Spatial neuronal synchronization and the waveform of oscillations : implications for EEG and MEG

  • Neuronal oscillations are ubiquitous in the human brain and are implicated in virtually all brain functions. Although they can be described by a prominent peak in the power spectrum, their waveform is not necessarily sinusoidal and shows rather complex morphology. Both frequency and temporal descriptions of such non-sinusoidal neuronal oscillations can be utilized. However, in non-invasive EEG/MEG recordings the waveform of oscillations often takes a sinusoidal shape which in turn leads to a rather oversimplified view on oscillatory processes. In this study, we show in simulations how spatial synchronization can mask non-sinusoidal features of the underlying rhythmic neuronal processes. Consequently, the degree of non-sinusoidality can serve as a measure of spatial synchronization. To confirm this empirically, we show that a mixture of EEG components is indeed associated with more sinusoidal oscillations compared to the waveform of oscillations in each constituent component. Using simulations, we also show that the spatial mixing of the non-sinusoidal neuronal signals strongly affects the amplitude ratio of the spectral harmonics constituting the waveform. Finally, our simulations show how spatial mixing can affect the strength and even the direction of the amplitude coupling between constituent neuronal harmonics at different frequencies. Validating these simulations, we also demonstrate these effects in real EEG recordings. Our findings have far reaching implications for the neurophysiological interpretation of spectral profiles, cross-frequency interactions, as well as for the unequivocal determination of oscillatory phase.
Author:Natalie Schaworonkow, Vadim Nikulin
Pubmed Id:
Parent Title (English):PLoS Computational Biology
Publisher:Public Library of Science
Place of publication:San Francisco, Calif.
Contributor(s):Francesco Paolo Battaglia
Document Type:Article
Year of Completion:2019
Date of first Publication:2019/05/14
Publishing Institution:Universitätsbibliothek Johann Christian Senckenberg
Release Date:2019/05/27
Tag:Bandpass filters; Butterworth filters; Electroencephalography; Eye movements; Fourier analysis; Neurophysiology; Signal filtering; Sine waves
Issue:(5): e1007055
Page Number:22
First Page:1
Last Page:22
Copyright: © 2019 Schaworonkow, Nikulin. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Institutes: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
Licence (German):License LogoCreative Commons - Namensnennung 4.0