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.
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.
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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