Humans selectively attend to task-relevant information in order to make accurate decisions. However, selective attention incurs consequences if the learning environment changes unexpectedly. This trade-off has been underscored by studies that compare learning behaviors between adults and young children: broad sampling during learning comes with a breadth of information in memory, often allowing children to notice details of the environment that are missed by their more selective adult counterparts. The current work extends the exemplar-similarity account of object discrimination to consider both the intentional and consequential aspects of selective attention when predicting choice. In a novel direct input approach, we used trial-level eye-tracking data from training and test to replace the otherwise freely estimated attention dynamics of the model. We demonstrate that only a model imbued with gaze correlates of memory precision in addition to decision weights can accurately predict key behaviors associated with (a) selective attention to a relevant dimension, (b) distributed attention across dimensions, and (c) flexibly shifting strategies between tasks. Although humans engage in selective attention with the intention of being accurate in the moment, our findings suggest that its consequences on memory constrain the information that is available for making decisions in the future. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

中文翻译：

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“眼睛是表征的窗口”：将目光与物体辨别任务中的记忆精度和决策权重联系起来。


人类有选择地关注与任务相关的信息，以便做出准确的决策。然而，如果学习环境发生意外变化，选择性注意力就会产生后果。比较成人和幼儿学习行为的研究强调了这种权衡：学习过程中的广泛采样伴随着记忆中的广泛信息，通常使儿童能够注意到环境的细节，而那些更有选择性的成人同伴会错过这些细节。目前的工作扩展了对象歧视的样本相似性解释，以在预测选择时考虑选择性注意的意图和后果方面。在一种新颖的直接输入方法中，我们使用来自训练和测试的试验级眼动追踪数据来替换模型的其他自由估计的注意力动态。我们证明，除了决策权重之外，只有充满注视与记忆精度相关的模型才能准确预测与以下相关的关键行为：（a）对相关维度的选择性关注，（b）跨维度的分布式注意力，以及（c）灵活转变策略任务之间。尽管人类进行选择性注意力的目的是为了在当下保持准确，但我们的研究结果表明，它对记忆的影响限制了可用于未来决策的信息。 （PsycInfo 数据库记录 (c) 2024 APA，保留所有权利）。