Abstract

Given the importance of emotion regulation as a transdiagnostic factor in the development of psychopathology, a myriad of neuroimaging studies has investigated its neural underpinnings. However, single studies usually provide limited insight into the function of specific brain regions. Hence, to better understand the interaction between key regions involved in emotion generation and regulation, we performed a coordinate-based meta-analysis on functional magnetic resonance imaging (fMRI) studies that examined emotion regulation-modulated connectivity of the amygdala using psychophysiological interaction (PPI) analysis. We analyzed fifteen PPI studies using the activation likelihood estimation (ALE) algorithm. Investigating emotion regulation-modulated connectivity independent of regulation strategy and goal revealed convergent connectivity between the amygdala and the left ventrolateral prefrontal cortex (vlPFC), which was primarily driven by PPI studies implementing reappraisal as a regulation strategy. A more focused analysis testing for effective coupling during the down-regulation of emotions by using reappraisal specifically revealed convergent connectivity between the amygdala and the right dorsolateral prefrontal cortex (dlPFC), the left ventrolateral prefrontal cortex (vlPFC), and the dorsomedial prefrontal cortex (dmPFC). These prefrontal regions have been implicated in emotion regulatory processes such as working memory (dlPFC), language processes (vlPFC), and the attribution of mental states (dmPFC). Our findings suggest not only a dynamic modulation of connectivity between emotion generative and regulatory systems during the cognitive control of emotions, but also highlight the robustness of task-modulated prefrontal-amygdala coupling, thereby informing neurally-derived models of emotion regulation.

Highlights

  • Experiencing positive and negative emotions plays a central role in our daily life

  • We extended the previous analysis by including experi­ ments that integrated individual difference factors as covariates in their psychophysiological interaction (PPI) analyses such as e.g., emotion regulation success based on emotional state ratings (Morawetzet al., 2017) or based on electromyography (EMG) difference scores (Lee et al, 2012) or self-reported self-control (Paschke et al, 2016)

  • This demonstrates that the observed coupling between the ventrolateral prefrontal cortex (vlPFC) and the amygdala was not solely driven by studies implementing emotion regulation success/selfcontrol as a covariate in the PPI analysis

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Summary

Introduction

Experiencing positive and negative emotions plays a central role in our daily life. The ability to regulate our emotions in a contextdependent manner by either up- or down-regulating emotional experi­ ences is essential for our mental and physical health (Berking and Wupperman, 2012) as well as successful social interaction (Gross and John, 2003). Impairments in emotion regulation are asso­ ciated with severe affective disorders such as depression and anxiety (Sloan et al, 2017). Given that emotion regulation represents a transdiagnostic factor in the development of psychopathology, affective neuroscience has shown an intense interest in understanding the neural mechanisms that support the cognitive control of emotions during the last two decades. The most prominent framework for conceptualizing emotion regu­ lation is the process model of emotion regulation that distinguishes five families of emotion regulation strategies (Gross, 1998): situation selec­ tion, situation modification, attentional deployment (via distraction: directing attention away from the emotional stimulus; or via concen­ tration: focus on the emotional experience), cognitive change (via reappraisal: reinterpreting the emotional situation), and response modulation (via suppression: modifying the behavioral/physiological emotional response) (Webb et al, 2012). The cortical networks consist (i) of the dorsolateral prefrontal cortex (dlPFC), supplementary

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