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Advances in Psychological Science    2019, Vol. 27 Issue (3) : 465-474     DOI: 10.3724/SP.J.1042.2019.00465
Research Method |
Visualization of mental representation: Noise-based reverse correlation image classification technology
HOU Chun-Na1(),LIU Zhi-Jun2
1 School of psychology, Northeast Normal University, Changchun 130024, China
2 Department of Sociology, Changchun University of Science and Technology, Changchun 130022, China
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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.

Keywords face      mental representation      reverse correlation image classification technology     
ZTFLH:  B841  
Corresponding Authors: Chun-Na HOU     E-mail: houcn359@nenu.edu.cn
Issue Date: 22 January 2019
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Chun-Na HOU
Zhi-Jun LIU
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Chun-Na HOU,Zhi-Jun LIU. Visualization of mental representation: Noise-based reverse correlation image classification technology[J]. Advances in Psychological Science, 2019, 27(3): 465-474.
URL:  
http://journal.psych.ac.cn/xlkxjz/EN/10.3724/SP.J.1042.2019.00465     OR     http://journal.psych.ac.cn/xlkxjz/EN/Y2019/V27/I3/465
  
  
  
  
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