Optimal reward harvesting in complex perceptual environments
Optimal reward harvesting in complex perceptual environments
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DOI：
10.1073/pnas.0911972107
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发表时间：
2010-03-16
影响因子：
11.1
通讯作者：
Perona, Pietro
中科院分区：
文献类型：
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作者：
Navalpakkam, Vidhya;Koch, Christof;Perona, Pietro
在复杂感知环境中的多个目标中快速选择的能力是生存的关键。目标的奖励值以及低级感知属性（例如视觉显着性）可能有所不同。之前的研究分别调查了价值或显着性对选择的影响；因此，尚不清楚大脑在决策过程中如何结合这两个变量。我们通过三个实验解决了这个问题，在这些实验中，人类受试者试图通过从简短的展示中快速选择物品来最大化他们的金钱收入。每个展示都包含几个毫无价值的物品（干扰物）以及两个目标，其价值和显着性有系统地变化。我们将行为数据与三个计算模型的预测进行了比较，假设（i）受试者寻找显示中最有价值的项目，（ii）受试者寻找最容易检测到的项目，以及（iii）受试者表现得像一个理想的贝叶斯观察者，结合这两个因素以最大化每次试验中的预期奖励。无论用于表达选择的运动反应类型如何，我们发现决策都会受到价值和特征对比度的影响，其方式与理想的贝叶斯观察者一致，即使目标的特征对比度在试验之间发生不可预测的变化。这表明，个人能够在时间压力下以最佳和动态的方式获得奖励，同时寻求嵌入感知混乱中的多个目标。
The ability to choose rapidly among multiple targets embedded in a complex perceptual environment is key to survival. Targets may differ in their reward value as well as in their low-level perceptual properties (e.g., visual saliency). Previous studies investigated separately the impact of either value or saliency on choice; thus, it is not known how the brain combines these two variables during decision making. We addressed this question with three experiments in which human subjects attempted to maximize their monetary earnings by rapidly choosing items from a brief display. Each display contained several worthless items (distractors) as well as two targets, whose value and saliency were varied systematically. We compared the behavioral data with the predictions of three computational models assuming that (i) subjects seek the most valuable item in the display, (ii) subjects seek the most easily detectable item, and (iii) subjects behave as an ideal Bayesian observer who combines both factors to maximize the expected reward within each trial. Regardless of the type of motor response used to express the choices, we find that decisions are influenced by both value and feature-contrast in a way that is consistent with the ideal Bayesian observer, even when the targets' feature-contrast is varied unpredictably between trials. This suggests that individuals are able to harvest rewards optimally and dynamically under time pressure while seeking multiple targets embedded in perceptual clutter.