Abstract
Previous research indicates that anxiety disorders are characterized by an overgeneralization of conditioned fear as compared with healthy participants. Therefore, fear generalization is considered a key mechanism for the development of anxiety disorders. However, systematic investigations on the variance in fear generalization are lacking. Therefore, the current study aims at identifying distinctive phenotypes of fear generalization among healthy participants. To this end, 1175 participants completed a differential fear conditioning phase followed by a generalization test. To identify patterns of fear generalization, we used a k-means clustering algorithm based on individual arousal generalization gradients. Subsequently, we examined the reliability and validity of the clusters and phenotypical differences between subgroups on the basis of psychometric data and markers of fear expression. Cluster analysis reliably revealed five clusters that systematically differed in mean responses, differentiation between conditioned threat and safety, and linearity of the generalization gradients, though mean response levels accounted for most variance. Remarkably, the patterns of mean responses were already evident during fear acquisition and corresponded most closely to psychometric measures of anxiety traits. The identified clusters reliably described subgroups of healthy individuals with distinct response characteristics in a fear generalization test. Following a dimensional view of psychopathology, these clusters likely delineate risk factors for anxiety disorders. As crucial group characteristics were already evident during fear acquisition, our results emphasize the importance of average fear responses and differentiation between conditioned threat and safety as risk factors for anxiety disorders.
Dokumententyp: | Zeitschriftenartikel |
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Fakultät: | Medizin |
Themengebiete: | 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin und Gesundheit |
ISSN: | 2158-3188 |
Sprache: | Englisch |
Dokumenten ID: | 78633 |
Datum der Veröffentlichung auf Open Access LMU: | 15. Dez. 2021, 14:44 |
Letzte Änderungen: | 15. Dez. 2021, 14:44 |