This paper reviews and synthesizes functional imaging research that over the past decade has begun to offer new insights into the brain mechanisms underlying emotion regulation. Towards that end, the first section of the paper outlines a model of the processes and neural systems involved in emotion generation and regulation. The second section surveys recent research supporting and elaborating the model, focusing primarily on studies of the most commonly investigated strategy, which is known as reappraisal. At its core, the model specifies how prefrontal and cingulate control systems modulate activity in perceptual, semantic and affect systems as a function of one's regulatory goals, tactics, and the nature of the stimuli and emotions being regulated. This section also shows how the model can be generalized to understand the brain mechanisms underlying other emotion regulation strategies as well as a range of other allied phenomena. The third and last section considers directions for future research, including how basic models of emotion regulation can be translated to understand changes in emotion across the lifespan and in clinical disorders.

In recent years, an explosion of neuroimaging studies has examined cognitive reappraisal, an emotion regulation strategy that involves changing the way one thinks about a stimulus in order to change its affective impact. Existing models broadly agree that reappraisal recruits frontal and parietal control regions to modulate emotional responding in the amygdala, but they offer competing visions of how this is accomplished. One view holds that control regions engage ventromedial prefrontal cortex (vmPFC), an area associated with fear extinction, that in turn modulates amygdala responses. An alternative view is that control regions modulate semantic representations in lateral temporal cortex that indirectly influence emotion-related responses in the amygdala. Furthermore, while previous work has emphasized the amygdala, whether reappraisal influences other regions implicated in emotional responding remains unknown. To resolve these questions, we performed a meta-analysis of 48 neuroimaging studies of reappraisal, most involving downregulation of negative affect. Reappraisal consistently 1) activated cognitive control regions and lateral temporal cortex, but not vmPFC, and 2) modulated the bilateral amygdala, but no other brain regions. This suggests that reappraisal involves the use of cognitive control to modulate semantic representations of an emotional stimulus, and these altered representations in turn attenuate activity in the amygdala.

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Although adolescents’ emotional lives are thought to be more turbulent than those of adults, it is unknown whether this difference is attributable to developmental changes in emotional reactivity or emotion regulation. Study 1 addressed this question by presenting healthy individuals aged 10–23 with negative and neutral pictures and asking them to respond naturally or use cognitive reappraisal to down-regulate their responses on a trial-by-trial basis. Results indicated that age exerted both linear and quadratic effects on regulation success but was unrelated to emotional reactivity. Study 2 replicated and extended these findings using a different reappraisal task and further showed that situational (i.e., social vs. nonsocial stimuli) and dispositional (i.e., level of rejection sensitivity) social factors interacted with age to predict regulation success: young adolescents were less successful at regulating responses to social than to nonsocial stimuli, particularly if the adolescents were high in rejection sensitivity. Taken together, these results have important implications for the inclusion of emotion regulation in models of emotional and cognitive development.

Emotion regulation is a critical life skill that develops throughout childhood and adolescence. Despite this development in emotional processes, little is known about how the underlying brain systems develop with age. This study examined emotion regulation in 112 individuals (aged 6-23 years) as they viewed aversive and neutral images using a reappraisal task. On "reappraisal" trials, participants were instructed to view the images as distant, a strategy that has been previously shown to reduce negative affect. On "reactivity" trials, participants were instructed to view the images without regulating emotions to assess baseline emotional responding. During reappraisal, age predicted less negative affect, reduced amygdala responses and inverse coupling between the ventromedial prefrontal cortex (vmPFC) and amygdala. Moreover, left ventrolateral prefrontal (vlPFC) recruitment mediated the relationship between increasing age and diminishing amygdala responses. This negative vlPFC-amygdala association was stronger for individuals with inverse coupling between the amygdala and vmPFC. These data provide evidence that vmPFC-amygdala connectivity facilitates vlPFC-related amygdala modulation across development.

SummaryData analysis workflows in many scientific domains have become increasingly complex and flexible. To assess the impact of this flexibility on functional magnetic resonance imaging (fMRI) results, the same dataset was independently analyzed by 70 teams, testing nine ex-ante hypotheses. The flexibility of analytic approaches is exemplified by the fact that no two teams chose identical workflows to analyze the data. This flexibility resulted in sizeable variation in hypothesis test results, even for teams whose statistical maps were highly correlated at intermediate stages of their analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Importantly, meta-analytic approaches that aggregated information across teams yielded significant consensus in activated regions across teams. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset. Our findings show that analytic flexibility can have substantial effects on scientific conclusions, and demonstrate factors related to variability in fMRI. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for multiple analyses of the same data. Potential approaches to mitigate issues related to analytical variability are discussed.

This study used functional MRI (fMRI) to examine a novel aspect of emotion regulation in adolescent development: whether age predicts differences in both the concurrent and lasting effects of emotion regulation on amygdala response. In the first active regulation phase of the testing session, fMRI data was collected while 56 healthy individuals (age range: 10.50–22.92 years) reappraised aversive stimuli so as to diminish negative responses to them. After a short delay, the second re-presentation phase involved passively viewing the aversive images from the reappraisal task. During active regulation, older individuals showed greater drops in negative affect and inverse rostrolateral prefrontal-amygdala connectivity. During re-presentation, older individuals continued to show lasting reductions in the amygdala response to aversive stimuli they had previously reappraised, an effect mediated by rostrolateral PFC. These data suggest that one source of heightened emotionality in adolescence is a diminished ability to cognitively down-regulate aversive reactions.

The ability to successfully regulate emotion plays a key role in healthy development and the maintenance of psychological well-being. Although great strides have been made in understanding the nature of regulatory processes and the consequences of deploying them, a comprehensive understanding of emotion regulation that can specify what strategies are most beneficial for a given person in a given situation is still a far-off goal. In this review, we argue that moving toward this goal represents a central challenge for the future of the field. As an initial step, we propose a concrete framework that (i) explicitly considers emotion regulation as an interaction of person, situation, and strategy, (ii) assumes that regulatory effects vary according to these factors, and (iii) sets as a primary scientific goal the identification of person-, situation-, and strategy-based contingencies for successful emotion regulation. Guided by this framework, we review current questions facing the field, discuss examples of contextual variation in emotion regulation success, and offer practical suggestions for continued progress in this area.