Oriet Chris, Hozempa Kadie
J Vis. 2016;16(3):3. doi: 10.1167/16.3.3.
Information taken in by the human visual system allows individuals to form statistical representations of sets of items. One's knowledge of natural categories includes statistical information, such as average size of category members and the upper and lower boundaries of the set. Previous research suggests that when subjects attend to a particular dimension of a set of items presented over an extended duration, they quickly learn about the central tendency of the set. However, it is unclear whether such learning can occur incidentally, when subjects are not attending to the relevant dimension of the set. The present study explored whether subjects could reproduce global statistical properties of a set presented over an extended duration when oriented to task-irrelevant properties of the set. Subjects were tested for their memory of its mean, its smallest and largest exemplars, the direction of its skew, and the relative distribution of the items. Subjects were able to accurately recall the average size circle, as well as the upper and lower boundaries of a set of 4,200 circles displayed over an extended period. This suggests that even without intending to do so, they were encoding and updating a statistical summary representation of a task-irrelevant attribute of the circles over time. Such incidental encoding of statistical properties of sets is thus a plausible mechanism for establishing a representation of typicality in category membership.
人类视觉系统接收的信息使个体能够形成物品集合的统计表征。一个人对自然类别的认识包括统计信息，例如类别成员的平均大小以及该集合的上下边界。先前的研究表明，当受试者长时间关注一组呈现的物品的特定维度时，他们会迅速了解该集合的集中趋势。然而，尚不清楚当受试者没有关注集合的相关维度时，这种学习是否会偶然发生。本研究探讨了受试者在关注集合的任务无关属性时，是否能够再现长时间呈现的集合的全局统计属性。测试了受试者对集合均值、最小和最大样本、偏斜方向以及物品相对分布的记忆。受试者能够准确回忆平均大小的圆圈，以及长时间展示的一组4200个圆圈的上下边界。这表明，即使没有刻意去做，随着时间的推移，他们也在对圆圈的任务无关属性的统计摘要表征进行编码和更新。因此，这种对集合统计属性的偶然编码是在类别成员中建立典型性表征的一种合理机制。
