EEG microstate periodicity explained by rotating phase patterns of resting-state alpha oscillations

  • Spatio-temporal patterns in electroencephalography (EEG) can be described by microstate analysis, a discrete approximation of the continuous electric field patterns produced by the cerebral cortex. Resting-state EEG microstates are largely determined by alpha frequencies (8-12 Hz) and we recently demonstrated that microstates occur periodically with twice the alpha frequency. To understand the origin of microstate periodicity, we analyzed the analytic amplitude and the analytic phase of resting-state alpha oscillations independently. In continuous EEG data we found rotating phase patterns organized around a small number of phase singularities which varied in number and location. The spatial rotation of phase patterns occurred with the underlying alpha frequency. Phase rotors coincided with periodic microstate motifs involving the four canonical microstate maps. The analytic amplitude showed no oscillatory behaviour and was almost static across time intervals of 1-2 alpha cycles, resulting in the global pattern of a standing wave. In n=23 healthy adults, time-lagged mutual information analysis of microstate sequences derived from amplitude and phase signals of awake eyes-closed EEG records showed that only the phase component contributed to the periodicity of microstate sequences. Phase sequences showed mutual information peaks at multiples of 50 ms and the group average had a main peak at 100 ms (10 Hz), whereas amplitude sequences had a slow and monotonous information decay. This result was confirmed by an independent approach combining temporal principal component analysis (tPCA) and autocorrelation analysis. We reproduced our observations in a generic model of EEG oscillations composed of coupled non-linear oscillators (Stuart-Landau model). Phase-amplitude dynamics similar to experimental EEG occurred when the oscillators underwent a supercritical Hopf bifurcation, a common feature of many computational models of the alpha rhythm. These findings explain our previous description of periodic microstate recurrence and its relation to the time scale of alpha oscillations. Moreover, our results corroborate the predictions of computational models and connect experimentally observed EEG patterns to properties of critical oscillator networks.
Metadaten
Author:Frederic von Wegner, Sebastian BauerORCiDGND, Felix RosenowORCiDGND, Jochen TrieschORCiD, Helmut LaufsORCiDGND
URN:urn:nbn:de:hebis:30:3-564708
DOI:https://doi.org/10.1016/j.neuroimage.2020.117372
ISSN:1095-9572
ISSN:1053-8119
Parent Title (English):NeuroImage
Publisher:Elsevier
Place of publication:Amsterdam [u.a.]
Document Type:Article
Language:English
Date of Publication (online):2020/09/24
Date of first Publication:2020/09/24
Publishing Institution:Universitätsbibliothek Johann Christian Senckenberg
Release Date:2020/11/11
Tag:Alpha oscillations; EEG; Microstates; Phase rotors; Resting-state
Volume:224.2021
Issue:117372
Page Number:14
HeBIS-PPN:477906168
Institutes:Medizin / Medizin
Wissenschaftliche Zentren und koordinierte Programme / Frankfurt Institute for Advanced Studies (FIAS)
Dewey Decimal Classification:6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit / 610 Medizin und Gesundheit
Sammlungen:Universitätspublikationen
Licence (German):License LogoCreative Commons - Namensnennung 4.0