Macroscale dynamics of EEG microstates determine the periodic and aperiodic features of the neural power spectrum

Abstract

The global signal characteristics of scalp-recorded electroencephalography (EEG) are composed of periodic oscillatory rhythms and aperiodic broadband fluctuations that together constitute the neural power spectrum. Spectral decomposition of these features has long served as the primary window into the macroscale characteristics of human brain activity. However, prevailing interpretations of spectral features lack a unifying mechanistic framework and often conflate activity resulting from distinct neural sources. Here, we propose that the primary periodic rhythms and majority share of broadband spectral power within the brains dominant frequencies originate from the brain network architecture responsible for generating EEG microstates. These microstates consist of a small repertoire of quasi-stable topographic voltage configurations that each reflect the momentary functional state of the cortex, and it is their dynamics that generate periodic and aperiodic spectral features. To computationally test this generating mechanism, we isolated and removed the spatial projections of microstates from high-density EEG using orthogonal subspace projection applied to both the surface scalp recordings and their modeled cortical generators. Spectral parameterization of the residual power spectral density revealed that removing seven distinct microstates strongly attenuated alpha and theta rhythms and features of the aperiodic 1/f background. Selectively removing specific topographic configurations also demonstrated that each microstate possesses independent oscillatory generators and unique 1/f aperiodic structures. Together, our findings suggest that dominant periodic and aperiodic spectral features are more accurately understood as the frequency-domain expressions of the distributed brain networks generating EEG microstates.