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This systematic review aims to identify and synthesize existing research that has combined electroencephalography (EEG) with the Implicit Association Test (IAT) to investigate implicit bias. By systematically reviewing the literature, this study will provide a comprehensive overview of how EEG has been used to capture the neural correlates of implicit associations across different domains, including race, gender, mental health, and substance use. A key focus of this review is to characterize the methodological approaches employed in these studies. This includes examining the EEG parameters used, such as electrode placement, frequency bands, and event-related potentials (ERPs) commonly analyzed in response to implicit bias tasks. Additionally, the review will consider variations in IAT design, including stimulus categories and response conditions, as well as the characteristics of the study populations, such as sample size, demographics, and distinctions between clinical and non-clinical groups. Beyond identifying and categorizing existing research, this review will synthesize the findings to determine common patterns in the neural processing of implicit bias. Particular attention will be given to well-documented ERP components such as the P300, N400, and late positive potential (LPP), which have been implicated in cognitive and affective processing related to bias. The methodological quality of the included studies will also be assessed to evaluate the reliability, validity, and consistency of findings across the literature.