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However, this kind of decision\u2010making has been largely overlooked in the literature. The current study investigated whether behavioral preference would change during sequential decisions, and the neural processes underlying the potential changes. For this purpose, we revised the classic balloon analogue risk task and recorded the electroencephalograph (EEG) signals associated with each step of decision\u2010making. Independent component analysis performed on EEG data revealed that four EEG components elicited by periodic feedback in the current step predicted participants\u2019 decisions (gamble vs. no gamble) in the next step. In order of time sequence, these components were: bilateral occipital alpha rhythm, bilateral frontal theta rhythm, middle frontal theta rhythm, and bilateral sensorimotor mu rhythm. According to the information flows between these EEG oscillations, we proposed a brain model that describes the temporal dynamics of sequential decision\u2010making. 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