• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利：CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法，用中文像聊天一样搜索，搜遍4000万医学文献。AI智能推荐，让科研检索更轻松。

立即免费搜索

文件翻译

保留排版，准确专业，支持PDF/Word/PPT等文件格式，支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述，25分钟生成高质量综述，智能提取关键信息，辅助科研写作。

立即免费体验

高斯噪声诱导的网络组织化 FitzHugh-Nagumo 模型中的自发性活动。

Spontaneous Activity Induced by Gaussian Noise in the Network-Organized FitzHugh-Nagumo Model.

机构信息

School of Science, Xuchang University, Xuchang, Henan 461000, China.

School of Mathematics and Statistics, Northwestern Polytechnical University, Xi'an, 710072 Shaanxi, China.

出版信息

Neural Plast. 2020 Nov 24;2020:6651441. doi: 10.1155/2020/6651441. eCollection 2020.

DOI:10.1155/2020/6651441
PMID:33299394
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7707970/
Abstract

In this paper, we show some dynamical and biological mechanisms of the short-term memory (the fixed point attractor) through the toggle switch in the FitzHugh-Nagumo model (FN). Firstly, we obtain the bistable conditions, show the effect of Gaussian noise on the toggle switch, and explain the short-term memory's switch mechanism by mean first passage time (MFPT). Then, we obtain a Fokker-Planck equation and illustrate the meaning of the monostable and bistable state in the short-term memory. Furthermore, we study the toggle switch under the interaction of network and noise. Meanwhile, we show that network structure and noise play a vital role in the toggle switch based on network mean first passage time (NMFPT). And we illustrate that the modest clustering coefficient and noise are necessary to maintain memories. Finally, the numerical simulation shows that the analytical results agree with it.

摘要

本文通过在 FitzHugh-Nagumo 模型 (FN) 中的 toggle switch 展示了短期记忆（平衡点吸引子）的一些动力学和生物学机制。首先，我们得到双稳条件，展示高斯噪声对 toggle switch 的影响，并通过平均首通时间 (MFPT) 解释短期记忆的开关机制。然后，我们得到福克-普朗克方程，并阐明了短期记忆中单稳和双稳状态的含义。此外，我们研究了网络和噪声共同作用下的 toggle switch。同时，我们基于网络平均首通时间 (NMFPT) 表明网络结构和噪声在 toggle switch 中起着至关重要的作用。并且我们说明适度的聚类系数和噪声是维持记忆所必需的。最后，数值模拟表明分析结果与之相符。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/26b1/7707970/587c85d3077a/NP2020-6651441.015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/26b1/7707970/7440c47112ff/NP2020-6651441.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/26b1/7707970/108542c067ab/NP2020-6651441.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/26b1/7707970/7b0b60a4d021/NP2020-6651441.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/26b1/7707970/c23ff54868f5/NP2020-6651441.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/26b1/7707970/eb7d9f1bfe1a/NP2020-6651441.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/26b1/7707970/b1916ea89b42/NP2020-6651441.006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/26b1/7707970/bd60e04aad56/NP2020-6651441.007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/26b1/7707970/1763db1a4833/NP2020-6651441.008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/26b1/7707970/088f12a8f04a/NP2020-6651441.009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/26b1/7707970/a49d402d12f5/NP2020-6651441.010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/26b1/7707970/a85a159f954f/NP2020-6651441.011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/26b1/7707970/dde46dac442a/NP2020-6651441.012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/26b1/7707970/a28fc89bc283/NP2020-6651441.013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/26b1/7707970/f2898d4f949f/NP2020-6651441.014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/26b1/7707970/587c85d3077a/NP2020-6651441.015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/26b1/7707970/7440c47112ff/NP2020-6651441.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/26b1/7707970/108542c067ab/NP2020-6651441.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/26b1/7707970/7b0b60a4d021/NP2020-6651441.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/26b1/7707970/c23ff54868f5/NP2020-6651441.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/26b1/7707970/eb7d9f1bfe1a/NP2020-6651441.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/26b1/7707970/b1916ea89b42/NP2020-6651441.006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/26b1/7707970/bd60e04aad56/NP2020-6651441.007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/26b1/7707970/1763db1a4833/NP2020-6651441.008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/26b1/7707970/088f12a8f04a/NP2020-6651441.009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/26b1/7707970/a49d402d12f5/NP2020-6651441.010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/26b1/7707970/a85a159f954f/NP2020-6651441.011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/26b1/7707970/dde46dac442a/NP2020-6651441.012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/26b1/7707970/a28fc89bc283/NP2020-6651441.013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/26b1/7707970/f2898d4f949f/NP2020-6651441.014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/26b1/7707970/587c85d3077a/NP2020-6651441.015.jpg

