Abstract: Cognition encompasses attention, memory, and emotion and is fundamental to the process by which humans acquire and apply knowledge. With the acceleration of global aging, cognitive impairments such as Mild Cognitive Impairment (MCI), Alzheimer's Disease (AD), and dementia have emerged as significant health concerns. Early diagnosis and treatment of cognitive impairments can improve patients' quality of life and reduce societal burdens. However, traditional methods such as pharmacotherapy, Functional Magnetic Resonance Imaging (fMRI), and Functional Near-Infrared Spectroscopy (fNIRS) are hindered by low diagnostic accuracy, limited drug efficacy, and a lack of comprehensive assessment tools. The integration of Brain-Computer Interface (BCI) and Virtual Reality (VR) technologies offers novel solutions for cognitive diagnosis and treatment. BCI, which facilitates information exchange between the brain and computers or other devices by analyzing brain signals, has been successfully applied in the rehabilitation of motor function disorders. VR, by creating immersive virtual environments, provides realistic interactive experiences for cognitive training and rehabilitation. The combination of BCI and VR technologies enhances the effectiveness of cognitive training through multi-sensory stimulation and real-time feedback. This paper reviews the current applications of BCI and VR technologies in cognitive diagnosis and treatment. It introduces BCI diagnostic methods based on Electroencephalogram (EEG), fMRI, and fNIRS, as well as VR-based diagnostic methods, and discusses the advantages and challenges of these technologies. Additionally, this paper analyzes the contribution of cross-individual and cross-scenario EEG signal analysis to the precision and effectiveness of cognitive impairment assessment. The paper also summarizes the applications of BCI-VR technology in cognitive behavioral therapy, memory and attention training, neurorehabilitation, and emotion regulation, highlighting its potential in treating cognitive impairments. Despite the promising prospects of BCI-VR technology, challenges such as device complexity, insufficient personalization, and limited experimental samples remain. Future research directions include the miniaturization and cost reduction of devices, the development of multimodal BCI technologies, and the application of large language models. Strengthening collaborations among government, industry, academia, research institutions, and the medical field is essential to advance the clinical translation of BCI-VR technology in cognitive diagnosis and treatment.