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外周视觉中的汇总统计表示解释了视觉拥挤现象。

A summary-statistic representation in peripheral vision explains visual crowding.

作者信息

Balas Benjamin, Nakano Lisa, Rosenholtz Ruth

机构信息

Laboratories of Cognitive Neuroscience, Children's Hospital Boston, Boston, MA, USA.

出版信息

J Vis. 2009 Nov 19;9(12):13.1-18. doi: 10.1167/9.12.13.

Abstract

Peripheral vision provides a less faithful representation of the visual input than foveal vision. Nonetheless, we can gain a lot of information about the world from our peripheral vision, for example in order to plan eye movements. The phenomenon of crowding shows that the reduction of information available in the periphery is not merely the result of reduced resolution. Crowding refers to visual phenomena in which identification of a target stimulus is significantly impaired by the presence of nearby stimuli, or flankers. What information is available in the periphery? We propose that the visual system locally represents peripheral stimuli by the joint statistics of responses of cells sensitive to different position, phase, orientation, and scale. This "textural" representation by summary statistics predicts the subjective "jumble" of features often associated with crowding. We show that the difficulty of performing an identification task within a single pooling region using this representation of the stimuli is correlated with peripheral identification performance under conditions of crowding. Furthermore, for a simple stimulus with no flankers, this representation can be adequate to specify the stimulus with some position invariance. This provides evidence that a unified neuronal mechanism may underlie peripheral vision, ordinary pattern recognition in central vision, and texture perception. A key component of our methodology involves creating visualizations of the information available in the summary statistics of a stimulus. We call these visualizations "mongrels" and show that they are highly useful in examining how the early visual system represents the visual input. Mongrels enable one to study the "equivalence classes" of our model, i.e., the sets of stimuli that map to the same representation according to the model.

摘要

与中央凹视觉相比,周边视觉对视觉输入的呈现不够准确。尽管如此,我们仍能从周边视觉中获取大量有关世界的信息,例如用于规划眼球运动。拥挤现象表明,周边可用信息的减少不仅仅是分辨率降低的结果。拥挤是指这样一种视觉现象:附近刺激物(即侧翼刺激)的存在会显著损害对目标刺激的识别。周边有哪些可用信息呢?我们提出,视觉系统通过对不同位置、相位、方向和尺度敏感的细胞反应的联合统计,在局部表征周边刺激。这种通过汇总统计进行的“纹理”表征预测了通常与拥挤相关的特征的主观“混乱”。我们表明,使用这种刺激表征在单个汇聚区域内执行识别任务的难度与拥挤条件下的周边识别性能相关。此外,对于没有侧翼刺激的简单刺激,这种表征足以在一定程度上指定具有位置不变性的刺激。这提供了证据,表明一种统一的神经元机制可能是周边视觉、中央视觉中的普通模式识别以及纹理感知的基础。我们方法的一个关键组成部分涉及创建刺激汇总统计中可用信息的可视化。我们将这些可视化称为“杂种图”,并表明它们在研究早期视觉系统如何表征视觉输入方面非常有用。杂种图使人们能够研究我们模型的“等价类”,即根据模型映射到相同表征的刺激集。

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