相似文献

1
Spontaneous Activity Induced by Gaussian Noise in the Network-Organized FitzHugh-Nagumo Model.高斯噪声诱导的网络组织化 FitzHugh-Nagumo 模型中的自发性活动。
Neural Plast. 2020 Nov 24;2020:6651441. doi: 10.1155/2020/6651441. eCollection 2020.
2
Analytical and simulation results for stochastic Fitzhugh-Nagumo neurons and neural networks.随机Fitzhugh-Nagumo神经元和神经网络的分析与仿真结果。
J Comput Neurosci. 1998 Mar;5(1):91-113. doi: 10.1023/a:1008811814446.
3
Analytical and simulation results for the stochastic spatial Fitzhugh-Nagumo model neuron.随机空间Fitzhugh-Nagumo模型神经元的分析与模拟结果。
Neural Comput. 2008 Dec;20(12):3003-33. doi: 10.1162/neco.2008.08-07-585.
4
Global dynamics and stochastic resonance of the forced FitzHugh-Nagumo neuron model.强迫FitzHugh-Nagumo神经元模型的全局动力学与随机共振
Phys Rev E Stat Nonlin Soft Matter Phys. 2001 Mar;63(3 Pt 1):031906. doi: 10.1103/PhysRevE.63.031906. Epub 2001 Feb 26.
5
The stochastic Fitzhugh-Nagumo neuron model in the excitable regime embeds a leaky integrate-and-fire model.可激发状态下的随机Fitzhugh-Nagumo神经元模型内嵌了一个漏电积分发放模型。
J Math Biol. 2019 Jul;79(2):509-532. doi: 10.1007/s00285-019-01366-z. Epub 2019 May 2.
6
Analytical approach to the stochastic FitzHugh-Nagumo system and coherence resonance.随机FitzHugh-Nagumo系统及相干共振的分析方法
Phys Rev E Stat Phys Plasmas Fluids Relat Interdiscip Topics. 1999 Dec;60(6 Pt B):7270-6. doi: 10.1103/physreve.60.7270.
7
Effects of Lévy noise on the Fitzhugh-Nagumo model: A perspective on the maximal likely trajectories.勒维噪声对菲茨休-纳戈莫模型的影响：最大可能轨迹的视角。
J Theor Biol. 2019 Nov 7;480:166-174. doi: 10.1016/j.jtbi.2019.08.010. Epub 2019 Aug 13.
8
Emergence of chaotic attractor and anti-synchronization for two coupled monostable neurons.两个耦合单稳态神经元的混沌吸引子的出现及反同步
Chaos. 2004 Dec;14(4):1148-56. doi: 10.1063/1.1821691.
9
Variability in noise-driven integrator neurons.噪声驱动积分神经元的变异性
Phys Rev E Stat Nonlin Soft Matter Phys. 2005 Jan;71(1 Pt 1):011911. doi: 10.1103/PhysRevE.71.011911. Epub 2005 Jan 27.
10
Frequency-selective response of FitzHugh-Nagumo neuron networks via changing random edges.通过改变随机边实现的菲茨休-纳古莫神经元网络的频率选择性响应
Chaos. 2006 Dec;16(4):043107. doi: 10.1063/1.2360503.

引用本文的文献

1
Hamiltonian energy in a modified Hindmarsh-Rose model.修正的 Hindmarsh-Rose 模型中的哈密顿能量。
Front Netw Physiol. 2024 Mar 26;4:1362778. doi: 10.3389/fnetp.2024.1362778. eCollection 2024.
2
Turing instability mechanism of short-memory formation in multilayer FitzHugh-Nagumo network.多层FitzHugh-Nagumo网络中短记忆形成的图灵不稳定性机制。
Front Psychiatry. 2023 Mar 27;14:1083015. doi: 10.3389/fpsyt.2023.1083015. eCollection 2023.
3
Spatiotemporal Patterns in a General Networked Hindmarsh-Rose Model.一般网络 Hindmarsh-Rose 模型中的时空模式

本文引用的文献

1
Discrete attractor dynamics underlies persistent activity in the frontal cortex.离散吸引子动力学是额叶皮层持续活动的基础。
Nature. 2019 Feb;566(7743):212-217. doi: 10.1038/s41586-019-0919-7. Epub 2019 Feb 6.
2
A diverse range of factors affect the nature of neural representations underlying short-term memory.多种因素影响短期记忆的神经表象的本质。
Nat Neurosci. 2019 Feb;22(2):275-283. doi: 10.1038/s41593-018-0314-y. Epub 2019 Jan 24.
3
Stable and Dynamic Coding for Working Memory in Primate Prefrontal Cortex.灵长类前额叶皮层工作记忆的稳定与动态编码
Front Physiol. 2022 Jun 28;13:936982. doi: 10.3389/fphys.2022.936982. eCollection 2022.
J Neurosci. 2017 Jul 5;37(27):6503-6516. doi: 10.1523/JNEUROSCI.3364-16.2017. Epub 2017 May 30.
4
Stable population coding for working memory coexists with heterogeneous neural dynamics in prefrontal cortex.工作记忆的稳定群体编码与前额叶皮层中异质性神经动力学共存。
Proc Natl Acad Sci U S A. 2017 Jan 10;114(2):394-399. doi: 10.1073/pnas.1619449114. Epub 2016 Dec 27.
5
The Switch in a Genetic Toggle System with Lévy Noise.具有 Lévy 噪声的基因开关系统中的开关
Sci Rep. 2016 Aug 19;6:31505. doi: 10.1038/srep31505.
6
Noise and interlocking signaling pathways promote distinct transcription factor dynamics in response to different stresses.噪声和连锁信号通路促进不同应激下不同转录因子动力学的形成。
Mol Biol Cell. 2013 Jun;24(12):2045-57. doi: 10.1091/mbc.E12-12-0870. Epub 2013 Apr 24.
7
Memory without feedback in a neural network.神经网络中无反馈的记忆。
Neuron. 2009 Feb 26;61(4):621-34. doi: 10.1016/j.neuron.2008.12.012.
8
Noise-induced switches in network systems of the genetic toggle switch.基因开关网络系统中的噪声诱导开关
BMC Syst Biol. 2007 Nov 15;1:50. doi: 10.1186/1752-0509-1-50.
9
Stochastic models for regulatory networks of the genetic toggle switch.基因开关调控网络的随机模型。
Proc Natl Acad Sci U S A. 2006 May 30;103(22):8372-7. doi: 10.1073/pnas.0507818103. Epub 2006 May 19.
10
Phenotypic diversity, population growth, and information in fluctuating environments.波动环境中的表型多样性、种群增长与信息
Science. 2005 Sep 23;309(5743):2075-8. doi: 10.1126/science.1114383. Epub 2005 Aug 25.