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The goal of this study was to test in a clinical sample the interrater reliability and convergent validity of the Differentiation-Relatedness Scale (D-RS), a measure that evaluates mental representations based on open-ended descriptions of self and significant others. The study also investigated the ability of the D-RS to predict personality disorders (PDs) from Section II of the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), and the dysfunctional trait domains presented in the Alternative DSM-5 Model for Personality Disorders Criterion B in Section III of the DSM-5. We also evaluated if the D-RS predicts observed Section II PDs over and above Criterion B of the Alternative DSM-5 Model for Personality Disorders. We found that the interrater reliability of the D-RS was good on the basis of the mean scores of 6 independent raters and that it showed moderate convergent validity. Results of dominance analyses indicated that the D-RS is a significant predictor of Section II borderline PD and of the overall number of DSM-5 PDs. When we considered the Section III Criterion B for PDs, the D-RS was not able to predict any of the Personality Inventory for DSM-5 domains, suggesting that the D-RS may be more related to personality functioning behind mental representations than to maladaptive personality traits. Finally, results of hierarchical regression analyses suggested that the D-RS produced a significant but modest increase in the prediction of borderline PD traits and the overall number of PDs traits even when the effect of the Personality Inventory for DSM-5 domains were controlled for.

Major depressive disorder (MDD) is a psychiatric disorder characterized by abnormal resting state functional connectivity (rsFC) in various neural networks and especially in default-mode network (DMN). However, inconsistent findings, i.e., increased and decreased DMN rsFC, have been reported, which raise the question for the source of DMN changes in MDD. Testing whether the DMN abnormalities in MDD can be traced to either a local, i.e., intra-network, or a global, i.e., inter-network, source, we conducted a novel sequence of rsFC analyses, i.e., global FC, intra-network FC, and inter-network FC. Moreover, all analyses were conducted without global signal regression (non-GSR) and with GSR in order to identify the impact of specifically the global component of functional connectivity on within-network functional connectivity within specifically the DMN. In MDD our findings demonstrate (i) increased representation of global signal correlation (GSCORR) in DMN regions, as confirmed independently by degree of centrality (DC) and by an independent DMN template, (ii) increased within-network DMN rsFC, (iii) highly increased inter-network rsFC of both lower- and higher order non-DMN networks with DMN, (iv) high accuracy in classifying MDD vs. healthy subjects by using GSCORR as predictor. Further supporting the global, i.e., non-DMN source of within-network rsFC of the DMN, all results were obtained only when including the global signal, i.e., non-GSR, but not when conducting GSR. Together, we show for the first time increased global signal representation within rsFC of DMN as stemming from inter-network sources as distinguished from local sources, i.e., within- or intra-DMN.

Objective: Clinical and neurobiological models posited that dissociative mechanisms might affect processes involved in emotional generation and regulation. However, there is a lack of a comprehensive theoretical framework that systematically includes dissociation within emotional functioning. Methods: The current study aims at conducting a meta-analytic review on the relationship between dissociation and emotion regulation in order to empirically estimate to what extent dissociation is related to emotion regulation processes. The meta-analysis was based on r coefficient as effect size measure, using a random-effect approach. Results: The meta-analysis included 57 independent studies for a total of 11596 individuals. Findings showed an overall moderate relationship between dissociation and emotion regulation (rw = .32; p < .05). The association between dissociation and emotion regulation was the same among clinical samples than non-clinical ones. Furthermore, dissociation showed moderate to large relationships with maladaptive domains of emotion regulation, namely disengagement (rw = 0.34; p < .01) (i.e., behavioral avoidance, experiential avoidance, thought and emotional suppression) and aversive cognitive perseveration (rw = 0.38; p < .001) (i.e., rumination, worry and nonacceptance). The analysis did not find significant relationship between dissociation and adaptive domain of emotional regulation (i.e., problem solving, mindfulness). Conclusion: Dissociation in the context of emotion regulation might be viewed as a basic neuro-mental mechanism that automatically contribute to the over-modulation of emotional states through avoidance reactions from internal and external reality. Future longitudinal studies are needed to clarify the causal relationships between dissociation and emotion regulation.