PATTERN-RECOGNITION COMPUTATION USING ACTION-POTENTIAL TIMING FOR STIMULUS REPRESENTATION
PATTERN-RECOGNITION COMPUTATION USING ACTION-POTENTIAL TIMING FOR STIMULUS REPRESENTATION
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DOI：
10.1038/376033a0
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发表时间：
1995-07-06
期刊：
影响因子：
64.8
通讯作者：
HOPFIELD, JJ
中科院分区：
文献类型：
--
作者：
HOPFIELD, JJ
描述了一种计算模型，其中变量的大小由动作电位发生的明确时间来表示，而非更常见的神经元“放电频率”。对模拟变量集模式的比较是由一个网络完成的，该网络对不同的信息路径使用不同的延迟。这种计算模式解释了一种神经结构方案如何可用于非常不同的感觉模态以及看似不同的计算。哺乳动物嗅觉系统的振荡和解剖结构依据这种表示有一个简单的解释，并且与听觉系统中的处理相关。单电极记录将难以检测到这种神经计算。这种类型的识别“单元”的反应更像是径向基函数单元，而不是基本的S型单元。
A computational model is described in which the sizes of variables are represented by the explicit times at which action potentials occur, rather than by the more usual 'firing rate' of neurons. The comparison of patterns over sets of analogue variables is done by a network using different delays for different information paths. This mode of computation explains how one scheme of neuroarchitecture can be used for very different sensory modalities and seemingly different computations. The oscillations and anatomy of the mammalian olfactory systems have a simple interpretation in terms of this representation, and relate to processing in the auditory system. Single-electrode recording would plot detect such neural computing. Recognition 'units' in this style respond more like radial basis function units than elementary sigmoid un its.