When there are many visual items, the visual system could represent their summary statistics (e.g., mean, variance) to process them efficiently. Although many previous studies have investigated the mean or variance representation itself, a relationship between these two ensemble representations has not been investigated much. In this study, we tested the potential interaction between mean and variance representations by using a visual adaptation method. We reasoned that if mean and variance representations interact with each other, an adaptation aftereffect to either mean or variance would influence the perception of the other. Participants watched a sequence of orientation arrays containing a specific statistical property during the adaptation period. To produce an adaptation aftereffect specific to variance or mean, one property of the adaptor arrays (variance or mean) had a fixed value while the other property was randomly varied. After the adaptation, participants were asked to discriminate the property of the test array that was randomly varied during the adaptation. We found that the adaptation aftereffect of orientation variance influenced the sensitivity of mean orientation discrimination (Experiment 1), and that the adaptation aftereffect of mean orientation influenced the bias of orientation variance discrimination (Experiment 2). These results suggest that mean and variance representations do closely interact with each other. Considering that mean and variance reflect the representative value and dispersion of multiple items respectively, the interactions between mean and variance representations may reflect their complementary roles to summarize complex visual information effectively.

中文翻译：

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适应均值和方差：取向感知中均值和方差表示之间的相互关系。

当存在许多视觉项目时，视觉系统可以表示其摘要统计信息（例如，均值，方差）以有效地对其进行处理。尽管许多先前的研究已经调查了均值或方差表示本身，但是对这两个整体表示之间的关系还没有进行太多研究。在这项研究中，我们通过使用视觉适应方法测试了均值和方差表示之间的潜在相互作用。我们认为，如果均值和方差表示彼此相互作用，则均值或方差的适应后效应将影响对方的感知。参与者观看了适应期间包含特定统计属性的一系列方向阵列。为了产生特定于方差或均值的适应后效应，适配器阵列的一个属性（方差或均值）具有固定值，而另一属性则是随机变化的。改编后，要求参与者区分改编过程中随机变化的测试阵列的属性。我们发现取向方差的适应后效应影响平均取向歧视的敏感性（实验1），平均取向的适应后效应影响取向变异歧视的偏差（实验2）。这些结果表明，均值和方差表示确实紧密地相互作用。考虑到均值和方差分别反映了多个项目的代表值和离散度，