How to compare two quantities? A computational model of flutter discrimination
How to compare two quantities? A computational model of flutter discrimination
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DOI：
10.1162/jocn.2007.19.3.409
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发表时间：
2007-03-01
影响因子：
3.2
通讯作者：
Verguts, Tom
中科院分区：
文献类型：
--
作者：
Verguts, Tom
在神经水平上已经被深入研究的任务是颤动辨别。我认为，颤振歧视需要一个时间分配问题和数量比较问题的组合，并提出了一个神经网络模型如何解决这些问题。该网络结合了无监督和单层监督训练。无监督部分聚类输入特征（刺激+时间窗口），有监督部分对所得聚类进行分类。训练后，该模型显示出与神经和行为特性的良好拟合。新的预测概述，并指出与其他认知领域的联系。
A task that has been intensively studied at the neural level is flutter discrimination. I argue that flutter discrimination entails a combination of a temporal assignment problem and a quantity comparison problem, and propose a neural network model of how these problems are solved. The network combines unsupervised and one-layer supervised training. The unsupervised part clusters input features (stimulus + time window) and the supervised part categorizes the resulting clusters. After training, the model shows a good fit with both neural and behavioral properties. New predictions are outlined and links with other cognitive domains are pointed out.