选择性视觉注意的转移:朝向潜在的神经回路。

Human neurobiology Pub Date : 1985-01-01
C Koch, S Ullman
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引用次数: 0

摘要

心理物理和生理证据表明,灵长类动物和人类的视觉系统已经进化出一种特殊的处理焦点,可以在视觉场景中移动。这项研究解决了神经元样元素的简单网络如何解释与这种选择性视觉注意转移相关的各种现象的问题。具体来说,我们提出了以下建议:(1)在不同的地形图中平行地表示一些基本特征,如颜色、方位、运动方向、视差等,称为早期表示。(2)从早期的地形表示到更中心的非地形表示存在选择性映射,这样在任何时刻,中心表示都只包含视觉场景中单个位置的属性,即所选位置。我们认为这种映射是早期选择性视觉注意的主要表现。选择性注意的一个功能是将来自不同地图的信息融合成一个连贯的整体。(3)某些选择规则决定了哪些位置将被映射到中心表示中。主要规则是利用早期表现中位置的显著性,通过所谓的“赢者通吃”网络实现。抑制该网络中选定的位置将导致自动向下一个最明显的位置移动。其他规则是接近性和相似性偏好。我们讨论了这些规则如何在神经元样网络中实现,并提出了从视觉皮层到LGN的广泛反向投影的可能作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Shifts in selective visual attention: towards the underlying neural circuitry.

Psychophysical and physiological evidence indicates that the visual system of primates and humans has evolved a specialized processing focus moving across the visual scene. This study addresses the question of how simple networks of neuron-like elements can account for a variety of phenomena associated with this shift of selective visual attention. Specifically, we propose the following: (1) A number of elementary features, such as color, orientation, direction of movement, disparity etc. are represented in parallel in different topographical maps, called the early representation. (2) There exists a selective mapping from the early topographic representation into a more central non-topographic representation, such that at any instant the central representation contains the properties of only a single location in the visual scene, the selected location. We suggest that this mapping is the principal expression of early selective visual attention. One function of selective attention is to fuse information from different maps into one coherent whole. (3) Certain selection rules determine which locations will be mapped into the central representation. The major rule, using the conspicuity of locations in the early representation, is implemented using a so-called Winner-Take-All network. Inhibiting the selected location in this network causes an automatic shift towards the next most conspicious location. Additional rules are proximity and similarity preferences. We discuss how these rules can be implemented in neuron-like networks and suggest a possible role for the extensive back-projection from the visual cortex to the LGN.

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