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神经科学中的随机网络模型:献给杰克·考恩的纪念文集。特刊引言。

Stochastic Network Models in Neuroscience: A Festschrift for Jack Cowan. Introduction to the Special Issue.

作者信息

Bressloff Paul C, Ermentrout Bard, Faugeras Olivier, Thomas Peter J

机构信息

Department of Mathematics, University of Utah, 155 South 1400 East, Salt Lake City, UT, 84112, USA.

Department of Mathematics, University of Pittsburgh, Pittsburgh, PA, 15260, USA.

出版信息

J Math Neurosci. 2016 Dec;6(1):4. doi: 10.1186/s13408-016-0036-y. Epub 2016 Apr 4.

DOI:10.1186/s13408-016-0036-y
PMID:27043152
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4820414/
Abstract

Jack Cowan's remarkable career has spanned, and molded, the development of neuroscience as a quantitative and mathematical discipline combining deep theoretical contributions, rigorous mathematical work and groundbreaking biological insights. The Banff International Research Station hosted a workshop in his honor, on Stochastic Network Models of Neocortex, July 17-24, 2014. This accompanying Festschrift celebrates Cowan's contributions by assembling current research in stochastic phenomena in neural networks. It combines historical perspectives with new results including applications to epilepsy, path-integral methods, stochastic synchronization, higher-order correlation analysis, and pattern formation in visual cortex.

摘要

杰克·考恩卓越的职业生涯贯穿并塑造了神经科学作为一门定量和数学学科的发展,他作出了深刻的理论贡献、进行了严谨的数学研究并带来了开创性的生物学见解。2014年7月17日至24日,班夫国际研究站举办了一场以他的名义召开的关于新皮质随机网络模型的研讨会。这本随附的纪念文集通过汇集神经网络中随机现象的当前研究来颂扬考恩的贡献。它将历史观点与新成果相结合,包括在癫痫中的应用、路径积分方法、随机同步、高阶相关性分析以及视觉皮层中的模式形成。

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本文引用的文献

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Wilson-Cowan Equations for Neocortical Dynamics.新皮层动力学的威尔逊-考恩方程
J Math Neurosci. 2016 Dec;6(1):1. doi: 10.1186/s13408-015-0034-5. Epub 2016 Jan 4.
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A Simple Mechanism for Beyond-Pairwise Correlations in Integrate-and-Fire Neurons.积分发放神经元中超越成对相关性的一种简单机制。
J Math Neurosci. 2015 Dec;5(1):30. doi: 10.1186/s13408-015-0030-9. Epub 2015 Sep 1.
3
Stochastic Synchronization in Purkinje Cells with Feedforward Inhibition Could Be Studied with Equivalent Phase-Response Curves.具有前馈抑制的浦肯野细胞中的随机同步可通过等效相位响应曲线进行研究。
J Math Neurosci. 2015 Dec;5(1):25. doi: 10.1186/s13408-015-0025-6. Epub 2015 Jun 19.
4
Orientation Maps in V1 and Non-Euclidean Geometry.初级视皮层中的方位地图与非欧几里得几何
J Math Neurosci. 2015 Dec;5(1):24. doi: 10.1186/s13408-015-0024-7. Epub 2015 Jun 17.
5
On the Effects on Cortical Spontaneous Activity of the Symmetries of the Network of Pinwheels in Visual Area V1.关于视觉区域V1中视皮层模块网络对称性对皮层自发活动的影响
J Math Neurosci. 2015 Dec;5(1):23. doi: 10.1186/s13408-015-0023-8. Epub 2015 May 30.
6
Noise-induced precursors of state transitions in the stochastic Wilson-cowan model.随机威尔逊-考恩模型中噪声诱导的状态转变先兆
J Math Neurosci. 2015 Apr 8;5:9. doi: 10.1186/s13408-015-0021-x. eCollection 2015.
7
Path integral methods for stochastic differential equations.随机微分方程的路径积分方法。
J Math Neurosci. 2015 Mar 24;5:8. doi: 10.1186/s13408-015-0018-5. eCollection 2015.
8
Modeling focal epileptic activity in the Wilson-cowan model with depolarization block.在具有去极化阻滞的威尔逊-考恩模型中模拟局灶性癫痫活动。
J Math Neurosci. 2015 Mar 27;5:7. doi: 10.1186/s13408-015-0019-4. eCollection 2015.
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