Bogazici University, Istanbul, Turkey.
Bogazici Universitesi, Psikoloji Bolumu, Bebek-Istanbul, Turkey.
Atten Percept Psychophys. 2021 Apr;83(3):1141-1151. doi: 10.3758/s13414-021-02270-9. Epub 2021 Mar 16.
It is known that the visual system can efficiently extract mean and variance information, facilitating the detection of outliers. However, no research to date has directly investigated whether ensemble perception mechanisms contribute to outlier representation precision. We specifically were interested in how the distinctiveness of outliers impacts their precision. Across two experiments, we compared how accurately viewers represented the orientation of spatial outliers that varied in distinctiveness and found that increased outlier distinctiveness resulted in greater precision. Based on comparisons of our data to simulations reflecting particular selective strategies, we eliminated the possibility that participants were selectively processing the outlier, at the expense of the ensemble. Thus, we argued that participants separately represented distinct outliers along with ensemble summaries of the remaining items in a display. We also found that outlier distinctiveness moderated the precision of how the remaining items were summarized. We discuss these findings in relation to computational capacity and constraints of ensemble perception mechanisms.
已知视觉系统能够有效地提取均值和方差信息，有助于检测异常值。然而，迄今为止，没有研究直接探讨集合感知机制是否有助于异常值的表示精度。我们特别感兴趣的是异常值的独特性如何影响其精度。在两项实验中，我们比较了观察者如何准确地表示在独特性上变化的空间异常值的方向，并发现异常值的独特性增加会导致更高的精度。基于将我们的数据与反映特定选择性策略的模拟进行比较，我们排除了参与者有选择地处理异常值而忽略集合的可能性。因此，我们认为参与者分别沿着显示器中剩余项目的集合摘要来单独表示独特的异常值。我们还发现，异常值的独特性调节了如何汇总剩余项目的精度。我们将这些发现与集合感知机制的计算能力和约束联系起来进行讨论。
