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视网膜拓扑学的随机模型:一种自组织过程。

A stochastic model of retinotopy: a self organizing process.

作者信息

Cottrell M, Fort J C

出版信息

Biol Cybern. 1986;53(6):405-11. doi: 10.1007/BF00318206.

DOI:10.1007/BF00318206
PMID:3697410
Abstract

Following Kohonen and using the Hebb principle, we define a self organizing stochastic process, which is a simple modelization of the retinotopy, i.e. the establishment of well-ordered connexions between the retina and the cortex. We give some mathematical results about convergence of this process. These results are illustrated by computer simulations.

摘要

遵循科霍宁并运用赫布原理,我们定义了一个自组织随机过程,它是视网膜拓扑学的一个简单模型,即视网膜与皮层之间建立有序连接。我们给出了关于这个过程收敛性的一些数学结果。这些结果通过计算机模拟得到了说明。

相似文献

1
A stochastic model of retinotopy: a self organizing process.视网膜拓扑学的随机模型:一种自组织过程。
Biol Cybern. 1986;53(6):405-11. doi: 10.1007/BF00318206.
2
Inverse retinotopy: inferring the visual content of images from brain activation patterns.逆向视网膜拓扑映射:从大脑激活模式推断图像的视觉内容。
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A neuronal subsystem in the cat's area 18 lacks retinotopy.
Brain Res. 1987 Apr 28;410(1):199-203. doi: 10.1016/s0006-8993(87)80047-1.
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[Visual information processing from the retina to the prefrontal cortex].[从视网膜到前额叶皮层的视觉信息处理]
Shinrigaku Kenkyu. 1986 Feb;56(6):365-78. doi: 10.4992/jjpsy.56.365.
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The visual perception of motion in depth.深度运动的视觉感知。
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Texture discrimination does not occur at the cyclopean retina.纹理辨别并非发生在双眼单视界视网膜。
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An overall description of retinotopic mapping in the cat's visual cortex areas 17, 18, and 19.猫视觉皮层17、18和19区视网膜拓扑映射的总体描述。
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引用本文的文献

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The neural development and organization of letter recognition: evidence from functional neuroimaging, computational modeling, and behavioral studies.字母识别的神经发育与组织:来自功能神经影像学、计算建模及行为研究的证据。
Proc Natl Acad Sci U S A. 1998 Feb 3;95(3):847-52. doi: 10.1073/pnas.95.3.847.
2
Brain localization for arbitrary stimulus categories: a simple account based on Hebbian learning.任意刺激类别的脑定位:基于赫布学习的简单解释。
Proc Natl Acad Sci U S A. 1995 Dec 19;92(26):12370-3. doi: 10.1073/pnas.92.26.12370.
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Pattern recognition and classification of images of biological macromolecules using artificial neural networks.

本文引用的文献

1
The extended branch-arrow model of the formation of retino-tectal connections.视网膜-顶盖连接形成的扩展分支-箭头模型。
Biol Cybern. 1982;45(3):157-75. doi: 10.1007/BF00336189.
2
Self-organizing mechanism for the formation of ordered neural mappings.
Biol Cybern. 1984;51(2):93-101. doi: 10.1007/BF00357922.
3
A marker induction mechanism for the establishment of ordered neural mappings: its application to the retinotectal problem.
Philos Trans R Soc Lond B Biol Sci. 1979 Nov 1;287(1021):203-43. doi: 10.1098/rstb.1979.0056.
使用人工神经网络对生物大分子图像进行模式识别和分类
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Self-organizing maps for internal representations.
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On the rate of convergence in topology preserving neural networks.关于拓扑保持神经网络中的收敛速率。
Biol Cybern. 1991;65(1):55-63. doi: 10.1007/BF00197290.