Control of spiral waves in myocardial tissue by optogenetics and temperature DOI Creative Commons
Yipeng Hu, Qianming Ding, Yonghong Wu

et al.

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

Published: June 20, 2024

Abstract Optogenetics as an emerging technology can eliminate spiral waves in myocardial tissue. The heat generated during illumination of tissue is overlooked influence. Even small fluctuations temperature may affect the action potentials cardiomyocyte. In this paper, a minimal ventricular model and simplified optogenetics are employed to study effects generation by on elimination waves. Luo-Rudy Channelrhodospin-2 light-sensitive ion channel used validate our conclusions. Weinduce drift through inhomogeneities discrete gradients illumination. inhomogeneity caused gradient inhibit Spiral medium be induced more efficiently controlling changes We emphasized importance factors optogenetic experiments, hoping that results could provide guidance for its clinical applications.

Language: Английский

Energy consumption in the synchronization of neurons coupled by electrical or memristive synapse DOI
Ying Xie, Xueqin Wang, Xuening Li

et al.

Chinese Journal of Physics, Journal Year: 2024, Volume and Issue: 90, P. 64 - 82

Published: May 22, 2024

Language: Английский

Citations

18
Synchronization behavior of memristive FitzHugh-Nagumo neurons in time-varying networks under external stimuli DOI
Weifang Huang, Yong Wu, Qianming Ding

et al.

Chaos Solitons & Fractals, Journal Year: 2025, Volume and Issue: 192, P. 116001 - 116001

Published: Jan. 10, 2025

Language: Английский

Citations

3
Synchronization of complex networks with synapse regulated by energy difference DOI
Ying Xie, Xuening Li, Xueqin Wang

et al.

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

Published: Jan. 6, 2025

Language: Английский

Citations

2
Dynamic modulation of external excitation enhance synchronization in complex neuronal network DOI
Yonghong Wu, Qianming Ding, Weifang Huang

et al.

Chaos Solitons & Fractals, Journal Year: 2024, Volume and Issue: 183, P. 114896 - 114896

Published: April 24, 2024

Language: Английский

Citations

12
A dynamic learning method for phase synchronization control in Hodgkin–Huxley neuronal networks DOI
Qianming Ding, Yonghong Wu, Weifang Huang

et al.

The European Physical Journal Special Topics, Journal Year: 2024, Volume and Issue: unknown

Published: April 23, 2024

Language: Английский

Citations

10
Community modularity structure promotes the evolution of phase clusters and chimeralike states DOI
Dong Yu, Xuening Li, Xueqin Wang

et al.

Physical review. E, Journal Year: 2025, Volume and Issue: 111(3)

Published: March 24, 2025

Community modularity structure is widely observed across various brain scales, reflecting a balance between information processing efficiency and neural wiring metabolic efficiency. Revealing the relationship community function facilitates our further understanding of brain. Here, we construct an adaptive network (ANN) consisting leaky integrate-and-fire neurons with adaptivity governed by spike-time-dependent plasticity rules. The ANN demonstrates diverse dynamic collective behaviors, including traveling waves dominated initial states, phase-cluster formations, chimeralike states. In addition to functional clustering, spontaneously organizes into structures characterized densely interconnected modules sparse interconnections. Neurons within synchronize, while those remain asynchronous, forming By encoding rhythms, segments asynchronous synchronous structural modules, leading These findings provide evidence supporting perspective that emerges from influenced in complex processes.

Language: Английский

Citations

1
Setting a double-capacitive neuron coupled with Josephson junction and piezoelectric source DOI
Yixuan Chen, Feifei Yang, Guodong Ren

et al.

Cognitive Neurodynamics, Journal Year: 2024, Volume and Issue: 18(5), P. 3125 - 3137

Published: July 2, 2024

Language: Английский

Citations

8
Collective behaviors of neural network regulated by the spatially distributed stimuli DOI
Ying Xie, Weifang Huang, Ya Jia

et al.

Physica A Statistical Mechanics and its Applications, Journal Year: 2024, Volume and Issue: 651, P. 130037 - 130037

Published: Aug. 12, 2024

Language: Английский

Citations

6
Enhancing orderly signal propagation between layers of neuronal networks through spike timing-dependent plasticity DOI
Yonghong Wu, Weifang Huang, Qianming Ding

et al.

Physics Letters A, Journal Year: 2024, Volume and Issue: 519, P. 129721 - 129721

Published: July 16, 2024

Language: Английский

Citations

4
Inverse stochastic resonance in adaptive small-world neural networks DOI
Marius E. Yamakou, Jinjie Zhu, Erik A. Martens

et al.

Chaos An Interdisciplinary Journal of Nonlinear Science, Journal Year: 2024, Volume and Issue: 34(11)

Published: Nov. 1, 2024

Inverse stochastic resonance (ISR) is a counterintuitive phenomenon where noise reduces the oscillation frequency of an oscillator to minimum occurring at intermediate intensity, and sometimes even complete absence oscillations. In neuroscience, ISR was first experimentally verified with cerebellar Purkinje neurons [Buchin et al., PLOS Comput. Biol. 12, e1005000 (2016)]. These experiments showed that enables locally optimal information transfer between input output spike train neurons. Subsequent studies have further demonstrated efficiency processing in neural networks small-world network topology. We conducted numerical investigation into impact adaptivity on noisy FitzHugh-Nagumo (FHN) neurons, operating bi-metastable regime consisting metastable fixed point limit cycle. Our results show degree highly dependent value FHN model's timescale separation parameter ε. The structure undergoes dynamic adaptation via mechanisms either spike-time-dependent plasticity (STDP) potentiation-/depression-domination P or homeostatic structural (HSP) rewiring F. demonstrate both STDP HSP amplify effect when ε lies within bi-stability region Specifically, larger values regime, higher frequencies F are observed enhance (weak) synaptic intensities, while consistent depression-domination (potentiation-domination) consistently (deteriorate) ISR. Moreover, although control parameters may jointly ISR, has greater improving compared findings inform future enhancement strategies artificial circuits, aiming optimize local trains neuromorphic systems prompt venues for networks.

Language: Английский

Citations

4