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视网膜神经节细胞的去相关和有效编码。

Decorrelation and efficient coding by retinal ganglion cells.

机构信息

Department of Brain and Cognitive Sciences, University of Rochester, Rochester, New York, USA.

出版信息

Nat Neurosci. 2012 Mar 11;15(4):628-35. doi: 10.1038/nn.3064.

Abstract

An influential theory of visual processing asserts that retinal center-surround receptive fields remove spatial correlations in the visual world, producing ganglion cell spike trains that are less redundant than the corresponding image pixels. For bright, high-contrast images, this decorrelation would enhance coding efficiency in optic nerve fibers of limited capacity. We tested the central prediction of the theory and found that the spike trains of retinal ganglion cells were indeed decorrelated compared with the visual input. However, most of the decorrelation was accomplished not by the receptive fields, but by nonlinear processing in the retina. We found that a steep response threshold enhanced efficient coding by noisy spike trains and that the effect of this nonlinearity was near optimal in both salamander and macaque retina. These results offer an explanation for the sparseness of retinal spike trains and highlight the importance of treating the full nonlinear character of neural codes.

摘要

一种有影响力的视觉处理理论认为,视网膜中心-环绕感受野去除了视觉世界中的空间相关性,产生的神经节细胞尖峰序列比相应的图像像素冗余度更低。对于明亮、高对比度的图像,这种去相关会提高有限容量视神经纤维的编码效率。我们测试了该理论的中心预测,发现与视觉输入相比,视网膜神经节细胞的尖峰序列确实存在去相关。然而,大部分去相关不是由感受野完成的,而是由视网膜中的非线性处理完成的。我们发现,陡峭的响应阈值通过噪声尖峰序列增强了有效编码,并且这种非线性的效果在蝾螈和猕猴视网膜中都接近最优。这些结果为视网膜尖峰序列的稀疏性提供了一种解释,并强调了处理神经码全非线性特征的重要性。

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