The neurobiology of internet addiction: a scoping review of developmental and gender-specific mechanisms

Background: Internet addiction (IA) constitutes a significant public health challenge, yet the distinct influence of neurodevelopmental stage and gender on its neural substrates remains under-characterized. This scoping review systematically synthesizes neuroimaging evidence to identify convergent brain alterations across IA subtypes and to disentangle the specific neural signatures associated with age and gender. Methods: Following PRISMA-ScR guidelines, we reviewed peer-reviewed studies published between 2015 and 2025. Searches were conducted across PubMed, Web of Science, and PsycINFO, focusing on investigations that explicitly incorporated age or gender as analytical factors in examining IA-related structural or functional brain changes. Results: The synthesized evidence indicates that IA is consistently associated with abnormal gray matter volume (GMV), compromised white matter integrity (WMI), and functional dysregulation within the prefrontal cortex (PFC), cingulate gyrus, and reward networks. Developmentally, findings reveal distinct trajectories: adolescents exhibit heightened vulnerability in regions governing emotion regulation and executive control, reflecting a developmental mismatch; in contrast, adults display alterations more indicative of established habit formation and reward circuit remodeling. Gender-specific patterns are also evident: males typically manifest neural alterations linked to gaming behaviors and impulse control, whereas females exhibit distinct profiles involving social-emotional processing networks. Conclusion: These findings confirm that IA pathology is not uniform but is significantly modulated by demographic factors. The evidence highlights the necessity of shifting from generalized approaches to prevention and intervention strategies that are tailored to specific developmental windows and gender profiles. Future research must prioritize longitudinal and multimodal designs to move from descriptive mapping to causal mechanistic understanding.