Haberman Jason, Whitney David
Center for Mind and Brain and Department of Psychology, University of California, Davis, CA 95616, USA.
J Exp Psychol Hum Percept Perform. 2009 Jun;35(3):718-34. doi: 10.1037/a0013899.
We frequently encounter groups of similar objects in our visual environment: a bed of flowers, a basket of oranges, a crowd of people. How does the visual system process such redundancy? Research shows that rather than code every element in a texture, the visual system favors a summary statistical representation of all the elements. The authors demonstrate that although it may facilitate texture perception, ensemble coding also occurs for faces-a level of processing well beyond that of textures. Observers viewed sets of faces varying in emotionality (e.g., happy to sad) and assessed the mean emotion of each set. Although observers retained little information about the individual set members, they had a remarkably precise representation of the mean emotion. Observers continued to discriminate the mean emotion accurately even when they viewed sets of 16 faces for 500 ms or less. Modeling revealed that perceiving the average facial expression in groups of faces was not due to noisy representation or noisy discrimination. These findings support the hypothesis that ensemble coding occurs extremely fast at multiple levels of visual analysis.
在我们的视觉环境中,我们经常会遇到成组的相似物体:一床鲜花、一篮橙子、一群人。视觉系统是如何处理这种冗余信息的呢?研究表明,视觉系统并非对纹理中的每个元素进行编码,而是倾向于对所有元素进行概括性的统计表示。作者证明,虽然整体编码可能有助于纹理感知,但它也会出现在面部处理中——这一处理水平远远超出了纹理的范畴。观察者观看了一系列情绪不同(如从开心到悲伤)的面孔,并评估每组面孔的平均情绪。尽管观察者对单个面孔的信息保留甚少,但他们对平均情绪却有非常精确的表征。即使观察者观看16张面孔的组图时间为500毫秒或更短,他们仍能继续准确地区分平均情绪。模型显示,感知面孔组中的平均面部表情并非由于噪声表征或噪声辨别。这些发现支持了这样一种假设,即整体编码在视觉分析的多个层面上极其快速地发生。