Effective amygdala-prefrontal connectivity during emotion regulation: a meta-analysis of psychophysiological interactions
Creators: name: Berboth, Stella
name: Morawetz, Carmen
Publisher: name: Zenodo
Year: 2020

description: <strong>Background</strong> In recent years, a myriad of neuroimaging studies has investigated the neural basis of emotion regulation (ER), and substantial progress has been made toward building neurally plausible models of ER. However, single studies usually provide limited insight into the function of specific brain regions. Thus, to better understand the role of the amygdala in emotion regulation and the relationship with other brain regions, we performed coordinate-based meta-analysis on studies of emotion regulation related connectivity of the amygdala which used functional magnetic resonance imaging (fMRI) and psychophysiological interaction (PPI) analysis. <strong>Methods</strong> Literature research was conducted using PubMed (www.pubmed.com) searching for combinations of keywords “emotion regulation” “affective regulation”, “reappraisal”, “fMRI”, “functional magnetic resonance imaging”, “functional MRI”, “effective connectivity”, “functional connectivity”, “PPI” and “psychophysiological interaction analysis”. The search was limited to 1<sup>st</sup> of January to 31<sup>st</sup> of December 2019 and revealed 196 studies. Based on specific inclusion/exclusion criteria, 17 studies were included in the analysis. The meta-analysis was performed using the revised version<sup>1</sup> of the activation likelihood estimation (ALE) algorithm for coordinate-based quantitative meta-analyses of neuroimaging results as implemented in GingerALE 3.0.2. Since the functional lateralization of the amygdala has been well documented, it is possible that the left and right amygdala show different patterns of task modulated connectivity. To explore this, we performed separate ALE analyses. As only 6 studies used the right amygdala as seed for the PPI analysis, we first performed an analysis based on studies using the left amygdala as seed region and then extended this analysis by including the coordinates of studies using the right amygdala as seed region for their analysis. By combining the probabilities of all reported foci for each voxel in a given experiment, modelled activation maps (MA maps) were generated. The maps were thresholded at a cluster-level family-wise error (cFWE) corrected threshold of p&lt;.05 (cluster-forming threshold at voxel-level p&lt;.001) as cFWE represents the most appropriate method for statistical inference. <strong>Results</strong> First, we performed a single dataset analysis for all studies reporting reappraisal-related activation against a control condition e.g., reappraise vs. control condition, using the left amygdala as seed region including 15 experiments, 150 foci and 568 subjects. We found one region that showed convergent connectivity with the left amygdala during regulation compared to a control condition, the left inferior frontal gyrus (IFG; BA47; x=-38, y=34, z=-8). Second, we extended the previous analysis and included the right amygdala as seed region resulting in 21 experiments, 230 foci, and 885 subjects. In addition to the left IFG, we found a second cluster of convergent connectivity in the medial frontal gyrus (MFG; BA8; x=4, y=28, z=46). <strong>Conclusions</strong> Our findings support the idea of a top-down cognitive control model of emotion regulation by demonstrating increased connectivity between the left amygdala and the left ventrolateral prefrontal cortex (vlPFC), which has previously been implicated in reappraisal<sup>2</sup> and specifically into language processes during emotion regulation<sup>3</sup>. Interestingly, both amygdalae demonstrate increased connectivity with the left vlPFC as well as the dorsomedial prefrontal cortex, a region that has been implicated into attributing mental states<sup>4</sup>. Thus, emotion regulation seems to selectively modulate amygdala connectivity to PFC regions and future studies need to address the causal relationship between these regions. <strong>References</strong> 1. Eickhoff, S. B., Bzdok, D., Laird, A. R., Kurth, F. &amp; Fox, P. T. Activation likelihood estimation meta-analysis revisited. <em>Neuroimage</em> <strong>59</strong>, 2349–2361 (2012). 2. Morawetz, C., Bode, S., Derntl, B. &amp; Heekeren, H. R. The effect of strategies, goals and stimulus material on the neural mechanisms of emotion regulation: A meta-analysis of fMRI studies. <em>Neurosci. Biobehav. Rev.</em> <strong>72</strong>, 111–128 (2017). 3. Morawetz, C. <em>et al.</em> Meta-analytic brain networks underlying emotion regulation. in <em>Annual Meeting of the Social and Affective Neuroscience Society</em> (2018). 4. Ochsner, K. N., Silvers, J. &amp; Buhle, J. T. Functional imaging studies of emotion regulation: a synthetic review and evolving model of the cognitive control of emotion. <em>Ann. N. Y. Acad. Sci.</em> <strong>1251</strong>, E1-24 (2012).