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利用统计信号对猫视觉系统中的神经网络进行分析——简单细胞和复杂细胞。第二部分。

Analysis of neuronal networks in the visual system of the cat using statistical signals--simple and complex cells. Part II.

作者信息

Hoffmann K P, von Seelen W

出版信息

Biol Cybern. 1978 Dec 5;31(3):175-85. doi: 10.1007/BF00337004.

Abstract

Superimposing additively a two-dimensional noise process to deterministic input signals (bars) the neurons of area 17 show a class-specific reaction for the task of signal extraction. Moving both parts of the signals simultaneously and varying the signal to noise ratio (S/N) the simple cells achieve the same performance as resulted from the psychophysical experiment. Type I complex cells extract moving deterministic signals (i.e. bars) from the stationary noise, whereas in the answers of Type II complex cells the statistical parts of the signals predominate. Considering the different cell types each as a series of a linear and a nonlinear system one obtains the cell specific space-time frequency and the amplitude characteristics.

摘要

将二维噪声过程叠加到确定性输入信号(条纹)上,17区的神经元在信号提取任务中表现出特定类别的反应。同时移动信号的两个部分并改变信噪比(S/N),简单细胞实现了与心理物理学实验相同的性能。I型复杂细胞从静止噪声中提取移动的确定性信号(即条纹),而在II型复杂细胞的反应中,信号的统计部分占主导。将每种不同的细胞类型视为一个线性和非线性系统的序列,可以得到细胞特定的时空频率和幅度特性。

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