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Title: | The assessment of gender differences in perceptual fear generalization and related processes | Authors: | Yu, Kenny Beckers, Tom Tuerlinckx, Francis Vanpaemel, Wolf ZAMAN, Jonas |
Issue Date: | 2024 | Publisher: | PERGAMON-ELSEVIER SCIENCE LTD | Source: | Behaviour research and therapy, 183 (Art N° 104640) | Abstract: | In this study we aimed to investigate gender differences in fear generalization tendencies in humans and, inspired by recent findings in animal research, examine whether any such differences could stem from differences in memory precision. Forty men and forty women underwent a differential fear conditioning procedure using geometric shapes as cues. Subsequently, generalized fear responses were assessed across a spectrum of perceptually similar shapes. Throughout generalization testing, perceptual memory accuracy was repeatedly probed using a stimulus recreation task. Using statistical and computational modeling, we found strong evidence for the absence of gender differences in fear learning and generalization behavior. The evidence for gender differences in related processes such as perception and memory was inconclusive. Although some of our findings hinted at the possibility that women may be more perceptive of physical differences between stimuli and have more accurate memory than men, those observations were not consistently replicated across experimental conditions and analytical approaches. Our results contribute to the emerging literature on gender differences in perceptual fear generalization in humans and underscore the need for further systematic research to explore the interplay between gender and mechanisms associated with fear generalization across different experimental contexts. | Notes: | Yu, KY (corresponding author), Tiensestr 102, B-3000 Leuven, Belgium. kenny.yu@kuleuven.be |
Keywords: | Fear learning;Fear generalization;Cognitive mechanisms;Visual perception;Visual memory | Document URI: | http://hdl.handle.net/1942/44533 | ISSN: | 0005-7967 | e-ISSN: | 1873-622X | DOI: | 10.1016/j.brat.2024.104640 | ISI #: | 001333041300001 | Rights: | 2024 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies. | Category: | A1 | Type: | Journal Contribution |
Appears in Collections: | Research publications |
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