Brain-Computer Interfaces in Modern Neurosurgery: Advances, Clinical Applications, and Future Perspectives
Brain-computer interfaces (BCIs) have emerged as one of the most significant technological innovations in modern neurosurgery, integrating neuroscience, biomedical engineering, artificial intelligence, and clinical neurology to establish direct communication between the brain and external devices. This review provides a comprehensive analysis of the current scientific evidence regarding the neurophysiological foundations, technological evolution, clinical applications, limitations, and future perspectives of BCIs in neurosurgical practice. A qualitative documentary review was conducted following the Scientific Method, using peer-reviewed literature retrieved from internationally recognized databases, including PubMed, Scopus, Web of Science, ScienceDirect, IEEE Xplore, and Google Scholar. The analyzed evidence indicates that current clinical applications are primarily focused on motor restoration, neurorehabilitation, communication recovery, speech neuroprostheses, and adaptive neuromodulation for neurological disorders such as spinal cord injury, stroke, Parkinson's disease, amyotrophic lateral sclerosis, and drug-resistant epilepsy. Recent advances in machine learning, implantable electrodes, wireless technologies, and closed-loop therapeutic systems have substantially improved neural decoding performance and expanded the potential clinical utility of BCIs. However, important challenges remain regarding long-term signal stability, biocompatibility, surgical safety, economic accessibility, regulatory frameworks, and equitable implementation across different healthcare systems. The available evidence suggests that continued multidisciplinary collaboration and technological innovation will facilitate the progressive integration of BCIs into routine neurosurgical care, supporting personalized therapeutic strategies aimed at improving functional recovery, communication, and quality of life in patients with complex neurological disorders.