Dysregulation of the prefrontal cortex, amygdala, and hippocampus, along with alterations in P300 amplitude and abnormalities in the theta and beta bands, has been closely linked to the onset and pathophysiology of depression. Consequently, integrating electroencephalograph-based emotion recognition technology into brain‒computer interface systems offers the potential for real-time identification and modulation of emotional states through continuous interaction between the brain‒computer interface system and brain activity. This closed-loop system could precisely control neural stimulation in brain regions associated with emotional disorders, potentially alleviating the distressing memories of traumatic events. Although the efficacy of the brain‒computer interface in treating depression still requires validation through extensive clinical trials, its inherent real-time feedback and adaptive capabilities present a promising avenue for depression therapy. This review aims to explore the neuroanatomical mechanisms and neural activity patterns associated with depression and evaluate the potential of brain‒computer interface technology as a treatment modality. The objectives include summarizing key brain regions and neural networks involved in depression, analyzing their activity patterns, and assessing the impact of brain‒computer interface technology on these regions to provide theoretical support for future clinical trials. Significant functional abnormalities have been identified in the prefrontal cortex, amygdala, and hippocampus of patients with depression. The gray matter density, functional connectivity, and neural activity in these regions are closely associated with the severity of depressive symptoms. Common features in patients with depression include a reduced P300 amplitude and increased θ and α current density. Brain‒computer interface technology has demonstrated potential in modulating these abnormal neural activities, particularly in emotion recognition and regulation. When combined with techniques such as repetitive transcranial magnetic stimulation and deep brain stimulation, brain‒computer interface may provide effective interventions for managing emotional states in patients with depression. This review confirms the association between depression and functional abnormalities in specific brain regions and suggests that brain‒computer interface technology offers promising therapeutic potential by modulating abnormal neural activity. Brain‒computer interface could represent a novel treatment approach for depression. Future research should focus on validating the practical applications, efficacy, and safety of brain‒computer interface in treating depression.