EEG microstate sequences in healthy humans at rest reveal scale-free dynamics

By D. Van de Ville, Juliane Britz, C. Michel. Proceedings of the National Academy of Sciences of the United States of America, 2010

609 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/d88d98ff15a79dc52ea862f23639aaab437f6dce

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Citations in the corpus

Fast transient networks in spontaneous human brain activity (2014, background): “One explanation for this observation is the idea that electrophysiological data are characterized by scale-free dynamics that span from hundreds of milliseconds to tens of seconds (Van de Ville et al., 2010).”
Criticality in the brain: A synthesis of neurobiology, models and cognition. (2017, background): “Analysis of the temporal statistics of resting-state fMRI and EEG also suggests that long-range, scale-free correlations may indeed lie at the very heart of the slow fluctuations that are observed in these data (Van de Ville et al., 2010).”
Electrophysiological Imaging of Brain Activity and Connectivity – Challenges and Opportunities (2011, background): “Also, recent findings suggested that continuous resting-state EEG can be classified into a limited number of micro-states with each spanning for a time window of about 100 ms [47].”
Criticality in Large-Scale Brain fMRI Dynamics Unveiled by a Novel Point Process Analysis (2012, background): “Both descriptions of electrical scalp activity have also been shown to exhibit properties consistent with critical dynamics (Allegrini et al., 2010; Van De Ville et al., 2010).”
Time-resolved resting-state brain networks (2014, background): “We hypothesize that these “transition epochs” mark changeover points between distinct metastates (33, 50).”
Spatiotemporal dynamics of the brain at rest - Exploring EEG microstates as electrophysiological signatures of BOLD resting state networks (2012, background): “Such variation in maintaining long-range dependency suggests that the microstates may be of different scale-free properties (Van de Ville et al., 2010).”
Tracking whole-brain connectivity dynamics in the resting state. (2014, positive): “Although microstates persist for only hundreds of milliseconds, their dynamics exhibit fractal (scale free) organization that spans time scales as long as tens of seconds (Van De Ville et al. 2010).”
Functional connectivity dynamics: Modeling the switching behavior of the resting state (2015, methodology): “…imaging modalities (as in the case of “The Virtual Brain” simulator (Sanz Leon et al., 2013), casting light on the links existing between BOLD FC states and the faster dynamics of EEG/MEGmicrostates (Mantini et al., 2007; Van De Ville et al., 2010) across different temporal and spatial scales.”
Self-organized criticality as a fundamental property of neural systems (2014, background): “Correlations can also be used to construct functional connectivity maps, whose power-law distributed properties might relate to self-organized criticality (e.g., Eguiluz et al., 2005; Bassett et al., 2006; Expert et al., 2010; Lee et al., 2010; Van De Ville et al., 2010).”
Principal components of functional connectivity: A new approach to study dynamic brain connectivity during rest (2013, background): “Along those lines, the scale-free dynamics of EEG microstate sequences have been shown to reach timescales of fMRI resting-state fluctuations (Van de Ville et al., 2010) and the link between EEG microstates and dynamic fMRI FC is an intriguing future research question.”
Spectrally resolved fast transient brain states in electrophysiological data (2016, neutral): “EEG/MEG data have been shown to exhibit scale-free behaviour (Van De Ville et al., 2010), (Gschwind et al., 2015), a feature that is common in the neural system at multiple levels, both anatomical and functional (Buzsaki and Mizuseki, 2014).”
Towards the utilization of EEG as a brain imaging tool (2012, background): “Fourth, the reason why the EEG microstate time-series correlate with fMRI BOLD signals even after the dramatic low-pass filtering is that the temporal structure of the microstate is scale-free, i.e. self-similar on different temporal scale (van de Ville et al., 2010).”
Microstates in Resting-State EEG: Current Status and Future Directions (2014, background): “…the remarkable observation that the microstate time series has scale-free dynamics over six dyadic scales, over the 256 ms to 16 s range, suggesting that resting-state brain activity at the EEG and fMRI timescales reflect the same underlying neurophysiological processes (Van De Ville et al., 2010).”