Facial-Attractiveness Choices Are Predicted by Divisive Normalization
Facial-Attractiveness Choices Are Predicted by Divisive Normalization
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DOI：
10.1177/0956797616661523
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发表时间：
2016-10-01
影响因子：
8.2
通讯作者：
Furl, Nicholas
中科院分区：
文献类型：
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作者：
Furl, Nicholas
人们看起来是更有吸引力还是不那么有吸引力取决于他们结交的朋友？一种分裂归一化账户，其中刺激强度的表示被同时的刺激强度归一化(除)，预测选项之间的选择偏好随着选项值范围的增加而增加。在这里报道的第一个实验中，我操纵了每个试验中呈现的面孔的吸引力范围，方法是改变一张不受欢迎的分散注意力的面孔的吸引力，同时呈现给两个有吸引力的目标，让参与者选择最有吸引力的面孔。我使用归一化模型来预测面部吸引力偏好的背景依赖关系。分心者越不吸引人，其中一个目标就越比另一个目标更受欢迎，这表明分裂归一化(大脑中的一种潜在的规范计算)会影响社会评价。当我操纵面孔的平均值时，我得到了同样的结果，参与者选择了最平均的面孔。这一发现表明，分裂的正常化并不局限于基于价值的决定(例如，吸引力)。这种对正常化的社会评价的新应用，这是一个经典的理论，为在广告或约会等自然主义背景下预测社会决策打开了可能性。
Do people appear more attractive or less attractive depending on the company they keep? A divisive-normalization accountin which representation of stimulus intensity is normalized (divided) by concurrent stimulus intensitiespredicts that choice preferences among options increase with the range of option values. In the first experiment reported here, I manipulated the range of attractiveness of the faces presented on each trial by varying the attractiveness of an undesirable distractor face that was presented simultaneously with two attractive targets, and participants were asked to choose the most attractive face. I used normalization models to predict the context dependence of preferences regarding facial attractiveness. The more unattractive the distractor, the more one of the targets was preferred over the other target, which suggests that divisive normalization (a potential canonical computation in the brain) influences social evaluations. I obtained the same result when I manipulated faces' averageness and participants chose the most average face. This finding suggests that divisive normalization is not restricted to value-based decisions (e.g., attractiveness). This new application to social evaluation of normalization, a classic theory, opens possibilities for predicting social decisions in naturalistic contexts such as advertising or dating.