Emotion regulation (ER) can be conceptualized as any process by which individuals modify their emotional experiences, expressions, and physiology (Gross, 1998). Individuals encounter situations every day in which they have to regulate emotions. To achieve this, people can choose from a variety of strategies: situation selection, situation modification,

A common and mostly effective emotion regulation strategy is reappraisal. During reappraisal, activity in cognitive control brain regions increases and activity in brain regions associated with emotion responding (e.g., the amygdala) diminishes. Immediately after reappraisal, it has been observed that activity in the amygdala increases again, which might reflect a paradoxical aftereffect. While there is extensive empirical evidence for these neural correlates of emotion regulation, only few studies targeted the association with individual differences in personality traits. The aim of this study is to investigate these associations more thoroughly. Seventy-six healthy participants completed measures of broad personality traits (Big Five, Positive and Negative Affect) as well as of more narrow traits (habitual use of emotion regulation) and performed an experimental fMRI reappraisal task. Participants were instructed to either permit their emotions or to detach themselves from the presented negative and neutral pictures. After each picture, a relaxation period was included. Reappraisal success was determined by arousal ratings and activity in the amygdala. During reappraisal, we found activation in the prefrontal cortex and deactivation in the left amygdala. During the relaxation period, an immediate aftereffect was found in occipital regions and marginally in the amygdala. Neither personality traits nor habitual use of emotion regulation predicted reappraisal success or the magnitude of the aftereffect. We replicated typical activation and deactivation patterns during intentional emotion regulation and partially replicated the immediate aftereffect in the amygdala. However, there was no association between personality traits and emotion regulation success.

Neuroimaging functional connectivity analyses have shown that the negative coupling between the amygdala and cortical regions is linked to better emotion regulation (ER) in experimental task settings. However, less is known about the neural correlates of ER traits or dispositions. The present study aimed to: (1) replicate the findings of differential cortico-limbic coupling during resting-state depending on the dispositional use of emotion regulation strategies. Furthermore, the study aimed to: (2) extend prior findings by examining whether differences in cortico-limbic coupling during resting-state predict experiential and neuronal ER success in a standard ER task. To this end, N = 107 healthy adults completed the Emotion Regulation Questionnaire (ERQ), underwent an 8-min resting-state fMRI acquisition, and completed a reappraisal task during fMRI. Functional connectivity maps of basolateral and centromedial amygdala nuclei were estimated with a seed-based approach regarding associations with regions of the prefrontal cortex and were then correlated with ERQ scores as well as experiential and neuronal ER success. All hypotheses and the analysis plan are preregistered at https://osf.io/8wsgu. Opposed to prior findings, we were not able to replicate a correlation of dispositional ER strategy use with functional connectivity between the amygdala and PFC regions (p > 0.05, FWE-corrected). Furthermore, there was no association of experiential and neuronal reappraisal success with functional connectivity between amygdala and insula as well as PFC (p > 0.05, FWE-corrected). The present preregistered study calls into question the reported association between individual differences in resting-state cortico-limbic connectivity and dispositional use of ER strategies. However, ongoing advances in functional brain imaging and distributed network approaches may leverage the identification of reliable functional connectivity patterns that underlie successful emotion regulation.

When individuals set goals, they consider the subjective value (SV) of the anticipated reward and the required effort, a trade-off that is of great interest to psychological research. One approach to quantify the SVs of levels of a cognitive task is the Cognitive Effort Discounting Paradigm by Westbrook and colleagues (2013). However, it fails to acknowledge the highly subjective nature of effort, as it assumes a unidirectional, inverse relationship between task load and SVs. Therefore, it cannot map differences in effort perception that arise from traits like Need for Cognition, since individuals who enjoy effortful cognitive activities likely do not prefer the easiest level. We aim to replicate the analysis of Westbrook and colleagues with our adaptation, the Cognitive and Emotion Regulation Effort Discounting paradigm, which quantifies SVs without assuming that the easiest level is preferred, thereby enabling the quantification of SVs for tasks without objective order of task load.

Individuals have a repertoire of emotion regulation (ER) strategies at their disposal, which they can use more or less flexibly. In ER flexibility research, strategies that facilitate goal achievement are considered adaptive and therefore are subjectively valuable. Individuals are motivated to reduce their emotional arousal effectively and to avoid cognitive effort. Perceived costs of ER strategies in the form of effort, however, are highly subjective. Subjective values (SVs) should therefore represent a trade-off between effectiveness and subjectively required cognitive effort. However, SVs of ER strategies have not been determined so far. We present a new paradigm for quantifying individual SVs of ER strategies by offering monetary values for ER strategies in an iterative process. N = 120 participants first conducted an ER paradigm with the strategies distraction, distancing, and suppression. Afterwards, individual SVs were determined using the new CAD paradigm. SVs significantly predicted later choice for an ER strategy (χ2 (4, n = 119) = 115.40, p < 0.001, BF10 = 1.62 × 1021). Further, SVs were associated with Corrugator activity (t (5, 618.96) = 2.09, p = 0.037, f2 = 0.001), subjective effort (t (5, 618.96) = − 13.98, p < 0.001, f2 = 0.035), and self-reported utility (t (5, 618.96) = 29.49, p < 0.001, f2 = 0.155). SVs were further associated with self-control (t (97.97) = 2.04, p = 0.044, f2 = 0.002), but not with flexible ER. With our paradigm, we were able to determine subjective values. The trait character of the values will be discussed. Protocol registration The stage 1 protocol for this Registered Report was accepted in principle on July 19, 2022. The protocol, as accepted by the journal, can be found at: https://doi.org/10.17605/OSF.IO/FN9BT.