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Functional networks underlying emotion processing

Periodic Reporting for period 1 - PFC-AMY (Functional networks underlying emotion processing)

Reporting period: 2018-09-03 to 2020-09-02

Experiencing emotions is part of our daily life. Sometimes, these emotions can be intense, and we need to control them. Emotion regulation (ER) describes our ability to effectively manage emotional experiences. It increases our general well-being, performance at work and personal and professional relationships. Impairments in self-regulation of emotions are a substantial aspect of neuropsychiatric disorders such as anxiety disorder, major depression, bipolar disorder, and borderline personality disorder. These disorders account for up to 40% of years lived with disability, with depression as the main cause. Up to 50% of chronic sick leavers are due to depression, thus the cost of mood disorders and anxiety in the EU is about 170 billion Euro per year. Key characteristics of these disorders are changes in emotion processing, i.e. emotion perception, emotion reactivity and emotion regulation . From a brain network perspective, these emotion processing alterations were found to be associated with hypoactivity in the prefrontal cortex (dorsolateral and ventrolateral prefrontal cortex, dlPFC and vlPFC), while at the same time limbic hyperactivity (i.e. in the amygdala) was observed. In this project, we aimed to indetify brain regions that are reliably activated during ER and that might consitute a biomarker for clinical research.
In the first step ,we addressed for the first time the issue of the test-retest reliability of brain activation during emotion regulation by acquiring 7T fMRI data. For this, 25 participants (21 female, age: M=22.84 ± 3.27years) performed a well-established emotion regulation task during three scanning sessions separated by one week. We acquired four runs/session and 80 trials/session using the CMRR multiband EPI sequence (TR=1.4s; TE=23ms; 78 slices; voxel size=1.5x1.5x1.2mm3) at ultra-high field (7 Tesla). Specifically, we focused on the reliability of regions within four different networks shown to be involved in emotion generation and regulation that were derived from a recent meta-analysis (Morawetz et al., 2020). The effect of emotion regulation was demonstrated on the behavioral and neuronal level. First, emotion regulation was successful as indicated by high emotion regulation success across all sessions. Second, in accord with previous findings, emotion regulation compared with the control condition across all sessions was associated with increased activation in frontal (IFG, SFG, SMA), temporal (MTG) and parietal (precuneus) regions. During emotion generation, i.e. control condition vs. emotion regulation condition, activity in the frontal (IFG, SMA), the temporal (STG) and the cingulate cortex as well as the insula was enhanced, in line with previous research (Morawetz et al., 2017; Ochsner et al., 2004). With regard to test-retest reliability, our results yielded good reliability of a well-established emotion regulation task on a behavioral level. Test-retest reliability of underlying neural networks varied considerable across the networks and respective ROIs. Importantly, prefrontal and temporal regions demonstrated good to excellent test-retest reliability during the down-regulation of emotions, which implies that these regions might represent stable core regions supporting cognitive emotion regulation that can be studied on an individual subject level.

In the second step, we determined which brain regions are functionally coupled with the amygdala during emotion regulation. A myriad of neuroimaging studies has investigated the neural underpinnings of emotion regulation. 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. Overall, convergent connectivity during emotion regulation independent of regulation strategy and goal between the amygdala and the left ventrolateral prefrontal cortex (vlPFC) emerged. 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 of the results
• First investigation of emotion regulation at ultra-high magnetic field (7T)
• First assessment of test-retest reliability of a well-established emotion regulation task
• Region- and voxel-wise test-retest reliability between 3 sessions
• Reliability of ROIs within 4 neuronal networks of emotion regulation and generation
• Assessment of the reliability of rs-fMRI connectivity within 4 neuronal networks of emotion regulation and generation
• First coordinate-based meta-analysis on PPI studies examining emotion regulation
• Indication of the robustness of task-modulated prefrontal-amygdala coupling
• Indication of highly reliable networks involved in emotion regulation

Scientific impact. The current findings will inform theoretical, biological and psychological models of emotion regulation, extend previous models and help formulate testable hypotheses about the role of different brain regions in emotion regulation.

Societal impact. The findings of the project are fundamental for the development of personalized prevention and intervention programs that aim to foster well-being, resilience and coping with negative emotions in daily life and thus help to improve interchange between individuals and support a respectful and positive society.

Clinical impact. The findings of the project could be directly transferred in a clinical setting. The demonstration of high test-retest reliability of fMRI data in the field of emotion regulation will impact the clinical assessment of emotion regulation ability in affective disorders and provide first evidence for an useful indicator for individual characteristics of brain functions. Our findings thus support the role of prefrontal and temporal regions as promising candidates for the study of individual differences in emotion regulation as well as for neurobiological biomarkers in clinical neuroscience research.
Networks inviolved in emotion regulation. Realibility of these networks has been assessed.