Ensemble perception is efficient because it summarizes redundant and complex information. However, it loses the fine details of individual items during the averaging process. Such characteristics of ensemble perception are similar to those of coarse processing. Here, we tested whether extracting an average of a set was similar to coarse processing. To manipulate coarse processing, we used the fast flicker adaptation known as suppressing coarse information processed by the magnocellular pathway. We hypothesized that if computing the average of a set relied on coarse processing, the precision of an averaging task should decrease after adaptation compared to baseline (no-adaptation). Across experiments with various features (orientation in Experiment 1, size in Experiment 2, and facial expression in Experiment 3), we found that suppressing coarse information did not disrupt the performance of the averaging tasks. Rather, adaptation increased the precision of mean representation. The precision of mean representation might have increased because fine information was relatively enhanced after adaptation. Our results suggest that the quality of ensemble representation relies on that of individual items.

集合感知是有效的，因为它总结了冗余和复杂的信息。但是，它会在平均过程中丢失单个项目的详细信息。合奏感知的这种特征类似于粗加工的特征。在这里，我们测试了提取集合的平均值是否类似于粗加工。为了处理粗加工，我们使用了快速闪烁适应功能，即抑制由巨细胞途径处理的粗信息。我们假设，如果计算集的平均值依赖于粗加工，则与基线（无适应）相比，适应后平均任务的精度应降低。跨各种功能的实验（实验1的方向，实验2的大小，实验3的面部表情），我们发现抑制粗略信息不会破坏平均任务的性能。相反，适应提高了均值表示的精度。均值表示的精度可能已提高，因为自适应后相对较精细的信息有所增强。我们的结果表明，合奏表示的质量取决于单个项目的质量。