Meta-analytic brain networks underlying emotion regulation

Recent models suggest that cognitive emotion regulation is based upon neural systems implicated in generation and regulation of emotional responses as well as systems with an undefined or intermediary role. Despite the wealth of research in this field, the exact functional nature and different topological features of these neural networks remain elusive.  To shed light on this, we applied a meta-analytic grouping technique to define network topology of clusters of emotion regulation experiments. To quantify these networks, we performed functional decoding using metadata terms (BrainMap). We included 100 studies, and a total of 225 experiments on over 4200 subjects. The results revealed four clusters of meta-analytic groupings: Network1 consisted of vlPFC, SMA, temporal and parietal areas. Functional decoding indicated that the network is associated with language, semantics and speech. Network2 included dlPFC, parietal cortex and posterior cingulate cortex and is associated to attention and working memory. Network3 involved the amygdala, thalamus, hippocampus and anterior insula and is related to paradigms implicated in emotion processing. Network4 consisted of the precuneus, posterior insula and superior parietal lobe and is associated with paradigms of action execution, somesthesis, and pain.  Our findings provide a link between distinct neural networks and cognitive and affective processes involved in emotion regulation thereby informing psychological theory.