Concurrent separation of phase-locked and non-phase-locked activity

Brain dynamics recorded via electroencephalography (EEG) is conceptualized as a sum of two components, "phase-locked" and "non-phase-locked" to the stimulus. Both activities are understood to be stemming from different neuronal mechanisms and hence accurately characterizing them is of immense importance in neuroscientific studies. Here, we discuss the drawbacks of currently used methods to separate the phase-locked and non-phase-locked activity and propose a new method that decomposes the two components simultaneously. First, we demonstrate that single-trial separation of phase-locked and non-phase-locked power is an ill-posed problem. Second, using simulations where ground truth validation is possible, we elucidate the drawbacks of the widely used averaging method and efficacy of the proposed concurrent phaser method (CPM). Using two experimental datasets, audio oddball EEG data and auditory steady-state responses (ASSR) we show how the empirical signal-to-noise estimates warrant the usage of CPM to separate phase-locked and non-phase-locked activity.