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Central pattern generator network model for the alternating hind limb gait of rats based on the modified Van der Pol equation

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Abstract

Herein, we employed a central pattern generator (CPG), a spinal cord neural network that regulates lower-limb gait during intra-spinal micro-stimulation (ISMS). Particularly, ISMS was used to determine the spatial distribution pattern of CPG sites in the spinal cord and the signal regulation pattern that induced the CPG network to produce coordinated actions. Based on the oscillation phenomenon of the single CPG neurons of Van der Pol (VDP) oscillators, a double-cell CPG neural network model was constructed to realise double lower limbs, six-joint modelling, the simulation of 12 neural circuits, the CPG loci characterising stimuli-inducing alternating movements and changes in polarity stimulation signals in rat hindlimbs, and leg-state change movements. The feasibility and effectiveness of the CPG neural network were verified by recording the electromyographic burst-release mode of the flexor and extensor muscles of the knee joints during CPG electrical stimulation. The results revealed that the output pattern of the CPG presented stable rhythm and coordination characteristics. The 12-neuron CPG model based on the improved VDP equation realised single-point control while significantly reducing the number of stimulation electrodes in the gait training of spinal cord injury patients. We believe that this study advances motor function recovery in rehabilitation medicine.

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Acknowledgements

We thank the National Natural Science Foundation of China (61534003, 81371663) and the Opening Project of State Key Laboratory of Bioelectronics in Southeast University for funding this project.

Funding

This research was also supported by the ‘Six talents peaks’ project (SWYY-116), the ‘226 Engineering’ Research Project of Nantong Government, and the Postgraduate Research & Practice Innovation Program of Jiangsu Province, China (KYCX21_3085).

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Authors and Affiliations

  1. School of Information Science and Technology, Nantong University, 9 Seyuan Road, Nantong, 226019, Jiangsu Province, China

    Xiaoyan Shen, Yan Wu, Xiongjie Lou, Zhiling Li, Lei Ma & Xiongheng Bian

  2. Nantong Research Institute for Advanced Communication Technologies, Nantong, Jiangsu, China

    Xiaoyan Shen

  3. Co-Innovation Center of Neuroregeneration, Nantong University, Nantong, Jiangsu, China

    Xiaoyan Shen

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  1. Xiaoyan Shen
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Shen, X., Wu, Y., Lou, X. et al. Central pattern generator network model for the alternating hind limb gait of rats based on the modified Van der Pol equation. Med Biol Eng Comput 61, 555–566 (2023). https://doi.org/10.1007/s11517-022-02734-6

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