TY  - JOUR
AU  - Morawetz, Carmen
AU  - Riedel, Michael C.
AU  - Salo, Taylor
AU  - Berboth, Stella
AU  - Eickhoff, Simon B.
AU  - Laird, Angela R.
AU  - Kohn, Nils
TI  - Multiple large-scale neural networks underlying emotion regulation
JO  - Neuroscience & biobehavioral reviews
VL  - 116
SN  - 0149-7634
CY  - Amsterdam [u.a.]
PB  - Elsevier Science
M1  - FZJ-2020-02608
SP  - 382 - 395
PY  - 2020
AB  - Recent models suggest emotion generation, perception, and regulation rely on multiple, interacting large-scale brain networks. Despite the wealth of research in this field, the exact functional nature and different topological features of these neural networks remain elusive. Here, we addressed both using a well-established data-driven meta-analytic grouping approach. We applied k-means clustering to a large set of previously published experiments investigating emotion regulation (independent of strategy, goal and stimulus type) to segregate the results of these experiments into large-scale networks. To elucidate the functional nature of these distinct networks, we used functional decoding of metadata terms (i.e. task-level descriptions and behavioral domains). We identified four large-scale brain networks. The first two were related to regulation and functionally characterized by a stronger focus on response inhibition or executive control versus appraisal or language processing. In contrast, the second two networks were primarily related to emotion generation, appraisal, and physiological processes. We discuss how our findings corroborate and inform contemporary models of emotion regulation and thereby significantly add to the literature.Keywords: Distraction; Emotion regulation strategies; Neuroimaging; Reappraisal; Suppression; fMRI.
LB  - PUB:(DE-HGF)16
C6  - 32659287
UR  - <Go to ISI:>//WOS:000557868200028
DO  - DOI:10.1016/j.neubiorev.2020.07.001
UR  - https://juser.fz-juelich.de/record/878064
ER  -