https://doi.org/10.1140/epjs/s11734-025-01824-4
Regular Article
A discrete piezoelectric neuron and its network dynamics
1
Department of Physics, Lanzhou University of Technology, 730050, Lanzhou, China
2
School of Science, Chongqing University of Posts and Telecommunications, 430065, Chongqing, China
Received:
24
April
2025
Accepted:
19
July
2025
Published online:
27
July
2025
Shape deformation of flexible cell membrane can modify the pumping between intracellular and extracellular ions, and the change of membrane potential is similar to the generation of piezoelectric materials. In this work, two simple nonlinear circuits are coupled to build a functional neural circuit by connecting the output ends for the capacitors via a piezoelectric device, which can mimic the electrical activities of a piezoelectric membrane of a neuron. Circuit equations and field energy are defined, and then an equivalent neuron model with two capacitive variables and sensitive to piezoelectric stimulus (or acoustic wave) is obtained. Based on the exact definition of energy function for the neuron, linear transformation is applied to convert the neuron with piezoelectric membrane into an equivalent discrete model, and discrete energy function is defined as well. Noisy excitation is applied to detect the occurrence of coherence resonance in the discrete neuron, and then an adaptive control law is activated to control the mode transition in the neural activities. Finally, the same discrete neurons are clustered to build a neural network for exploring the collective behaviors by detecting its pattern formation and synchronization stability, which is discerned by calculating the distribution of synchronization factors vs. one bifurcation parameter. This work provides complete guidance for building reliable biophysical neuron models in continuous and discrete forms, and then the models can be coupled to investigate the network dynamics under self-organization.
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© The Author(s), under exclusive licence to EDP Sciences, Springer-Verlag GmbH Germany, part of Springer Nature 2025
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
