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视觉周边的赌博:对人类判断视觉不确定性能力的联合测量分析。

Gambling in the visual periphery: a conjoint-measurement analysis of human ability to judge visual uncertainty.

机构信息

Department of Psychology, New York University, New York, New York, United States of America.

出版信息

PLoS Comput Biol. 2010 Dec 2;6(12):e1001023. doi: 10.1371/journal.pcbi.1001023.

Abstract

Recent work in motor control demonstrates that humans take their own motor uncertainty into account, adjusting the timing and goals of movement so as to maximize expected gain. Visual sensitivity varies dramatically with retinal location and target, and models of optimal visual search typically assume that the visual system takes retinal inhomogeneity into account in planning eye movements. Such models can then use the entire retina rather than just the fovea to speed search. Using a simple decision task, we evaluated human ability to compensate for retinal inhomogeneity. We first measured observers' sensitivity for targets, varying contrast and eccentricity. Observers then repeatedly chose between targets differing in eccentricity and contrast, selecting the one they would prefer to attempt: e.g., a low contrast target at 2° versus a high contrast target at 10°. Observers knew they would later attempt some of their chosen targets and receive rewards for correct classifications. We evaluated performance in three ways. Equivalence: Do observers' judgments agree with their actual performance? Do they correctly trade off eccentricity and contrast and select the more discriminable target in each pair? Transitivity: Are observers' choices self-consistent? Dominance: Do observers understand that increased contrast improves performance? Decreased eccentricity? All observers exhibited patterned failures of equivalence, and seven out of eight observers failed transitivity. There were significant but small failures of dominance. All these failures together reduced their winnings by 10%-18%.

摘要

最近的运动控制研究表明,人类会考虑自身的运动不确定性,调整运动的时间和目标,以最大化预期收益。视觉灵敏度随视网膜位置和目标而显著变化,而最优视觉搜索模型通常假设视觉系统在规划眼球运动时会考虑视网膜的非均匀性。这些模型可以利用整个视网膜,而不仅仅是中央凹,来加速搜索。我们使用一个简单的决策任务来评估人类补偿视网膜非均匀性的能力。我们首先测量了观察者在对比度和离焦度变化时对目标的敏感度。然后,观察者在离焦度和对比度不同的目标之间反复进行选择,选择他们更愿意尝试的目标:例如,在 2°处选择低对比度目标,而在 10°处选择高对比度目标。观察者知道他们稍后会尝试一些选择的目标,并因正确分类而获得奖励。我们通过三种方式评估了表现。等价性:观察者的判断是否与他们的实际表现一致?他们是否正确权衡离焦度和对比度,并在每一对中选择更具可分辨性的目标?传递性:观察者的选择是否自洽?优势性:观察者是否理解对比度增加会提高性能?离焦度降低会提高性能?所有观察者都表现出等价性的模式性失败,8 个观察者中有 7 个失败了传递性。有显著但较小的优势性失败。所有这些失败一起使他们的奖金减少了 10%-18%。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0069/2996320/15580c701cfb/pcbi.1001023.g001.jpg

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