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Individual differences in human fear generalization-pattern identification and implications for anxiety disorders.
Translational Psychiatry ( IF 5.8 ) Pub Date : 2019-11-18 , DOI: 10.1038/s41398-019-0646-8 Y Stegmann 1, 2 , M A Schiele 3 , D Schümann 4 , T B Lonsdorf 4 , P Zwanzger 5, 6, 7 , M Romanos 8 , A Reif 2, 9 , K Domschke 2, 3, 10 , J Deckert 11 , M Gamer 1, 2 , P Pauli 1, 2
Translational Psychiatry ( IF 5.8 ) Pub Date : 2019-11-18 , DOI: 10.1038/s41398-019-0646-8 Y Stegmann 1, 2 , M A Schiele 3 , D Schümann 4 , T B Lonsdorf 4 , P Zwanzger 5, 6, 7 , M Romanos 8 , A Reif 2, 9 , K Domschke 2, 3, 10 , J Deckert 11 , M Gamer 1, 2 , P Pauli 1, 2
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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.
中文翻译：
人类恐惧泛化模式识别的个体差异及其对焦虑症的影响。
先前的研究表明，与健康参与者相比，焦虑症的特点是过度概括条件性恐惧。因此，恐惧泛化被认为是焦虑症发生的关键机制。然而，缺乏对恐惧泛化差异的系统研究。因此，当前的研究旨在确定健康参与者中恐惧泛化的独特表型。为此，1175 名参与者完成了差异性恐惧调节阶段，随后进行了泛化测试。为了识别恐惧泛化模式，我们使用了基于个体唤醒泛化梯度的 k 均值聚类算法。随后，我们根据心理测量数据和恐惧表达标记检查了聚类的可靠性和有效性以及亚组之间的表型差异。聚类分析可靠地揭示了五个聚类，它们在平均响应、条件威胁与安全之间的差异以及泛化梯度的线性度方面存在系统差异，尽管平均响应水平占了大部分方差。值得注意的是，平均反应模式在恐惧习得过程中已经很明显，并且与焦虑特征的心理测量最接近。所识别的聚类可靠地描述了在恐惧泛化测试中具有不同反应特征的健康个体的亚组。从精神病理学的维度来看，这些集群可能描绘了焦虑症的危险因素。由于在恐惧习得过程中关键的群体特征已经很明显，我们的结果强调了平均恐惧反应以及区分条件性威胁和安全作为焦虑症危险因素的重要性。
更新日期：2019-11-18
中文翻译：
人类恐惧泛化模式识别的个体差异及其对焦虑症的影响。
先前的研究表明，与健康参与者相比，焦虑症的特点是过度概括条件性恐惧。因此，恐惧泛化被认为是焦虑症发生的关键机制。然而，缺乏对恐惧泛化差异的系统研究。因此，当前的研究旨在确定健康参与者中恐惧泛化的独特表型。为此，1175 名参与者完成了差异性恐惧调节阶段，随后进行了泛化测试。为了识别恐惧泛化模式，我们使用了基于个体唤醒泛化梯度的 k 均值聚类算法。随后，我们根据心理测量数据和恐惧表达标记检查了聚类的可靠性和有效性以及亚组之间的表型差异。聚类分析可靠地揭示了五个聚类，它们在平均响应、条件威胁与安全之间的差异以及泛化梯度的线性度方面存在系统差异，尽管平均响应水平占了大部分方差。值得注意的是，平均反应模式在恐惧习得过程中已经很明显，并且与焦虑特征的心理测量最接近。所识别的聚类可靠地描述了在恐惧泛化测试中具有不同反应特征的健康个体的亚组。从精神病理学的维度来看，这些集群可能描绘了焦虑症的危险因素。由于在恐惧习得过程中关键的群体特征已经很明显，我们的结果强调了平均恐惧反应以及区分条件性威胁和安全作为焦虑症危险因素的重要性。
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