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A Linear Implementation of the Hodgkin–Huxley Neuron Model on FPGA Considering Its Dynamics

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Abstract

The study of neural cell behavior is one of the exciting fields that has attracted scientists’ attention since 1890. Accordingly, many efforts have been made to model the neural cell specifying different neuron behaviors and characteristics. These studies mainly focus on two primary targets: finding new computing paradigms and providing better models and tools for medical applications. A critical model for studying biological neurons' behavior is the Hodgkin–Huxley neuron model (HH for short), presented in 1952. In this paper, the model is realized and verified using only one multiplier with some simplification. By comparing the original and simplified HH models, the RMSE and NRMSE are 1.83 and 0.016 for neuron membrane output potential, respectively, at the injected current of 20 uA. The dynamical behaviors of the model are also studied to ensure stability. The proposed model is synthesized and implemented on an FPGA platform, where the outputs are examined, and the results are presented as proof of concept.

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Data Availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

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Authors and Affiliations

  1. Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran

    Yosef Khakipoor, Farnaz Khani & Ghader Karimian

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  1. Yosef Khakipoor
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  2. Farnaz Khani
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  3. Ghader Karimian
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Correspondence to Yosef Khakipoor.

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Khakipoor, Y., Khani, F. & Karimian, G. A Linear Implementation of the Hodgkin–Huxley Neuron Model on FPGA Considering Its Dynamics. Neural Process Lett 55, 7777–7805 (2023). https://doi.org/10.1007/s11063-023-11285-2

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  • DOI: https://doi.org/10.1007/s11063-023-11285-2

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