Macroscale dynamics of EEG microstates constitute the periodic and aperiodic features of the neural power spectrum
- 1University of Kentucky
Abstract
The global signal characteristics of scalp-recorded electroencephalography (EEG) are composed of periodic oscillatory rhythms and aperiodic broadband fluctuations that together comprise the neural power spectrum. Spectral decomposition of these features has long served as the primary window into the macroscale characteristics of human brain activity. Here, we propose that the primary periodic rhythms and majority share of broadband spectral power within the brain's dominant frequencies are the frequency-domain representations of the dynamics of EEG microstates. Microstates are characterized by a small repertoire of topographic voltage configurations that each reflect the momentary functional state of the cortex, and it is their time-domain dynamics that mathematically constitute periodic and aperiodic spectral features. We isolated and removed the spatial projections of distinct microstate configurations from high-density EEG using orthogonal subspace projection applied to both the surface scalp recordings and their modeled cortical generators to computationally test this dependency. Spectral parameterization of the residual power spectral density revealed that removing these spatial projections strongly attenuated alpha and theta rhythms and features of the aperiodic 1/f background. Selectively removing specific microstate configurations also demonstrated that each configuration aligned with spatially specific oscillatory and aperiodic 1/f components. Furthermore, correlational analyses of microstate temporal dynamics demonstrated that the average duration and temporal persistence of microstates strongly correlate with periodic alpha power, theta power, and the aperiodic 1/f background. Our findings suggest that dominant periodic and aperiodic spectral features are more accurately understood as the frequency-domain expressions of the dynamics of EEG microstates.
Related
- Overlapping perceptual benefits of temporal attention in aperiodic and periodic streams are mediated by delta phase alignment, but not alpha suppression, in sensory circuits
- Sequential syntax of EEG microstates captures the temporal dynamics of inhibitory control
- Aperiodic dynamics track cortical state shifts during sleep K-complexes
- Multi-Methodological Characterization of Sleep Deprivation: From Standard EEG Power Spectra to Aperiodic Dynamics in Humans and Mice.
- Resolution-aware spectral parameterization reveals robust context-dependent aperiodic EEG dynamics during real-world table tennis
BibTeX
@misc{zanesco2026macroscale,
title = {{Macroscale dynamics of EEG microstates constitute the periodic and aperiodic features of the neural power spectrum}},
author = {A. P. Zanesco and R. A. Perez},
howpublished = {bioRxiv},
year = {2026},
month = jul,
doi = {10.64898/2026.07.28.741333},
url = {https://www.biorxiv.org/content/10.64898/2026.07.28.741333v2},
note = {CC BY-NC},
}
RIS
TY - UNPB
TI - Macroscale dynamics of EEG microstates constitute the periodic and aperiodic features of the neural power spectrum
AU - A. P. Zanesco
AU - R. A. Perez
PY - 2026
DA - 2026/07/28
PB - bioRxiv
DO - 10.64898/2026.07.28.741333
UR - https://www.biorxiv.org/content/10.64898/2026.07.28.741333v2
AB - The global signal characteristics of scalp-recorded electroencephalography (EEG) are composed of periodic oscillatory rhythms and aperiodic broadband fluctuations that together comprise the neural power spectrum. Spectral decomposition of these features has long served as the primary window into the macroscale characteristics of human brain activity. Here, we propose that the primary periodic rhythms and majority share of broadband spectral power within the brain's dominant frequencies are the frequency-domain representations of the dynamics of EEG microstates. Microstates are characterized by a small repertoire of topographic voltage configurations that each reflect the momentary functional state of the cortex, and it is their time-domain dynamics that mathematically constitute periodic and aperiodic spectral features. We isolated and removed the spatial projections of distinct microstate configurations from high-density EEG using orthogonal subspace projection applied to both the surface scalp recordings and their modeled cortical generators to computationally test this dependency. Spectral parameterization of the residual power spectral density revealed that removing these spatial projections strongly attenuated alpha and theta rhythms and features of the aperiodic 1/f background. Selectively removing specific microstate configurations also demonstrated that each configuration aligned with spatially specific oscillatory and aperiodic 1/f components. Furthermore, correlational analyses of microstate temporal dynamics demonstrated that the average duration and temporal persistence of microstates strongly correlate with periodic alpha power, theta power, and the aperiodic 1/f background. Our findings suggest that dominant periodic and aperiodic spectral features are more accurately understood as the frequency-domain expressions of the dynamics of EEG microstates.
ER -