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The reduction of aversive emotions by a conspecific’s presence—called social buffering—is a universal phenomenon in the mammalian world and a powerful form of human social emotion regulation. Animal and human studies on neural pathways underlying social buffering typically examined physiological reactions or regional brain activations. However, direct links between emotional and social stimuli, distinct neural processes and behavioural outcomes are still missing. Using data of 27 female participants, the current study delineated a large-scale process model of social buffering’s neural underpinnings, connecting changes in neural activity to emotional behaviour by means of voxel-wise multilevel mediation analysis. Our results confirmed that three processes underlie human social buffering: (i) social support-related reduction of activity in the orbitofrontal cortex, ventromedial and dorsolateral prefrontal cortices, anterior and mid-cingulate; (ii) downregulation of aversive emotion-induced brain activity in the superficial cortex-like amygdala and mediodorsal thalamus; and (iii) downregulation of reported aversive feelings. Results of the current study provide evidence for a distinct neural process model of aversive emotion regulation in humans by social buffering.

Verifying that conceptualisations of emotions are consistent across languages and cultures is a critical precondition for meaningful cross-cultural research on emotional experience. For achievement-related emotions tied to successes or failures, such evidence is virtually non-existent. To address this gap, we compared Canadian, German, Colombian, and Chinese university students’ (NTotal = 126) perceptions of affective, cognitive, motivational, physiological, and expressive characteristics of 16 achievement-related emotions using a psycholinguistic tool for profiling emotion concepts (Achievement Emotions CoreGRID). Cross-cultural similarity of emotion concepts quantified through double-entry intraclass correlations was generally high, and highest for their affective, cognitive, and motivational components. However, results also point to cultural variation, particularly for physiological and expressive components. Variation in perceived physiological characteristics was most pronounced for boredom, and for comparisons of Canada, Germany, and Colombia with China. Implications for theoretical propositions of universality of emotion concepts and future research on achievement-related emotions are discussed.

Cognitive emotion regulation (CER) enables humans to flexibly modulate their emotions. While local theories of CER neurobiology suggest interactions between specialized local brain circuits underlying CER, e.g., in subparts of amygdala and medial prefrontal cortices (mPFC), global theories hypothesize global interaction increases among larger functional brain modules comprising local circuits. We tested the global CER hypothesis using graph-based whole-brain network analysis of functional MRI data during aversive emotional processing with and without CER. During CER, global between-module interaction across stable functional network modules increased. Global interaction increase was particularly driven by subregions of amygdala and cuneus-nodes of highest nodal participation-that overlapped with CER-specific local activations, and by mPFC and posterior cingulate as relevant connector hubs. Results provide evidence for the global nature of human CER, complementing functional specialization of embedded local brain circuits during successful CER.

While the similarities between emotion regulation (Gross in J Personal Soc Psychol 74:224–237, 1998a) and emotional labor (Hochschild in The managed heart: commercialization of human feeling. University of California Press, Berkeley, 1983) have been theoretically discussed, empirical research on their relation is lacking. We examined the relations between the two constructs as well as their relations with teachers’ discrete emotions in a sample of 189 secondary school teachers. The results showed that reappraisal correlated positively with deep acting, whereas suppression correlated positively with surface acting. The findings further suggest that reappraisal and deep acting are linked to experiencing positive emotions, whereas suppression and surface acting are linked to experiencing negative emotions. However, there also were some differences in how emotion regulation and emotional labor were related to teachers’ discrete emotional experiences. Specifically, reappraisal and deep acting strategies were positively related to enjoyment; in addition, deep acting was negatively related to negative emotions such as anxiety, anger, and frustration. By contrast, suppression and surface acting strategies were positively associated with negative emotions (i.e., suppression with anxiety; surface acting with anxiety, anger, and frustration), and surface acting was negatively associated with the positive emotion enjoyment. Implications for integrating research on teachers’ emotion regulation and emotional labor are discussed.

