视觉搜索
选择(遗传算法)
任务(项目管理)
统计学习
感知
人工智能
心理学
概率逻辑
视觉感受
实验心理学
统计模型
机器学习
计算机科学
认知
神经科学
管理
经济
作者
Sisi Wang,Stanislas Huynh Cong,Geoffrey F. Woodman
摘要
Learning statistical regularities of target objects speeds visual search performance. However, we do not yet know whether this statistical learning effect is driven by biasing attentional selection at the early perceptual stage of processing, as theories of attention propose, or by improving the decision-making efficiency at a late response-related stage. Leveraging the high-temporal resolution of the event-related potential (ERP) technique, we had 16 human observers perform a visual search task where we inserted a fine-grained statistical regularity that the target shapes appeared in different colors with six unique probabilities. Observers unintentionally learned these regularities such that they were faster to report targets that appeared in more likely target colors. The observers' ERPs showed that this learning effect resulted in subjects making faster decisions about the target presence, and not by preferentially shifting attention to more rapidly select likely target colors, as is often assumed by the attentional selection account, supporting a post-selection account for statistical learning of the probabilistic regularities of target features. These results provide fundamental insights into the attentional control mechanisms of statistical learning. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
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