The Graduate Program in Cognitive Science, Yonsei University, Seoul, South Korea.
The Graduate Program in Cognitive Science, Yonsei University, Seoul, South Korea; Department of Psychology, Yonsei University, Seoul, South Korea.
Vision Res. 2021 Jun;183:91-105. doi: 10.1016/j.visres.2021.02.008. Epub 2021 Mar 18.
When confronted with many visual items, people can compute their variability accurately and rapidly, which facilitates efficient information processing and optimal decision making. However, how the visual system computes variability is still unclear. To investigate this, we implemented situations whereby estimates of variability based on several possible variability measures (e.g., range, standard deviation, and weighted standard deviation) could be differentiated, and then examined which best accounted for human variability perception. In three psychophysical experiments, participants watched two arrays of items with various orientations and judged which had more variable orientations. Results showed that perceived variability was most consistent with the weighted standard deviation based on the reliability of individual items. Specifically, participants gave less consideration to deviant orientations that were likely to be outliers, and greater consideration to salient orientations that were likely to be encoded precisely. This reliability-based weighted standard deviation suggests an efficient and flexible way of representing visual variability.
当面对许多视觉项目时，人们可以准确而快速地计算它们的可变性，这有利于高效的信息处理和最佳的决策制定。然而，视觉系统如何计算可变性尚不清楚。为了研究这一点，我们实施了几种可能的可变性度量（例如范围、标准差和加权标准差）的可变性估计可以区分的情况，然后检查哪种情况最能说明人类的可变性感知。在三项心理物理学实验中，参与者观看了具有不同方向的两个项目阵列，并判断哪个具有更多变化的方向。结果表明，感知到的可变性与基于个体项目可靠性的加权标准差最一致。具体来说，参与者较少考虑可能是异常值的偏差方向，而更多地考虑可能被精确编码的突出方向。这种基于可靠性的加权标准差为表示视觉可变性提供了一种高效灵活的方法。
