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Compact hybrid type electronic neuron and computational model of its dynamics

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Abstract

We propose a Neurosimilator, novel analog neuron circuit and mathematical model of its dynamics that both simulate with high precision the spiking behavior of known types of excitable cells. The analog circuit is compact and can be built using off-the-shelf components. This could facilitate its use in teaching neuroscience and biophysics. The circuit is scalable down to the pF-valued capacitors, presenting an advantage in research on the analog nerve fiber networks. The equations of circuit dynamics contain exponential non-linearities and Heaviside functions, so that the model combines features from the generalized adapting exponential integrate-and-fire neuron model and from the intermittent feedback Hindmarsh-Rose model, but it is not directly related to them. Our four-dimensional system (4D-Neurosimilator) simulates most of excitable cells’ spiking, bursting and chaotic behavior depending on only fewer predefined parameters. In bursting and chaotic oscillatory patterns, the model demonstrates self-adaptive energy flow redistribution. The energy expenditure amounts to ≈36 µJ per one spiking event in original model and to ≈0.63 pJ in its down-scaled version. The model has computational cost comparable to that of the Hodgkin–Huxley model, but it tends to handle noisy input stimulations more efficiently. Our work provides novel insights to the simulation of neuron’s non-linear dynamics and may constitute another choice of available model in computational neuroscience research that expands the limits of a tradeoff between accuracy, biological explainability, noise-resistance and computing time.

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Data availability

The authors declare that the data supporting the findings of this study are available within the paper. The Fortran codes and XPPAUT codes are available from the corresponding author upon request, as well as on GitHub repository: https://github.com/Shlyonsky/3D-Neurosimilator and https://github.com/Shlyonsky/4D-Neurosimilator.

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Acknowledgements

Authors would like to thank Prof. P. Gaspard for his critical reading of the manuscript and his helpful suggestions.

Funding

This study was supported by funds from the Université libre de Bruxelles.

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Authors and Affiliations

  1. Laboratoire d’Enseignement de La Physique, Faculté de Médecine, Université Libre de Bruxelles, Brussels, Belgium

    V. Shlyonsky, F. Dupuis, B. de Prelle & D. Gall

  2. Departement de Physique des Systèmes Dynamiques, Faculté des Sciences, Université Libre de Bruxelles, Brussels, Belgium

    T. Erneux

  3. BEAMS (Bio-, Electro- and Mechanical Systems) Department, Ecole Polytechnique de Bruxelles, Université Libre de Bruxelles, Brussels, Belgium

    M. Osée & A. Nonclercq

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  1. V. Shlyonsky
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Contributions

All authors contributed to the study conception. Electronic circuit was designed by DF and SV. Nodal analysis was performed by SV, PB and OM. Fortran code was written and optimized by SV and GD. Data collection and analysis were made by SV, ET, NA and PB. GD provided funding and coordinated the study. The first draft of the manuscript was written by SV and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to V. Shlyonsky.

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Shlyonsky, V., Dupuis, F., de Prelle, B. et al. Compact hybrid type electronic neuron and computational model of its dynamics. Nonlinear Dyn 112, 14343–14362 (2024). https://doi.org/10.1007/s11071-024-09772-9

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