Learning about environmental geometry: A flaw in Miller and Shettleworth's (2007) operant model
Learning about environmental geometry: A flaw in Miller and Shettleworth's (2007) operant model
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DOI：
10.1037/0097-7403.34.3.415
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发表时间：
2008-07-01
影响因子：
1.3
通讯作者：
Dupuis, Brian
中科院分区：
文献类型：
--
作者：
Dawson, Michael R. W.;Kelly, Debbie M.;Dupuis, Brian
许多研究都探讨了人类和其他动物在封闭环境中迷失方向后如何重新建立方向感。结果表明，机舱外壳的几何形状通常被编码，有时会排除特征线索，这导致人们建议几何形状可能被编码在专用的几何模块中。最近，Miller 和 Shettleworth（2007）提出，重新定向任务应被视为一项操作性任务，他们提出了一个关联操作模型，该模型似乎可以解释重新定向研究中的许多实证结果。在本文中，我们表明，尽管米勒和谢特尔沃斯对重新定向任务的操作性质的见解可能是合理的，但他们的数学模型存在严重缺陷。我们通过模拟来说明该缺陷的影响。我们还提出了一个简单神经网络的输出。感知器可用于在重新定向任务中进行操作性学习，并可以解决 Miller 和 Shettleworth 模型中的问题。
Many Studies have examined how humans and other animals reestablish a sense of direction following disorientation in enclosed environments. Results showing that geometric shape of ail enclosure is typically encoded, sometimes to the exclusion of featural cues, have led to suggestions that geometry might be encoded in a dedicated geometric module. Recently, Miller and Shettleworth (2007) proposed that the reorientation task be viewed as an operant task and they presented an associative operant model that appears to account for many empirical findings from reorientation Studies. In this paper we show that, although Miller and Shettleworth's insights into the operant nature of the reorientation task may be sound, their mathematical model has a serious flaw. We present simulations to illustrate the implications of the flaw. We also propose that the output of a simple neural network. the perceptron, can be used to conduct operant learning within the reorientation task and can solve the problem in Miller and Shettleworth's model.