Background: Altered large-scale brain systems, including structural alterations and resting-state functional connectivity (rs-FC) changes, have been demonstrated as effective system-level biomarkers for revealing potential neural mechanism of multiple brain disorders. However, identifying consistent abnormalities of large-scale brain systems in behavioral addictions (BA) is challenging due to varying methods and inconsistent results. Therefore, the aim of this study was to identify the significantly abnormal large-scale brain systems in BA. Method: PubMed, OVID Embase, OVID Medline, and Web of Science were searched with relevant keywords to identify potential studies. A total of 52 studies including 35 rs-FC studies and 17 structural studies were examined by extracting the coordinates of seeds and target brain regions. The seeds were then categorized into predefined seven networks by their locations based on previous parcellations in rs-FC studies, followed by pooling the results in those networks. Results: The rs-FC findings illustrated that BA were characterized as abnormal networks in response to inhibition, salience attribution, self-referential mental process, and reward-driven behaviors. Meanwhile, meta-analysis of structural studies showed decreased gray matter volume in the anterior cingulate cortex, extending to the middle cingulate cortex and the superior frontal gyrus. Importantly, overlapping regions in the cingulate cortex and anterior thalamus projections extending to caudate regions exhibited both dysfunctions in structure and rs-FC. Conclusions: This study highlighted substantial dysconnectivity in BA, which might result in impaired response to inhibition and salience attribution. Therefore, this study might provide novel insights of neural biomarkers for clinical diagnoses and treatment targets for BA.  Kulcsszavak: meta-analysis, behavioral addiction, frontoparietal network, ventral attention network, insula