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The ability to find the right balance between more persistent and more flexible cognitive‐control styles is known as "metacontrol." Recent findings suggest a relevance of aperiodic EEG activity and task conditions that are likely to elicit a specific metacontrol style. Here we investigated whether individual differences in aperiodic EEG activity obtained off‐task (during resting state) predict individual cognitive‐control styles under task conditions that pose different demands on metacontrol. We analyzed EEG resting‐state data, task‐EEG, and behavioral outcomes from a sample of N = 65 healthy participants performing a Go/Nogo task. We examined aperiodic activity as indicator of "neural noise" in the EEG power spectrum, and participants were assigned to a high‐noise or low‐noise group according to a median split of the exponents obtained for resting state. We found that off‐task aperiodic exponents predicted different cognitive‐control styles in Go and Nogo conditions: Overall, aperiodic exponents were higher (i.e., noise was lower) in the low‐noise group, who however showed no difference between Go and Nogo trials, whereas the high‐noise group exhibited significant noise reduction in the more persistence‐heavy Nogo condition. This suggests that trait‐like biases determine the default cognitive‐control style, which however can be overwritten or compensated for under challenging task demands. We suggest that aperiodic activity in EEG signals represents valid indicators of highly dynamic arbitration between metacontrol styles, representing the brain's capability to reorganize itself and adapt its neural activity patterns to changing environmental conditions. Via the FOOOF toolbox which calculates aperiodic exponents as indicators of "neural noise," we were able to theoretically link aperiodic EEG activity to cognitive‐control styles. We found that in demanding conditions, the modulation of aperiodic activity is more driven by stimuli and demand‐signaling information than by trait‐like biases. [ABSTRACT FROM AUTHOR]