利用CNN揭示脊椎动物视网膜的时空处理

F. Werblin, A. Jacobs
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引用次数: 23

摘要

脊椎动物的视网膜在空间和时间上进行许多高度复杂的转换。因为我们还没有足够的工具来分析这些功能,所以目前对这些转换背后的机制知之甚少。CNN首次提供了一个分析框架,在这个框架中可以预测、测量和分析这些转换。虽然传统的分析只依赖于对单个细胞的研究,但CNN使我们能够思考、操纵、生成和研究涉及大量细胞的活动模式。因此,CNN有望揭示视网膜在空间和时间上抽象和编码视觉信息的一些重要机制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using CNN to unravel space-time processing in the vertebrate retina
The vertebrate retina performs a number of highly complex transformations in space and time. Because we have not had adequate tools for analyzing these functions, little is presently known about the mechanisms underlying these transformations. CNN provides, for the first time, an analytical framework within which these transformations can be predicted, measured and analyzed. While conventional analyses have relied on studies of only single cells CNN allows us to think about, manipulate generate and study patterns of activity involving large populations of cells. Thus, CNN promises to unravel some of the important mechanisms by which the retina abstracts and encodes the visual message in space and time.<>
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