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单个神经元的动力学和计算。

Single neuron dynamics and computation.

机构信息

Departments of Statistics and Neurobiology, University of Chicago, Chicago, USA.

Laboratoire de Physique Statistique, CNRS, University Pierre et Marie Curie, Ecole Normale Supérieure, Paris, France.

出版信息

Curr Opin Neurobiol. 2014 Apr;25:149-55. doi: 10.1016/j.conb.2014.01.005. Epub 2014 Feb 1.

Abstract

At the single neuron level, information processing involves the transformation of input spike trains into an appropriate output spike train. Building upon the classical view of a neuron as a threshold device, models have been developed in recent years that take into account the diverse electrophysiological make-up of neurons and accurately describe their input-output relations. Here, we review these recent advances and survey the computational roles that they have uncovered for various electrophysiological properties, for dendritic arbor anatomy as well as for short-term synaptic plasticity.

摘要

在单个神经元水平上,信息处理涉及将输入的尖峰序列转换为适当的输出尖峰序列。近年来,在经典的神经元作为门控装置的观点基础上,已经开发出了一些模型,这些模型考虑了神经元的多种电生理构成,并准确描述了它们的输入-输出关系。在这里,我们回顾了这些最新进展,并调查了它们为各种电生理特性、树突分支解剖结构以及短期突触可塑性所揭示的计算作用。

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