Coexistence and control of firing patterns in a heterogeneous neuronal network coupled by memristive synapses DOI Creative Commons
Jinyi Wu, Zhijun Li, Yong‐Hong Lan

et al.

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 9, 2024

Abstract To simulate the complex electrical activity exhibited in biological neuronal networks more accurately, a heterogeneous neuron-coupled network is established this study. This consists of an Hindmarsh-Rose (HR) neuron and tri-cell Hopfield Neural Network (HNN) interconnected via three memristive synapses. The dynamical behaviors coupled are investigated by means bifurcation diagram, Lyapunov exponent, time series phase portrait. firing pattern transitions also revealed as synaptic coupling strengths vary. Furthermore, coexisting patterns, including period-1, period-2, period-4 chaotic firing, observed manipulating initial conditions. Especially, linear augmentation strategy introduced to target desired pattern. Both numerical simulations hardware experimental tests demonstrate that method can not only select but promote synchronous activities within network.

Language: Английский

Jointed pendulums driven by a neural circuit, electromechanical arm model approach DOI
Yitong Guo, Chunni Wang, Jun Ma

et al.

Chaos Solitons & Fractals, Journal Year: 2024, Volume and Issue: 189, P. 115739 - 115739

Published: Nov. 18, 2024

Citations

5
Model approach of artificial muscle and leg movements DOI
Yitong Guo, Chunni Wang, Jun Ma

et al.

Physics Letters A, Journal Year: 2024, Volume and Issue: 529, P. 130069 - 130069

Published: Nov. 20, 2024

Language: Английский

Citations

4
Coexistence and control of firing patterns in a heterogeneous neuron-coupled network by memristive synapses DOI Creative Commons
Jinyi Wu,

Zhijun Li,

Yong‐Hong Lan

et al.

Nonlinear Dynamics, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 8, 2025

Language: Английский

Citations

0
Edge-of-Chaos Kernel and Dynamic Analysis of a Hopfield Neural Network with a Locally Active Memristor DOI Open Access
Li Zhang, Yike Ma, R Jiang

et al.

Electronics, Journal Year: 2025, Volume and Issue: 14(4), P. 766 - 766

Published: Feb. 16, 2025

Locally active memristors with an Edge-of-Chaos kernel (EOCK) represent a significant advancement in the simulation of neuromorphic dynamics. However, current research on EOCK remains at circuit level, without further analysis their feasibility. In this context, we designed memristor and installed it third-order circuit, where showed local activity stability under defined voltage inductance parameters. This behavior ensured that by varying input inductance, could effectively simulate various neural activities, including inhibitory postsynaptic potential chaotic waveforms. By subsequently integrating into Hopfield network (HNN) framework substituting self-coupling weight, observed rich spectrum dynamic behaviors, rare phenomenon antimonotonicity bubble bifurcation. Finally, used hardware circuits to realize these generated phenomena, confirming feasibility memristor. introducing HNN studying its implementation, study provides theoretical insights empirical basis for developing systems replicate complexity human brain functions. reference development application future.

Language: Английский

Citations

0
A memristive neuron with nonlinear membranes and network patterns DOI

Binchi Wang,

Yaquan Wang, Xiaofeng Zhang

et al.

Physics Letters A, Journal Year: 2025, Volume and Issue: 540, P. 130390 - 130390

Published: Feb. 22, 2025

Language: Английский

Citations

0
Neurodynamic behavior of hippocampal CA1 neuron model driven by external current stimulation DOI
Guizhi Xu, Huan Liu, Youxi Wu

et al.

Chinese Journal of Physics, Journal Year: 2025, Volume and Issue: unknown

Published: March 1, 2025

Language: Английский

Citations

0
Multiple generalized stability of nonlinear delayed systems subject to impulsive disturbance DOI
Fanghai Zhang,

C. Zhan

Cognitive Neurodynamics, Journal Year: 2025, Volume and Issue: 19(1)

Published: April 19, 2025

Language: Английский

Citations

0
Coherence resonance, parameter estimation and self-regulation in a thermal sensitive neuron DOI Creative Commons
Qun Guo,

Ping Zhou,

Xiaofeng Zhang

et al.

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 5, 2024

Abstract In this work, two capacitors connected by a thermistor are used to explore the electrical property of double-layer membrane in neuron, which is sensitive changes temperature and capacitive variables measure potentials for inner outer membrane. The circuit characteristic energy definition neural its equivalent neuron model oscillator form clarified from physical aspect. Considering shape deformation cell under external stimuli injection, intrinsic parameters can be controlled with adaptive growth flow, an control law proposed regulate firing modes accompanying shift. presence noisy excitation, coherence resonance induced confirmed taming noise intensity carefully. distributions CV (coefficient variability) average value < H > vs. provide feasible way predict even stochastic activities. Adaptive parameter observers designed identify unknown model. Our results helpful design thermal-sensitive artificial injecting thermosensitive medium between capacitor plates.

Language: Английский

Citations

0
Coexistence and control of firing patterns in a heterogeneous neuronal network coupled by memristive synapses DOI Creative Commons
Jinyi Wu, Zhijun Li, Yong‐Hong Lan

et al.

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 9, 2024

Abstract To simulate the complex electrical activity exhibited in biological neuronal networks more accurately, a heterogeneous neuron-coupled network is established this study. This consists of an Hindmarsh-Rose (HR) neuron and tri-cell Hopfield Neural Network (HNN) interconnected via three memristive synapses. The dynamical behaviors coupled are investigated by means bifurcation diagram, Lyapunov exponent, time series phase portrait. firing pattern transitions also revealed as synaptic coupling strengths vary. Furthermore, coexisting patterns, including period-1, period-2, period-4 chaotic firing, observed manipulating initial conditions. Especially, linear augmentation strategy introduced to target desired pattern. Both numerical simulations hardware experimental tests demonstrate that method can not only select but promote synchronous activities within network.

Language: Английский

Citations

0