children. Additionally, findings indicated that hyperactivity in ADHD reflects the outcome of at least two similarly important factors: (a) a baseline level of elevated motor movement that is independent of environmental demands on their executive and nonexecutive cognitive abilities (d = 0.72); and (b) additional elevations attributable to demands placed on specific executive functions, with working memory and inhibition demands evoking similarly large, differential increases in movement for children with ADHD above and beyond their elevated baselines (Δd = 0.80). These findings suggests that executive function demands exacerbate, but do not fully explain, hyperactivity in ADHD, and/or there are at least two pathways to hyperactivity in ADHD-hyperactivity caused by environmental demands that challenge their underdeveloped executive functions, and hyperactivity caused by one or more other factors that need future research to identify. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Robust Driving Control Design for Precise Positional Motions of Permanent Magnet Synchronous Motor Driven Rotary Machines with Position-Dependent Periodic Disturbances

Position-dependent periodic disturbances often limit the accuracy and smoothness of the positional motion of permanent magnet synchronous motor (PMSM)-driven rotary machines. Because the period of these disturbances varies with the motion velocity of the rotary machine, spatial domain control methods such as spatial iterative learning control (SILC) and spatial repetitive control (SRC) have been proposed and applied to improve rotary machine motion control designs. However, problems with learning period convergence and rotary machine dynamics significantly affect transient motion, further constraining the overall motion performance. To address these challenges, this study developed a robust driving control (RDC) that integrates a robust control design with position-dependent periodic disturbance feedforward compensation, rotary machine dynamics compensation, and proportional–proportional integral feedback control. A position-dependent periodic disturbance model was developed using multiple position–sinusoidal signals and identified using a spatial fast Fourier transform. RDC compensates for disturbances and dynamics and considers the effects of model parameter uncertainty and modeling error on the stability of the control system. Several motion control experiments were conducted on a PMSM test bench to compare the RDC, SILC, and SRC. The experimental results demonstrated that although both SILC and SRC can effectively suppress position-dependent periodic disturbances, SILC provides slower position error convergence owing to the learning process, and SILC and SRC result in significant position errors because of the influence of the PMSM-driven rotary machine dynamics. RDC not only suppresses position-dependent periodic disturbances, but also significantly reduces position errors with a reduction rate of 90%. Therefore, the RDC developed in this study effectively suppressed position-dependent periodic disturbances and significantly improved both the transient-state and steady-state position-tracking performances of the PMSM-driven rotary machine.

Modeling and control of dynamical biomechanical arm systems with elastic joints sensitive to the effect of an external load

In this study, a biomechanical model mimicking the human hand-arm system under heavy disk excitation is developed to define the stability threshold between the preload vibration and the stress of the human hand-arm system. The fully electromechanical system, consisting of a DC motor, a transmission system, and three discrete masses representing the upper arm, forearm, and hand lifting a heavy disk, is connected by shock absorbers and various springs. The challenge of mimicking the angular activity of the elbow joint in torsion and flexion was also included to assess its contribution to system stability and to study the absorption of mechanical energy in the human hand-arm system. Finally, the movements of the model were described by a differential matrix equation, and its analysis facilitates the understanding of the threshold of the chaotic behaviors observed in an oscillating arms system. Specifically, it explores how the motion of a DC motor can be regulated using a single controller parameter within the context of a multi-degree-of-freedom human hand-arm system. The study uses numerical integrations to analyze system behaviors, with an emphasis on the use of frequency spectra, Poincaré maps, and bifurcation diagrams for visualization and interpretation. The results indicate that the system exhibits chaotic behavior when subjected to certain conditions, particularly when the mass load exceeds 35 kg. Imposing motion on the mass block further intensifies the chaos, leading to manifestations such as strong oscillations and frequency-synchronization effects. These characteristics, exhibited by the idealized model, which imitates the human body through a mechanical model and computation of the motions of the body, play a vital role in various fields of ergonomics and sports biomechanics. Understanding the dynamic behaviors of such systems, especially in response to varying conditions, has significant implications for engineering applications.

MBNL deficiency in motor neurons disrupts neuromuscular junction maintenance and gait coordination.

Muscleblind-like proteins (MBNLs) are a family of RNA-binding proteins that play essential roles in the regulation of RNA metabolism. Beyond their canonical role in RNA regulation, MBNL proteins have emerged as key players in the pathogenesis of Myotonic Dystrophy type 1 (DM1). In DM1, sequestration of MBNL proteins by expansion of the CUG repeat RNA leads to functional depletion of MBNL, resulting in deregulated alternative splicing and aberrant RNA processing, which underlie the clinical features of the disease. While attention to MBNL proteins has focused on their functions in skeletal muscle, new evidence suggests that their importance extends to motor neurons (MNs), pivotal cellular components in the control of motor skills and movement. To address this question, we generated conditional double knockout mice in which Mbnl1 and Mbnl2 were specifically deleted in motor neurons (MN-dKO). Adult MN-dKO mice develop gait coordination deficits associated with structural and ultrastructural defects in the neuromuscular junction, indicating that MBNL activity in MNs is crucial for the maintenance of the neuromuscular junction. In addition, transcriptome analysis performed on the spinal cord of MN-dKO mice identified mis-splicing events in genes associated with synaptic transmission and neuromuscular junction homeostasis. In summary, our results highlight the complex roles and regulatory mechanisms of MBNL proteins in MNs for muscle function and locomotion. This work provides valuable insights into fundamental aspects of RNA biology and offers promising avenues for therapeutic intervention in DM1 as well as a range of diseases associated with RNA dysregulation.

Effect of sling exercise training on motor function in children with cerebral palsy: A systematic review and meta-analysis.

