BACKGROUND: Many studies have attempted to understand the neural basis of internet gaming disorder (IGD) to explore if IGD could be diagnosed as an addictive behavior. However, those findings were often inconsistent due to the participants having varying craving levels. Individual brain activities in the abstinence state are different from that in the neutral state. Therefore, exploring the responses of the brain during abstinence in IGD and comparing them with substance addiction is crucial in understanding this complex, craving-prone disorder. METHODS: Three groups of male participants were recruited: IGD (61), tobacco use disorder (TUD) (61), and health controls (80). Resting-state functional Magnetic Resonance Imaging data were collected after brief abstinence (not gaming/smoking for about 1.5 h). First, we identified abnormal brain regions with altered amplitude of low-frequency fluctuations (ALFF) in IGD and TUD. Then, using these regions as the regions of interest, we conducted a functional connectivity (FC) analysis to explore the similarities and differences between IGD and TUD. Finally, we used a neural network analysis to build a classification model based on ALFF results. RESULTS: The abnormal brain regions with altered ALFF were observed in both IGD and TUD, including the superior frontal gyrus, orbitofrontal cortex, precentral gyrus, caudate, and thalamus. FC analysis showed similarities in the orbitofrontal regions, specifically between caudate-nucleus accumbens and thalamus-precentral gyrus, and differences in the executive control and reward regions. Neural network analysis demonstrated that abnormal ALFF brain regions can effectively classify addicted individuals from health controls. CONCLUSIONS: This study showed that brain regions in IGD and TUD had similar ALFF changes during brief abstinence. However, FC analyses revealed contrasting results. FC in IGD increased, while it decreased in TUD. These differences may be due to IGD's internal craving, unlike nicotine for TUD. These findings deepen our understanding of the neural mechanisms of IGD.