Objectives: The aim of this study was to identify the determinants of presenteeism, taking health and individual factors into account. Methods: A quantitative analysis applying structural equation modelling analysis was conducted on the basis of secondary data from the Health and Retirement Survey (2008 wave), which measured presenteeism and its determinants. Results: Stress related factors at work (beta=-0.35, p

Cognitive emotion regulation is a powerful way of modulating emotional responses. However, despite the vital role of emotions in learning, it is unknown whether the effect of cognitive emotion regulation also extends to the modulation of learning. Computational models indicate prediction error activity, typically observed in the striatum and ventral tegmental area, as a critical neural mechanism involved in associative learning. We used model-based fMRI during aversive conditioning with and without cognitive emotion regulation to test the hypothesis that emotion regulation would affect prediction error-related neural activity in the striatum and ventral tegmental area, reflecting an emotion regulation-related modulation of learning. Our results show that cognitive emotion regulation reduced emotion-related brain activity, but increased prediction error-related activity in a network involving ventral tegmental area, hippocampus, insula and ventral striatum. While the reduction of response activity was related to behavioral measures of emotion regulation success, the enhancement of prediction error-related neural activity was related to learning performance. Furthermore, functional connectivity between the ventral tegmental area and ventrolateral prefrontal cortex, an area involved in regulation, was specifically increased during emotion regulation and likewise related to learning performance. Our data, therefore, provide first-time evidence that beyond reducing emotional responses, cognitive emotion regulation affects learning by enhancing prediction error-related activity, potentially via tegmental dopaminergic pathways.

Socially-induced cognitive emotion regulation (Social-Reg) is crucial for emotional well-being and social functioning; however, its brain mechanisms remain poorly understood. Given that both social cognition and cognitive emotion regulation engage key regions of the default-mode network (DMN), we hypothesized that Social-Reg would rely on the DMN, and that its effectiveness would be associated with social functioning. During functional MRI, negative emotions were elicited by pictures, and – via short instructions – a psychotherapist either down-regulated participants' emotions by employing reappraisal (Reg), or asked them to simply look at the pictures (Look). Adult Attachment Scale was used to measure social functioning. Contrasting Reg versus Look, aversive emotions were successfully reduced during Social-Reg, with increased activations in the prefrontal and parietal cortices, precuneus and the left temporo-parietal junction. These activations covered key nodes of the DMN and were associated with Social-Reg success. Furthermore, participants' attachment security was positively correlated with both Social-Reg success and orbitofrontal cortex involvement during Social-Reg. In addition, specificity of the neural correlates of Social-Reg was confirmed by comparisons with participants' DMN activity at rest and their brain activations during a typical emotional self-regulation task based on the same experimental paradigm without a psychotherapist. Our results provide first evidence for the specific involvement of the DMN in Social-Reg, and the association of Social-Reg with individual differences in attachment security. The findings suggest that DMN dysfunction, found in many neuropsychiatric disorders, may impair the ability to benefit from Social-Reg.

Objective: Abnormal brain networks have been observed in patients with obsessive-compulsive disorder (OCD). However, detailed network hub and connectivity changes remained unclear in treatment-naive patients with OCD. Here, we sought to determine whether patients show hub-related connectivity changes in their whole brain functional networks. Methods: We used resting-state functional magnetic resonance imaging data and voxel-based graph-theoretic analysis to investigate functional connectivity strength and hubs of whole-brain networks in 29 treatment-naive patients with OCD and 29 age-and gender-matched healthy controls. Correlation analysis was applied for potential associations with OCD symptom severity. Results: OCD selectively targeted brain regions of higher functional connectivity strength than the average including brain network hubs, mainly distributed in the cortico-striato-thalamo-cortical (CSTC) circuits and additionally parietal, occipital, temporal and cerebellar regions. Moreover, affected functional connectivity strength in the cerebellum, the medial orbitofrontal cortex and superior occipital cortex was significantly associated with global OCD symptom severity. Conclusion: Our results provide the evidence about OCD-related brain network hub changes, not only in the CSTC circuits but more distributed in whole brain networks. Data suggest that whole brain network hub analysis is useful for understanding the pathophysiology of OCD. (C) 2015 ELSEVIER. All rights reserved.