ISSN 1671-3710
CN 11-4766/R
主办:中国科学院心理研究所
出版:科学出版社

心理科学进展 ›› 2019, Vol. 27 ›› Issue (3): 465-474.doi: 10.3724/SP.J.1042.2019.00465

• 研究方法 • 上一篇    下一篇

心理表征的可视化途径:基于噪音的反向相关图像分类技术

侯春娜1(), 刘志军2   

  1. 1 东北师范大学心理学院, 长春 130024
    2 长春理工大学社会学系, 长春 130022
  • 收稿日期:2018-07-17 出版日期:2019-03-15 发布日期:2019-01-22
  • 通讯作者: 侯春娜 E-mail:houcn359@nenu.edu.cn
  • 基金资助:
    教育部人文社会科学研究青年基金(16YJC190009);中央高校基本科研业务费专项资金资助资助(2412017QD030)

Visualization of mental representation: Noise-based reverse correlation image classification technology

HOU Chun-Na1(), LIU Zhi-Jun2   

  1. 1 School of psychology, Northeast Normal University, Changchun 130024, China
    2 Department of Sociology, Changchun University of Science and Technology, Changchun 130022, China
  • Received:2018-07-17 Online:2019-03-15 Published:2019-01-22
  • Contact: HOU Chun-Na E-mail:houcn359@nenu.edu.cn

摘要:

社会心理学对图像的心理表征研究一直难以将心理活动的内容准确刻画出来。近10年来出现了一种新心理物理学方法——“反向相关图像分类技术”, 该技术假定观察者的反应与视觉噪音存在相关关系, 且反应是依照观察者的社会判断标准进行而非随机做出; 通过对其做出反应的相应噪音模式的足够次数的权重计算与视觉代码显现, 从而将观察者内在的评估特点可视化。该技术已在特质研究、种族和群际偏见等领域取得了一些成果, 但是未来仍需解决实验次数过多, 分离混杂的噪音以及被试的表现等问题, 才能获得更为真实的心理表征。

关键词: 面孔, 心理表征, 反向相关图像分类技术

Abstract:

Studies of the mental representation of images in social psychology have encountered difficulty in accurately portraying psychological activity. Over the past decade, reverse correlation image classification has emerged as a new psychophysical method that assumes there is a relationship between an observer’s response and visual noise, and that the response is based on the observer’s social judgment criteria, and are not random. Performing a sufficient number of weight calculations on the corresponding noise patterns of the observer’s reaction allows us to visualize the intrinsic evaluation characteristics of the observer. The use of reverse correlation image classification technology has achieved some results in the areas of trait research, ethnicity, and intergroup bias. In the future, however, it is necessary to solve the problems of excessive experimental trials, separation of mixed noise, and subjects’ performance, in order to achieve more realistic mental representations.

Key words: face, mental representation, reverse correlation image classification technology

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