EEG Monitoring of Temporal Anticipation in Coincidence Anticipation Timing Tasks: A Scoping Review With Recommendations.
André Felipe Dos Santos, Gabriel Chaves de Melo, Gabriela Castellano, Arturo Forner-Cordero
Abstract
Open AccessBACKGROUND: Coincidence anticipation timing (CAT) tasks require individuals to synchronize their movement with an external moving stimulus. Electroencephalography (EEG), due to its high temporal resolution, offers a valuable tool for investigating the neural processes underlying temporal anticipation in these tasks. OBJECTIVES: This scoping review aims to map the existing literature on EEG monitoring of temporal anticipation during CAT tasks, identify methodological patterns, evaluate the consistency of reported EEG markers, and highlight potential gaps. ELIGIBILITY CRITERIA: Studies were included if they examined EEG activity related to anticipatory processes during CAT tasks in human participants. SOURCES OF EVIDENCE: Studies were obtained from PubMed, Web of Science, and Scopus. A systematic search was conducted in May 2024 and updated in October 2025. CHARTING METHODS: Data were charted across studies, focusing on participant characteristics, protocols, EEG methodologies, and reported outcomes. RESULTS: Eleven studies met our criterion. Substantial methodological variability was identified in participant setup, task design, EEG acquisition, and data analysis strategies. Although some EEG markers have been recurrently explored, no neural features were consistently assessed across all studies, limiting the identification of robust markers of temporal anticipation. Reporting gaps were observed regarding participant characteristics, anticipation type, and error metrics. CONCLUSIONS: The field remains exploratory, with considerable heterogeneity across studies. To support more reliable comparisons and advance progress, this review proposes practical methodological recommendations focused on standardizing CAT task design and EEG procedures. These guidelines aim to enhance research quality and contribute to a more cohesive understanding of the neural correlates of temporal anticipation.