Negative emotionality is a well-established and stable risk factor for affective disorders. Individual differences in negative emotionality have been linked to associative learning processes which can be captured experimentally by computing CS-discrimination values in fear conditioning paradigms. Literature suffers from underpowered samples, suboptimal methods, and an isolated focus on single questionnaires and single outcome measures. First, the specific and shared variance across three commonly employed questionnaires [STAI-T, NEO-FFI-Neuroticism, Intolerance of Uncertainty (IU) Scale] in relation to CS-discrimination during fear-acquisition in multiple analysis units (ratings, skin conductance, startle) is addressed (NStudy1 = 356). A specific significant negative association between STAI-T and CS-discrimination in SCRs and between IU and CS-discrimination in startle responding was identified in multimodal and dimensional analyses, but also between latent factors negative emotionality and fear learning, which capture shared variance across questionnaires/scales and across outcome measures. Second, STAI-T was positively associated with CS-discrimination in a number of brain areas linked to conditioned fear (amygdala, putamen, thalamus), but not to SCRs or ratings (NStudy2 = 113). Importantly, we replicate potential sampling biases between fMRI and behavioral studies regarding anxiety levels. Future studies are needed to target wide sampling distributions for STAI-T and verify whether current findings are generalizable to other samples.
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.
Intolerance of uncertainty (IU) is a transdiagnostic risk factor for internalizing disorders. Prior work has found that IU may be associated with either increased reactivity to threat or, alternatively, with decreased differential responding between threat and nonthreat/safety cues (i.e., threat generalization). For example, work by Morriss, Macdonald, & van Reekum (2016) found that higher IU was associated with increased threat generalization during acquisition (using skin conductance response (SCR)), as well as less differentiation between acquisition and extinction (using subjective uneasiness ratings). Here, three labs attempted direct and conceptual replications of Morriss, Macdonald, et al. (2016). Results showed that the direct replication failed, despite being conducted at the same lab site as the original study; moreover, in contrast to Morriss, Macdonald, et al. (2016), the direct replication found that higher IU was associated with greater SCR discrimination between threat and safety cues (across acquisition and extinction), as well as greater differences in uneasiness ratings between acquisition and extinction. Nonetheless, in the conceptual replications, higher IU was associated with greater threat generalization, as well as less discrimination between acquisition and extinction, as measured using SCR. Higher IU was also associated with larger late positive potentials to threat versus safety cues during extinction—results that mirror those observed by Morriss, Macdonald, et al. (2016) using SCR. Results are discussed with regards to the challenge involved in defining a successful replication attempt, the benefits of collaborative replication and the use and reliability of multiple measures.
Background The general understanding of the ‘vulnerability–stress model’ of mental disorders neglects the modifying impact of resilience-increasing factors such as coping ability. Aims Probing a conceptual framework integrating both adverse events and coping factors in an extended ‘vulnerability–stress–coping model’ of mental disorders, the effects of functional neuropeptide S receptor gene (NPSR1) variation (G), early adversity (E) and coping factors (C) on anxiety were addressed in a three-dimensional G × E × C model. Method In two independent samples of healthy probands (discovery: n = 1403; replication: n = 630), the interaction of NPSR1 rs324981, childhood trauma (Childhood Trauma Questionnaire, CTQ) and general self-efficacy as a measure of coping ability (General Self-Efficacy Scale, GSE) on trait anxiety (State-Trait Anxiety Inventory) was investigated via hierarchical multiple regression analyses. Results In both samples, trait anxiety differed as a function of NPSR1 genotype, CTQ and GSE score (discovery: β = 0.129, P = 3.938 × 10−8; replication: β = 0.102, P = 0.020). In A allele carriers, the relationship between childhood trauma and anxiety was moderated by general self-efficacy: higher self-efficacy and childhood trauma resulted in low anxiety scores, and lower self-efficacy and childhood trauma in higher anxiety levels. In turn, TT homozygotes displayed increased anxiety as a function of childhood adversity unaffected by general self-efficacy. Conclusions Functional NPSR1 variation and childhood trauma are suggested as prime moderators in the vulnerability–stress model of anxiety, further modified by the protective effect of self-efficacy. This G × E × C approach – introducing coping as an additional dimension further shaping a G × E risk constellation, thus suggesting a three-dimensional ‘vulnerability–stress–coping model’ of mental disorders – might inform targeted preventive or therapeutic interventions strengthening coping ability to promote resilient functioning.
Abstract. As the criticism of the definition of the phenotype (i.e., clinical diagnosis) represents the major focus of the Research Domain Criteria (RDoC) initiative, it is somewhat surprising that discussions have not yet focused more on specific conceptual and procedural considerations of the suggested RDoC constructs, sub-constructs, and associated paradigms. We argue that we need more precise thinking as well as a conceptual and methodological discussion of RDoC domains and constructs, their interrelationships as well as their experimental operationalization and nomenclature. The present work is intended to start such a debate using fear conditioning as an example. Thereby, we aim to provide thought-provoking impulses on the role of fear conditioning in the age of RDoC as well as conceptual and methodological considerations and suggestions to guide RDoC-based fear conditioning research in the future.
Background: Anxiety disorders are more prevalent in women than in men. Despite this sexual dimorphism, most experimental studies are conducted in male participants, and studies focusing on sex differences are sparse. In addition, the role of hormonal contraceptives and menstrual cycle phase in fear conditioning and extinction processes remain largely unknown. Methods: We investigated sex differences in context-dependent fear acquisition and extinction (day 1) and their retrieval/expression (day 2). Skin conductance responses (SCRs), fear and unconditioned stimulus expectancy ratings were obtained. Results: We included 377 individuals (261 women) in our study. Robust sex differences were observed in all dependent measures. Women generally displayed higher subjective ratings but smaller SCRs than men and showed reduced excitatory/inhibitory conditioned stimulus (CS+/CS-) discrimination in all dependent measures. Furthermore, women using hormonal contraceptives showed reduced SCR CS discrimination on day 2 than men and free-cycling women, while menstrual cycle phase had no effect. Limitations: Possible limitations include the simultaneous testing of up to 4 participants in cubicles, which might have introduced a social component, and not assessing postexperimental contingency awareness. Conclusion: The response pattern in women shows striking similarity to previously reported sex differences in patients with anxiety. Our results suggest that pronounced deficits in associative discrimination learning and subjective expression of safety information (CS-responses) might underlie higher prevalence and higher symptom rates seen in women with anxiety disorders. The data call for consideration of biological sex and hormonal contraceptive use in future studies and may suggest that targeting inhibitory learning during therapy might aid precision medicine.
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