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  • Title: Epidural Stimulation of Rat Spinal Cord at Lumbosacral Segment Using a Surface Electrode: A Computer Simulation Study.
    Author: Xu Q, Kong L, Zhou H, He J.
    Journal: IEEE Trans Neural Syst Rehabil Eng; 2017 Oct; 25(10):1763-1772. PubMed ID: 27834648.
    Abstract:
    Clinical research indicates that the epidural spinal cord stimulation (ESCS) at lumbosacral segment has shown potential for promoting locomotor recovery in patients with incomplete spinal cord injury. However, the underlying neural mechanism needs to be determined by animal experiments. In order to refine experimental protocols, we used a finite element simulation to investigate the activation of nerve fibers in a rat spinal cord model. Our model is composed of a volume conductor model from L1 to S2 spinal segments and the McIntyre-Richard-Grill axon model, which is used to investigate the threshold of selected spinal fibers with different diameters at varied locations and predict the neural responses of any target fibers with bipolar electrode configuration. Mathematical modeling suggests that the electrode-fiber distance may play an important role in the recruitment of nerve fibers, whereas longer pulse width predicted greater activity of spinal root fibers and dorsal column fibers, as well as may exert an effective influence on the motor system by the ability to increase and even "steer" spatial selectivity with deeper penetration into the dorsal columns. The spikes were initiated at sites along the nerve fibers depending on which component was closest to the cathode among the longitudinal part of the fiber, its entrance into spinal cord, or strong bending at the entry. Our simulation results show good agreement with the previous findings from animal studies. It is concluded that the computational ESCS model is a valuable tool to obtain a better insight into the immediately evoked electrophysiological phenomena in animal models, and provides further guidelines for conducting animal experiments to enhance the exploration of basic neural mechanisms.
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