Generalization gradients for fear and disgust in human associative learning
Wang, J., Sun, X., Lu, J., Dou, H., & Lei, Y. (2021). Generalization gradients for fear and disgust in human associative learning. Scientific Reports, 11, Article 14210. https://doi.org/10.1038/s41598-021-93544-7
Published inScientific Reports
© The Author(s) 2021
Previous research indicates that excessive fear is a critical feature in anxiety disorders; however, recent studies suggest that disgust may also contribute to the etiology and maintenance of some anxiety disorders. It remains unclear if differences exist between these two threat-related emotions in conditioning and generalization. Evaluating different patterns of fear and disgust learning would facilitate a deeper understanding of how anxiety disorders develop. In this study, 32 college students completed threat conditioning tasks, including conditioned stimuli paired with frightening or disgusting images. Fear and disgust were divided into two randomly ordered blocks to examine differences by recording subjective US expectancy ratings and eye movements in the conditioning and generalization process. During conditioning, differing US expectancy ratings (fear vs. disgust) were found only on CS-, which may demonstrated that fear is associated with inferior discrimination learning. During the generalization test, participants exhibited greater US expectancy ratings to fear-related GS1 (generalized stimulus) and GS2 relative to disgust GS1 and GS2. Fear led to longer reaction times than disgust in both phases, and the pupil size and fixation duration for fear stimuli were larger than for disgust stimuli, suggesting that disgust generalization has a steeper gradient than fear generalization. These findings provide preliminary evidence for differences between fear- and disgust-related stimuli in conditioning and generalization, and suggest insights into treatment for anxiety and other fear- or disgust-related disorders. ...
PublisherSpringer Science and Business Media LLC
Publication in research information system
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Additional information about fundingThis work was supported by the National Natural Science Foundation of China [Grant NO. 31871130]; Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions (2019SHIBS0003; 2021SHIBS0003); Guangdong Key Project in “Development of new tools for diagnosis and treatment of Autism” (2018B030335001).
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