Theoretical Analysis and Hardware Reproduction of the Hodgkin-Huxley Bifurcation Diagram in a LAM-Based Neuron on Edge of Chaos

Research output: Contribution to journalResearch articleContributedpeer-review

Contributors

  • Yan Liang - , Hangzhou Dianzi University (Author)
  • Zhiruo Zeng - , Hangzhou Dianzi University (Author)
  • Kuixing Liu - , Hangzhou Dianzi University (Author)
  • Yuxin Yang - , Hangzhou Dianzi University (Author)
  • Yujiao Dong - , Hangzhou Dianzi University (Author)
  • Peipei Jin - , Hangzhou Dianzi University (Author)
  • Guangyi Wang - , Hangzhou Dianzi University (Author)
  • Ahmet Samil Demirkol - , Chair of Fundamentals of Electronics (Author)
  • Ronald Tetzlaff - , Chair of Fundamentals of Electronics (Author)
  • Fernando Corinto - , Polytechnic University of Turin (Author)
  • Alon Ascoli - , Polytechnic University of Turin (Author)

Abstract

Inspired by recent research reported in [1], this paper investigates the bio-inspired bifurcation patterns of a simple memristive neuron on edge of chaos. The adopted memristive neuron, comprising a DC current source, a current-controlled locally active memristor, and a capacitor, successfully reproduces the bifurcation cascade patterns observed in the Hodgkin-Huxley (H-H) neuron model, including fold limit cycle bifurcation (FLCB), subcritical Hopf bifurcation (SUB-HB), and supercritical Hopf bifurcation (SUP-HB). Through attraction basin analysis and pulse-based initial state regulation, we verify the coexistence phenomenon of stable and unstable limit cycles induced by FLCB, as well as the bistable behaviors triggered by SUB-HB. Furthermore, taking resistively coupled memristive neurons as an example, we explore the influence of the dynamics of individual neurons on the bifurcation patterns of coupled networks, where two neurons have identical parameters but different initial states. The results demonstrate that the three bifurcation modes also emerge in memristive coupled networks, and their evolutionary patterns are closely related to the dynamic behaviors of individual neurons. Finally, hardware experiments successfully reproduce the bifurcation cascade phenomenon thereby validating the correctness of theoretical analysis and simulation results.

Details

Original languageEnglish
JournalIEEE Transactions on Circuits and Systems I: Regular Papers
Publication statusE-pub ahead of print - 26 Jun 2025
Peer-reviewedYes

External IDs

ORCID /0000-0001-7436-0103/work/189704865
ORCID /0000-0002-1236-1300/work/189706014

Keywords

Keywords

  • bifurcation pattern, coupled networks, edge of chaos, Memristor, neurons