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多面孔表情的平均表征
其他题名Mean Representation of Multiple Facial Expressions
季琭妍
学位类型硕士
导师陈文锋
2014-05
学位授予单位中国科学院研究生院
学位授予地点北京
学位专业心理学
关键词表情面孔 情绪 个体表征 平均表征 精确性
摘要人们可以相当精确地提取多张表情面孔的平均情绪, 然而对于这种平均表征的机制仍然存在很多的问题和争议。本研究从个体表征与平均表征之间的关系为切入点,探讨了个体表征精确性如何影响平均表征这一问题。
实验 1通过操纵多面孔呈现时间改变面孔个体表征精确程度,考察了个体面孔表征精确性如何影响人们对多面孔集合中面孔成员的认知以及内隐的平均表征,结果发现人们倾向于判断“平均情绪”面孔为集合成员。随着面孔集合呈现时间增加,将“实际面孔成员”判断为“是成员”的比例增加后趋于稳定,将“平均情绪”面孔判断为集合成员的比例也增加后趋于稳定,但之后有所下降,不过依然与相应条件下对“实际面孔成员”的判断相当。
实验 2通过操纵多面孔呈现时间,考察了个体面孔表征精确性对外显的平均情绪辨别的影响,发现人们可以相当精确地提取多表情面孔的情绪信息,平均情绪辨别能力与一般情绪辨别能力非常相似,随面孔呈现时间变化为变化的趋势也基本一致。不过,在快速呈现(50ms)条件下,人们获取多个不同面孔平均情绪信息的速度快于多个相同面孔情绪信息的速度。
实验 3通过操纵面孔在视野中的位置改变个体面孔表征精确性,发现相比于中央窝外的面孔,位于中央窝的面孔在情绪平均表征中起到更大的作用,拥有更高的权重。
实验 4在控制面孔物理显著性和情绪强度的基础上,探究了中央窝外面孔的情绪显著性如何调节其在平均情绪表征中的作用,结果表明多面孔平均情绪加工中存在中央窝外的正性优势。
本研究说明了平均表征在一定程度上依赖个体表征的精确性,人们会基于个体表征精确性进行加权平均;不过当个体表征精确性非常差时,平均表征可以做出弥补因此依然保持相对较高的精确性;视野和情绪属性也会共同影响平均表征。
本研究增进了我们对多面孔平均表征的机制的理解, 为多面孔与单面孔加工理论的发展以及情绪加工研究提供了新的启示。
其他摘要People could extract mean expression of multiple faces pretty precisely. However, the mechanism of how we make such ensemble representation was far from clear. This study aimed to explore  the relationship between individual representation and mean representation, to be specific, how the  precision  of individual representation influences mean representation.
Experiment  1  examined how durations of multiple faces  impact individual representation and the implicit mean representation. It was found that there was a bias to indicate the face with mean emotion as the member of the  set. As the duration increased, the probability of judging  “actual set member”  as  the member of the set increased and then kept constant; the probability of judging the “mean emotion face” as the member of the set increased, kept constant and then dropped, but  was  still comparable to that of “actual set member”.
Experiment 2 explored how durations of multiple faces influence explicit discrimination of mean emotion. The results showed that the ability to discriminate mean emotion was very similar to regular emotion discrimination. However, when the duration of face set was 50ms, people could uptake information of mean emotion from  heterogeneous  faces  much quickly than that of emotion  from  homogeneous faces.  
Experiment 3 manipulated the accuracy of individual representation by changing positions of the faces in the field of vision and found  that  faces in the foveal vision were given more weight than those in the extrafoveal vision in  mean emotion representation.
Experiment 4 controlled the physical saliency and emotional intensity of face stimuli  and investigated how emotion saliency of faces in the extrafoveal vision modulated the mean emotion representation. It was found that there was an advantage for happy faces in the extrafoveal vision.
The present study  suggests  that  the mean representation  is  dependent on the precision  of individual representation to some extent and people  may  conduct a precision-weighted averaging. On the other hand, when the quality of individual representation  is  rather low, the mean  representation  can serve as a compensatory mechanism and still kept pretty high precision. The study also demonstrates  that  the visual field influences the mean representation along with the emotional saliency. The present study improves our understanding  of mean representation of multiple facial expressions, contributes to  the development of theories of multiple-  and single-face processing and sheds new light on emotional processing study.
学科领域基础心理学
语种中文
文献类型学位论文
条目标识符http://ir.psych.ac.cn/handle/311026/19597
专题认知与发展心理学研究室
作者单位中国科学院心理研究所
推荐引用方式
GB/T 7714
季琭妍. 多面孔表情的平均表征[D]. 北京. 中国科学院研究生院,2014.
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