生物神经网络中的运动和记忆功能

N. Ishii, K. Naka
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引用次数: 5

摘要

不对称的神经网络显示在生物神经网络,鲶鱼视网膜。人们提出了几种检测生物系统运动的机制。运动的Hassenstein和Reichardt网络(1956)和Barlow和Levick网络(1965)与这里发展的不对称网络相似。为了明确这些不对称网络之间的区别,我们应用了N. Wiener开发的非线性分析。然后,我们可以推导出/spl alpha/-运动方程,该方程显示了运动方向。在运动过程中,我们还可以推导出运动方程,这意味着无论参数/spl α /如何,运动都保持不变。通过对生物非对称神经网络的分析,表明非对称神经网络在视网膜水平上具有优异的空间信息处理能力。应用非线性分析方法对对称网络进行了讨论。在对称神经网络中,我们认为需要记忆功能来感知运动。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Movement and memory function in biological neural networks
Asymmetrical neural networks are shown in a biological neural network, the catfish retina. Several mechanisms have been proposed for the detection of motion in biological system. Hassenstein and Reichardt network (1956) and Barlow and Levick network (1965) of movements are similar to the asymmetrical network developed here. To make clear the difference among these asymmetrical networks, we applied nonlinear analysis developed by N. Wiener. Then, we can derive the /spl alpha/-equation of movement, which shows the direction of movement. During the movement, we also can derive the movement equation, which implies that the movement holds regardless of the parameter /spl alpha/. By analyzing the biological asymmetric neural networks, it is shown that the asymmetric networks are excellent in the ability of spatial information processing on the retinal level. The symmetric network was discussed by applying nonlinear analysis. In the symmetric neural network, it was suggested that memory function is needed to perceive the movement.<>
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