To systematically evaluate the efficacy of sling exercise training on balance and gross motor movement in children with cerebral palsy, and to investigate the effects of different intervention times and ages on treatment outcomes. Randomized controlled trials on sling exercise training for children with cerebral palsy published in full text from CNKI, Wanfang datebase, PubMed, Cochrane Library, Web of Science, and Scopus were searched from the time of build to November 2023. Literature screening, data extraction, and quality assessment were performed independently by 2 researchers, and Meta-analysis was performed using RevMan5.4 and Stata17.0 software. A total of 12 studies with 725 patients were included sling exercise training significantly improved balance (I2 = 0%, mean difference [MD] = 3.42, 95% CI: 2.93-3.92, P < .00001), gross motor function (I2 = 0%, MD = 5.90, 95% CI: 1.50-10.29, P < .00001), standing function (I2 = 14%, MD = 2.73, 95% CI: 2.17-3.29, P < .00001) walking and running and jumping function(I2 = 79%, MD = 5.93, 95% CI: 3.82-8.04, P < .00001) and 10-meter maximum walking speed(I2 = 58%, MD = 1.47, 95% CI: 0.52-2.42, P = .003) in children with cerebral palsy. Subgroup analyses of balance showed that children in the 5 + age group (I2 = 0%, MD = 3.73, 95% CI: 2.55-4.91, P < .00001) had better outcomes relative to the 4-5 year old group (I2 = 23%, MD = 3.49, 95% CI: 2.88-4.09, P<0.00001) and the under 4 year old group (I2 = 0%, MD = 282.73, 95% CI: 1.57-4.06, P < .00001). Subgroup analyses of walking and running and jumping function showed that a 6-month treatment course(I2 = 0%, MD = 5.93, 95% CI: 3.82-8.04, P < .00001) had better efficacy relative to a 3-month treatment course(I2 = 0%, MD = 4.11, 95% CI: 2.84-5.39, P < .00001). Sling exercise training significantly improves balance and gross motor function in children with cerebral palsy, and The average age of 5+ years is a critical period for the development of balance in children with cerebral palsy, and the treatment course is an important factor affecting walking and running and jumping function.

Exploring temporal congruence in motor imagery and movement execution in non-specific chronic low back pain

Chronic non-specific low back pain (NSCLBP) is linked to sensorimotor dysfunctions and altered motor planning, likely due to neuroplastic changes. Motor imagery (MI) and movement execution share neural pathways, but the relationship between imagined and executed movements in NSCLBP patients remains underexplored. This study aimed to assess the temporal congruence between imagined and executed movements in NSCLBP sufferers, with secondary goals of investigating group differences in movement chronometry, psychological well-being, and disability, as well as possible correlations among these factors. Fifty-six participants, including 28 NSCLBP patients and 28 asymptomatic subjects (AS), performed lumbar flexion and Timed Up and Go (TUG) tasks. NSCLBP patients showed significant temporal incongruence in both tasks, executing movements more slowly than imagined, whereas AS displayed incongruence only in the TUG task. NSCLBP patients also took longer to imagine and execute lumbar flexion movements compared to AS, with correlations observed between execution delays, higher disability, and greater fear of movement. The findings highlight a lack of temporal congruence in NSCLBP patients, especially in lumbar flexion, emphasizing the complex relationship between chronic pain, motor ability, and psychological factors. These results suggest that integrated treatment approaches addressing cognitive and emotional aspects are crucial for managing NSCLBP.

Impact of motor education levels and circuit training on enhancing wrestling techniques among adolescent athletes

Background Problems: Wrestling is a compulsory course that can improve physical strength, discipline, and strategic skills and student learning outcomes. However, the learning outcomes are still not optimal due to inconsistent training, limited technique understanding, and a lack of independent training opportunities. Research Objectives: The purpose of this study is to evaluate the effect of motor education level and circuit training on proficiency in learning wrestling martial arts techniques. Methods: This study used an experimental design with a pretest-posttest control group where there are two groups, the high motor ability group and the low motor ability group. The population consists of 40 students, and a sample of 20 students was selected using purposive sampling techniques based on certain criteria. Motor ability in this study is defined as an individual's ability to learn and develop motor skills, which is used to measure how quickly and efficiently a person can learn new motor movements. Data collection was done by measuring the level of motor ability and evaluating the techniques of wrestling after a period of practice. Data analysis was conducted using SPSS 23 statistical software to evaluate the learning outcomes of the basic techniques of wrestling. Findings/Results: The results of the data analysis showed that overall, there were no significant differences between the two groups. However, when looking closely at the level of motor skills, there are differences in the post-test scores between students with high and low motor skills. Conclusion: The conclusions of the study showed that although there were no significant differences between the two groups, the high motor skills group showed more consistent improvements. Future research could focus on the development of physical and mental skills such as endurance, strength, and discipline, which are important in improving wrestlers’ performance.

Invasive neurophysiological recordings in human basal ganglia. What have we learned about non-motor behaviour?

Research into the function of deep brain structures has benefited greatly from microelectrode recordings in animals. This has helped to unravel physiological processes in the healthy and malfunctioning brain. Translation to the human is necessary for improving basic understanding of subcortical structures and their implications in diseases. The use of microelectrode recordings as a standard component of deep brain stimulation surgery offers the most viable route for studying the electrophysiology of single cells and local neuronal populations in important deep structures of the human brain. Most of the studies in the basal ganglia have targeted the motor loop and movement disorder pathophysiology. In recent years, however, research has diversified to include limbic and cognitive processes. This review aims to provide an overview of advances in neuroscience made using intraoperative and post-operative recordings with a focus on non-motor activity in the basal ganglia.