• 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

两群神经元场模型中局域持久活动态的产生与消除。

Generation and annihilation of localized persistent-activity states in a two-population neural-field model.

机构信息

Department of Mathematical Sciences and Technology, Norwegian University of Life Sciences, P.O. Box 5003, N-1432 Ås, Norway.

出版信息

Neural Netw. 2013 Oct;46:75-90. doi: 10.1016/j.neunet.2013.04.012. Epub 2013 May 6.

DOI:10.1016/j.neunet.2013.04.012
PMID:23708672
Abstract

We investigate the generation and annihilation of persistent localized activity states, so-called bumps, in response to transient spatiotemporal external input in a two-population neural-field model of the Wilson-Cowan type. Such persistent cortical states have been implicated as a biological substrate for short-term working memory, that is, the ability to store stimulus-related information for a few seconds and discard it once it is no longer relevant. In previous studies of the same model it has been established that the stability of bump states hinges on the relative inhibitory constant τ, i.e., the ratio of the time constants governing the dynamics of the inhibitory and excitatory populations: persistent bump states are typically only stable for values of τ smaller than a critical value τcr. We find here that τ is also a key parameter determining whether a transient input can generate a persistent bump state (in the regime where τ<τcr) or not. For small values of τ generation of the persistent states is found to depend only on the overall strength of the transient input, i.e., as long as the magnitude and duration of the excitatory transient input are larger and/or long enough, the persistent state will be activated. For higher values of τ we find that only specific combinations of amplitude and duration leads to persistent activation. For the corresponding annihilation process, no such delicate selectivity on the transient input is observed.

摘要

我们研究了在威尔逊-考恩(Wilson-Cowan)型双种群神经场模型中,对短暂的时空外部输入,持久局域活动状态(所谓的“驼峰”)的产生和消除。这种持久的皮质状态被认为是短期工作记忆的生物学基础,即能够在几秒钟内存储与刺激相关的信息,并在不再相关时将其丢弃的能力。在对同一模型的先前研究中,已经确定驼峰状态的稳定性取决于相对抑制常数τ,即控制抑制和兴奋种群动态的时间常数之比:持久的驼峰状态通常仅在τ小于临界值τcr的情况下稳定。我们在这里发现,τ也是决定瞬态输入是否可以产生持久驼峰状态(在τ<τcr的范围内)的关键参数。对于较小的τ值,持久状态的产生仅取决于瞬态输入的整体强度,即只要兴奋性瞬态输入的幅度和持续时间足够大且/或足够长,持久状态就会被激活。对于更高的τ值,我们发现只有特定的幅度和持续时间组合才会导致持久激活。对于相应的消除过程,在瞬态输入中没有观察到这种微妙的选择性。

相似文献

1
Generation and annihilation of localized persistent-activity states in a two-population neural-field model.两群神经元场模型中局域持久活动态的产生与消除。
Neural Netw. 2013 Oct;46:75-90. doi: 10.1016/j.neunet.2013.04.012. Epub 2013 May 6.
2
Background-activity-dependent properties of a network model for working memory that incorporates cellular bistability.包含细胞双稳性的工作记忆网络模型的背景活动依赖特性。
Biol Cybern. 2005 Aug;93(2):109-18. doi: 10.1007/s00422-005-0543-5. Epub 2005 Apr 1.
3
Mean-driven and fluctuation-driven persistent activity in recurrent networks.循环网络中均值驱动和波动驱动的持续活动。
Neural Comput. 2007 Jan;19(1):1-46. doi: 10.1162/neco.2007.19.1.1.
4
Stationary bumps in networks of spiking neurons.脉冲神经元网络中的静止波峰。
Neural Comput. 2001 Jul;13(7):1473-94. doi: 10.1162/089976601750264974.
5
Orientation tuning properties of simple cells in area V1 derived from an approximate analysis of nonlinear neural field models.基于非线性神经场模型的近似分析得出的V1区简单细胞的方向调谐特性。
Neural Comput. 2001 Aug;13(8):1721-47. doi: 10.1162/08997660152469323.
6
Persistent neural states: stationary localized activity patterns in nonlinear continuous n-population, q-dimensional neural networks.持续神经状态:非线性连续n种群、q维神经网络中的静态局部活动模式。
Neural Comput. 2009 Jan;21(1):147-87. doi: 10.1162/neco.2008.12-07-660.
7
Power-law neuronal fluctuations in a recurrent network model of parametric working memory.参数化工作记忆循环网络模型中的幂律神经元波动。
J Neurophysiol. 2006 Feb;95(2):1099-114. doi: 10.1152/jn.00491.2005. Epub 2005 Oct 19.
8
New patterns of activity in a pair of interacting excitatory-inhibitory neural fields.一对相互作用的兴奋性抑制性神经场中的新活动模式。
Phys Rev Lett. 2011 Nov 25;107(22):228103. doi: 10.1103/PhysRevLett.107.228103. Epub 2011 Nov 21.
9
A neural circuit basis for spatial working memory.空间工作记忆的神经回路基础。
Neuroscientist. 2004 Dec;10(6):553-65. doi: 10.1177/1073858404268742.
10
Cortical network modeling: analytical methods for firing rates and some properties of networks of LIF neurons.皮层网络建模:LIF神经元网络放电率的分析方法及网络的一些特性
J Physiol Paris. 2006 Jul-Sep;100(1-3):88-99. doi: 10.1016/j.jphysparis.2006.09.001. Epub 2006 Oct 24.