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在现实世界中,扫视之后还留存哪些信息?

What information survives saccades in the real world?

作者信息

Tatler Benjamin W

机构信息

Sussex Centre for Neuroscience, School of Biological Sciences, University of Sussex, Brighton BN1 9QG, UK.

出版信息

Prog Brain Res. 2002;140:149-63. doi: 10.1016/S0079-6123(02)40048-9.

Abstract

Recent change detection research demonstrates impressively that we do not retain and fuse the pictorial content of successive fixations. This raises two distinct issues: (1) when and how is point-by-point information lost or replaced? and (2) might more abstract information be extracted and retained from fixations? In this chapter I explore both of these issues. I consider the evidence for a very short-term richly detailed visual representation of the current target of fixation that survives the saccade but is overwritten by the content of each new fixation shortly after it begins. The possibility of abstract representations of the visual surroundings is then discussed. Under conditions of competitive, parallel processing, as are present in real life situations, multiple types of information are extracted and retained from complex natural scenes. Time courses for extraction vary between different types of information. The inclusion of eye movement data reveals a crucial role for fixations in information extraction. The data suggest that information assimilation into the representations tested here is dominated by the fovea and is integrated and accumulated from multiple foveations. From these studies we are able to construct a rudimentary framework, in which representational faithfulness and richness depend upon fixation history of that part of the visual scene, thus producing an efficient and potentially task-specific representation.

摘要

近期的变化检测研究令人印象深刻地表明,我们不会保留并融合连续注视的图像内容。这引发了两个不同的问题:(1)逐点信息何时以及如何丢失或被替换?(2)是否可以从注视中提取并保留更抽象的信息?在本章中,我将探讨这两个问题。我考虑了关于当前注视目标的非常短期的、细节丰富的视觉表征的证据,这种表征在扫视后仍然存在,但在每个新注视开始后不久就会被其内容覆盖。然后讨论了视觉环境抽象表征的可能性。在现实生活中存在的竞争性并行处理条件下,从复杂的自然场景中提取并保留了多种类型的信息。不同类型信息的提取时间进程各不相同。眼动数据的纳入揭示了注视在信息提取中的关键作用。数据表明,此处测试的表征中的信息同化主要由中央凹主导,并从多个中央凹注视中整合和积累。从这些研究中,我们能够构建一个基本框架,其中表征的忠实度和丰富度取决于视觉场景该部分的注视历史,从而产生一种高效且可能针对特定任务的表征。

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