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Spike-sorting analysis of neural electrical signals evoked by acupuncture based on model

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Abstract

Acupuncturing the Zusanli (ST 36) point with different types of manual acupuncture manipulations (MAs) and different frequencies can evoke a lot of neural response activities in spinal dorsal root neurons. The action potential is the basic unit of communication in the neural response process. With the rapid development of the electrode acquisition technology, we can simultaneously obtain neural electrical signals of multiple neurons in the target area. So it is crucial to extract spike trains of each neuron from raw recorded data. To solve the problem of variability of the spike waveform, this paper adopts a optimization algorithm based on model to improve the wave-cluster algorithm, which can provide higher accuracy and reliability. Further, through this optimization algorithm, we make a statistical analysis on spike events evoked by different MAs. Results suggest that numbers of response spikes under reinforcing manipulations are far more than reducing manipulations, which mainly embody in synchronous spike activities.

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Acknowledgments

We wish to thank the anonymous reviewers for constructive and helpful comments. This paper is supported by the National Natural Science Foundation of China (Grants No. 61801328, 61871287, 61671320 and 62071324), the Natural Science Foundation of Tianjin, China (Grants No. 18JCYBJC88200, 17JCQNJC03700, 18JCQNJC04700), and Tianjin Municipal Special Program of Talents Development for Excellent Youth Scholars (Grants No. TJTZJH-QNBJRC-2-21).

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Authors and Affiliations

  1. Tianjin Key Laboratory of Information Sensing & Intelligent Control, School of Automation and Electrical Engineering, Tianjin University of Technology and Education, Tianjin, People’s Republic of China

    Qing Qin, Yanqiu Che, Chunxiao Han, Yingmei Qin & Ruofan Wang

  2. School of Electrical and Information Engineering, Tianjin University, Tianjin, People’s Republic of China

    Yajiao Liu & Jiang Wang

  3. China Academy of Electronics and Information Technology, Beijing, People’s Republic of China

    Bonan Shan

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  1. Qing Qin
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  2. Yajiao Liu
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  3. Bonan Shan
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  4. Yanqiu Che
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  6. Yingmei Qin
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  7. Ruofan Wang
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  8. Jiang Wang
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Correspondence to Jiang Wang.

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Qin, Q., Liu, Y., Shan, B. et al. Spike-sorting analysis of neural electrical signals evoked by acupuncture based on model. Cogn Neurodyn 15, 131–140 (2021). https://doi.org/10.1007/s11571-020-09650-1

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  • DOI: https://doi.org/10.1007/s11571-020-09650-1

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