Recently featured in “Scientific Reports”, a rehabilitation robotic system that controls trunk posture in closed-loop improves locomotor performance during gait rehabilitation after spinal cord injury. To date, rehabilitation robotics has primarily focused on assistive devices that guide leg movements in order to maximize locomotor consistency and effort during training. Despite the importance of trunk posture …
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Epidural electrical stimulation (EES) of lumbosacral segments can restore a range of movements after spinal cord injury. However, the mechanisms and neural structures through which EES facilitates movement execution remain unclear. Here, we designed a computational model and performed in vivo experiments to investigate the type of fibers, neurons, and circuits recruited in response to EES. We first developed a realistic finite element computer model of rat lumbosacral segments to identify the currents generated by EES. To evaluate the impact of these currents on sensorimotor circuits, we coupled this model with an anatomically realistic axon-cable model of motoneurons, interneurons, and myelinated afferent fibers for antagonistic ankle muscles. Comparisons between computer simulations and experiments revealed the ability of the model to predict EES-evoked motor responses over multiple intensities and locations. Analysis of the recruited neural structures revealed the lack of direct influence of EES on motoneurons and interneurons. Simulations and pharmacological experiments demonstrated that EES engages spinal circuits trans-synaptically through the recruitment of myelinated afferent fibers. The model also predicted the capacity of spatially distinct EES to modulate side-specific limb movements and, to a lesser extent, extension versus flexion. These predictions were confirmed during standing and walking enabled by EES in spinal rats. These combined results provide a mechanistic framework for the design of spinal neuroprosthetic systems to improve standing and walking after neurological disorders.
Objectives. We aimed to develop a robotic interface capable of providing finely-tuned, multidirectional trunk assistance adjusted in real-time during unconstrained locomotion in rats and mice. Approach. We interfaced a large-scale robotic structure actuated in four degrees of freedom to exchangeable attachment modules exhibiting selective compliance along distinct directions. This combination allowed high-precision force and torque control in multiple directions over a large workspace. We next designed a neurorobotic platform wherein real-time kinematics and physiological signals directly adjust robotic actuation and prosthetic actions. We tested the performance of this platform in both rats and mice with spinal cord injury. Main Results. Kinematic analyses showed that the robotic interface did not impede locomotor movements of lightweight mice that walked freely along paths with changing directions and height profiles. Personalized trunk assistance instantly enabled coordinated locomotion in mice and rats with severe hindlimb motor deficits. Closed-loop control of robotic actuation based on ongoing movement features enabled real-time control of electromyographic activity in anti-gravity muscles during locomotion. Significance. This neurorobotic platform will support the study of the mechanisms underlying the therapeutic effects of locomotor prosthetics and rehabilitation using high-resolution genetic tools in rodent models.
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