Resumen
Spontaneous broadband electroencephalography (EEG) demonstrates short moments of stability in the spatial distribution of the head-surface voltage topography. This phenomenon underlies the premise behind segmenting multichannel EEG into topographically defined brain states, known as EEG microstates. Microstate segmentation methods commonly identify representative topographical configurations based on clustering applied to a subset of voltage maps selected at the time series points of greatest strength in the neuroelectric field. These moments are well-reasoned to best represent periods of momentary stability in the voltage topography, and consequently, points of greatest signal relative to noise. Yet, more direct empirical evidence for these assumptions is warranted, and the consistency of this phenomenon across individuals has not been characterized. In the present investigation, the association between electric field strength and topographic dissimilarity of temporally adjacent samples of EEG were characterized in a large sample of healthy adults engaged in quiet rest. Samples of individuals’ EEG time series high in electric field strength were found to be topographically similar relative to adjacent time series samples. The strong phase-synchronized actvity of neuronal populations therefore coincides with momentary stability in the topographic voltage configuration, providing robust empirical support for the basic premise underlying segmentation of broadband EEG into microstates.
| Idioma original | English |
|---|---|
| Páginas (desde-hasta) | 450-460 |
| Número de páginas | 11 |
| Publicación | Brain Topography |
| Volumen | 33 |
| N.º | 4 |
| DOI | |
| Estado | Published - jul 1 2020 |
Nota bibliográfica
Publisher Copyright:© 2020, Springer Science+Business Media, LLC, part of Springer Nature.
Financiación
I thank the Mind-Body-Emotion group at the Max Planck Institute for Human Cognitive and Brain Sciences who gathered and made available the de-identified data on which this manuscript is based. I utilized the freely available Cartool software toolbox (cartoolcommunity.unige.ch) programmed by Denis Brunet, from the Functional Brain Mapping Laboratory, Geneva, Switzerland, and supported by the Center for Biomedical Imaging of Geneva and Lausanne. The data supporting the findings of this study are openly available in the OSF repository and can be found at: https://osf.io/7bcem/ .
| Financiadores |
|---|
| Center for Biomedical Imaging of Geneva |
| Functional Brain Mapping Laboratory, Geneva |
ASJC Scopus subject areas
- Anatomy
- Radiological and Ultrasound Technology
- Radiology Nuclear Medicine and imaging
- Neurology
- Clinical Neurology
Huella
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