Decomposing alpha and 1/f brain activities reveals their differential associations with cognitive processing speed

Research in cognitive neuroscience has extensively demonstrated that the temporal dynamics of brain activity are associated with cognitive functioning. The temporal dynamics mainly include oscillatory and 1/f noise-like, non-oscillatory brain activities that coexist in many forms of brain activity and confound each other’s variability. As such, observed functional associations of narrowband oscillations might have been confounded with the broadband 1/f component. Here, we investigated the relationship between resting-state EEG activity and the efficiency of cognitive functioning in N = 180 individuals. We show that 1/f brain activity plays an essential role in accounting for between-person variability in cognitive speed – a relationship that can be mistaken as originating from brain oscillations using conventional power spectrum analysis. At first glance, the power of alpha oscillations appeared to be predictive of cognitive speed. However, when dissociating pure alpha oscillations from 1/f brain activity, only the 1/f predicted cognitive speed, whereas the predictive power of alpha vanished. With this highly powered study, we disambiguate the functional relevance of the 1/f power law pattern in resting state neural activities and substantiate the necessity of isolating the 1/f component from oscillatory activities when studying the functional relevance of spontaneous brain activities. •The mixture of brain oscillation and 1/f noise obscures their functional roles.•Structural equation modelling was applied to decompose 1/f and alpha oscillation.•Parametric curve fitting was also applied to decompose 1/f and alpha oscillation.•Decomposition of 1/f and alpha reveals their differential functional associations.