Electroencephalographic Resting-State Networks: Source Localization of Microstates
University of Geneva · Centre d'Imagerie BioMedicale · +4 more institutions
Abstract
Using electroencephalography (EEG) to elucidate the spontaneous activation of brain resting-state networks (RSNs) is nontrivial as the signal of interest is of low amplitude and it is difficult to distinguish the underlying neural sources. Using the principles of electric field topographical analysis, it is possible to estimate the meta-stable states of the brain (i.e., the resting-state topographies, so-called microstates). We estimated seven resting-state topographies explaining the EEG data set with k-means clustering (N = 164, 256 electrodes). Using a method specifically designed to localize the sources of broadband EEG scalp topographies by matching sensor and source space temporal patterns, we…
Citation impact
- FWCI
- 8.51
- Percentile
- 100%
- References
- 73
Authors
6- ACAnna CustoCorresponding
University of Geneva, Centre d'Imagerie BioMedicale
- DVDimitri Van De Ville
École Polytechnique Fédérale de Lausanne, University of Geneva, Centre d'Imagerie BioMedicale
- WMWilliam M. Wells
Brigham and Women's Hospital, Harvard University, Massachusetts Institute of Technology
- MIMiralena I. Tomescu
University of Geneva
- DBDenis Brunet
Centre d'Imagerie BioMedicale, University of Geneva
Topics & keywords
- Electroencephalography
- Resting state fMRI
- Pattern recognition (psychology)
- EEG-fMRI
- Neuroscience
- Functional magnetic resonance imaging
- Artificial intelligence
- Computer science