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Abstract

Amygdala dysregulation is a core dysfunction in multiple psychiatric disorders. Thus, the introduction of Amygdala self-modulation through NeuroFeedback (NF) is a valuable non-invasive intervention tool. Yet, the feasibility and best practices of Amygdala-NF have not been systematically examined. The current perspective presents a thorough review of relevant studies, an analytic summary of design parameters, and examination of brain mechanisms related to successful Amygdala-self-modulation. A meta-analysis of 33 publications showed that real Amygdala-NF facilitates learned modulation compared to control conditions. In addition, while variability in design choices could be explained by the involved amygdala-related valance domains (positive, negative), in most cases the targeted neuro-behavioral processes were not directly assessed as an outcome measure. Lastly, re-analyzing six data sets of Amygdala-fMRI-NF revealed that successful Amygdala down-modulation is coupled with deactivation of the posterior insula and nodes in the Default-Mode-Network. Our findings point to Amygdala self-modulation can be acquired using NF. Yet, further controlled studies, relevant tasks before and after treatment, and neural 'target engagement' measures are critically needed to establish efficacy and specificity.