From EEG Source Localization to Brain Network Analysis: A Computational Neuroscience Perspective

Abstract

Simple Summary Electroencephalography is a safe and noninvasive technique for recording the brain’s electrical activity that has long been used to study brain function and diagnose neurological disorders. Recent advances now allow researchers to estimate where the electrical signals originate inside the brain and examine how different brain regions communicate as networks, rather than as isolated areas, developments that provide new opportunities to better understand brain function, improve the diagnosis and treatment of disorders such as epilepsy, and identify reliable markers of disease. This review outlines the principles of brain signal localization, methods for analyzing communication among brain regions, and approaches for studying the organization of brain networks, in addition to discussing how artificial intelligence can help analyze these complex data while emphasizing the importance of accurate modeling, standardized analysis methods, and careful validation. By investigating these rapidly developing fields together, this review highlights current achievements, remaining challenges, and future directions for development. These advances have the potential to improve both neuroscience research and clinical care by providing more accurate and personalized tools for understanding brain disorders.