Spatiotemporal dynamics of the brain at rest - Exploring EEG microstates as electrophysiological signatures of BOLD resting state networks
By Han Yuan, Vadim Zotev, Raquel Phillips, Wayne C. Drevets, Jerzy Bodurka. NeuroImage, 2012
325 citations recorded by the source corpus.
Subfields: Cognitive Neuroscience
View Paper: https://www.semanticscholar.org/paper/f1143e72b176b271ee9b77df27e641ff2025f095
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In Cognitive Neuroscience
- Mark William Woolrich
- Stephen M. Smith
- Timothy Edward John Behrens
- Matthew J. Brookes
- C. Michel
- Jessica S. Damoiseaux
- Alvaro Pascual-Leone
- Faranak Farzan
Citations in the corpus
- Effects of aging on functional and structural brain connectivity☆ (2017, background): “…state functional connectivity has been debated (Morcom and Fletcher, 2007), but comparisons of electrophysiological recordings and resting state functional MRI data provide support for a neural correlate of these connectivity patterns (Nir et al., 2008; Ossandón et al., 2011; Yuan et al., 2012).”
- EEG microstates as a tool for studying the temporal dynamics of whole‐brain neuronal networks: A review (2017, unknown): “Subsequently, Yuan and colleagues (Yuan et al., 2012) reported a”
- Fast transient networks in spontaneous human brain activity (2014, background): “…there exist distinct functional connectivity states that recur at different points in time is compatible with computational models of neuronal connectivity (Deco et al., 2011) and observations from both fMRI (Allen et al., 2012) and EEG (Britz et al., 2010; Musso et al., 2010; Yuan et al., 2012).”
- Microstates in Resting-State EEG: Current Status and Future Directions (2014, methodology): “The field would benefit from standardization of the many technical aspects of the method that have been developed over the last two decades (Wackermann et al., 1993, Pascual-Marqui et al., 1995, Tibshirani and Walther, 2005, Britz et al., 2010, Yuan et al., 2012).”
- Tracking whole-brain connectivity dynamics in the resting state. (2014, unknown): “Indeed, several recent studies have pursued microstate-based fusion of EEG-fMRI resting-state datasets, with promising results suggesting some correspondence between microstates and a limited number of fMR-based ICNs (Britz et al. 2010; Musso et al. 2010; Yuan et al. 2012).”