A motor program generator control model is proposed to simulate neuromuscular control. Three muscles (Biceps, Triceps, Brachialis) driving elbow joint flexion in a plane are simulated by integrating their nonlinear dynamic property and spinal neural circuitry. The motor descending commands are described by a visual feedback signal from the joint and an excitation signal for the motor neuron pool. The visual feedback signal mimics the gamma command whereas the excitation signal mimics another descending co-activation command. The gamma command is expressed as the output of a PID controller with the visual feedback error signal as the input. The gamma command and the motoneuron pool background activity are the inputs to the motoneuron pool model coupled with the Renshaw cell recurrent inhibitions. The output of the motoneuron pool model mimics the alpha command feeding directly to the muscle dynamics. A movement is produced by reducing the error signal between goal position and actual position and altering excitation signal properly. The simulation results show that a burst pattern of excitation signal and a PID controller can accurately trace the terminal goal and generate a smooth movement with a bell shaped velocity profile. The muscle activation signals have the characteristic similar to the smoothed EMG. Changing different parameters of the PID can cause the same effects as the stimulus pulse intensity or duration modulation.
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Autism
January 2025
Department of Psychology, Umeå University, Sweden.
Many children with autism struggle with movement difficulties, yet the causes of these difficulties remain unclear. One possible explanation is atypical motor planning and integration of visual and motoric information. Before performing a goal-directed movement, the brain creates a prediction of the movement based on visual and sensory information and previous experience, forming a "blueprint" of the motor steps needed to achieve the goal.
View Article and Find Full Text PDFFront Neurol
December 2024
School of Physical Education and Sports Science, South China Normal University, Guangzhou, Guangdong, China.
Background: This study aims to evaluate the optimal rehabilitation regimen for lower limb dysfunction in stroke patients by analyzing the effects of proprioceptive training (PT) in combination with different rehabilitation interventions.
Methods: Randomized controlled trials (RCTs) published up to April 23, 2024, were searched from PubMed, Embase, Cochrane Library, Web of Science, CNKI, Wanfang, VIP, and SinoMed. The quality of the included studies was assessed using the Cochrane Risk of Bias tool (ROB 2.
Curr Probl Surg
January 2025
Department of Urology, Cedars-Sinai Medical Center, Los Angeles, CA.
Introduction:: Surgical training is a constant exchange between trainers and trainees, and intraoperative surgical feedback is an integral part of learning. New technologies in robotic surgery allow for the delivery of visual aid and verbal feedback intraoperatively, but it has not yet been determined if feedback type affects the trainee learning process.
Methods:: 49 novice participants were recruited and randomized into four feedback groups: , , of verbal/visual, and no feedback ().
J Appl Biomech
January 2025
Rehabilitation Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.
Knee osteoarthritis (KOA) can have more pronounced effects on joint position sense (JPS) accuracy and gait characteristics. The aim of this study is to investigate the association between lower limb JPS and different aspects of gait pattern including gait asymmetry and variability and spatiotemporal coordination in individuals with bilateral KOA. In this cross-sectional study, lower limb JPS of 43 individuals with bilateral KOA (mild and moderate) were measured.
View Article and Find Full Text PDFBrain Commun
January 2025
Department of Psychology, University of California, Riverside, CA 92507, USA.
Visual perceptual learning (VPL), the training-induced improvement in visual tasks, has long been considered the product of neural plasticity at early and local stages of signal processing. However, recent evidence suggests that multiple networks and mechanisms, including stimulus- and task-specific plasticity, concur in generating VPL. Accordingly, early models of VPL, which characterized learning as being local and mostly involving early sensory areas, such as V1, have been updated to embrace these newfound complexities, acknowledging the involvement on parietal (i.
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