Microstates in Resting-State EEG: Current Status and Future Directions

By Arjun R. Khanna, Alvaro Pascual-Leone, C. Michel, Faranak Farzan. Neuroscience and Biobehavioral Reviews, 2014

857 citations recorded by the source corpus.

Electroencephalography (EEG) is a powerful method of studying the electrophysiology of the brain with high temporal resolution. Several analytical approaches to extract information from the EEG signal have been proposed. One method, termed microstate analysis, considers the multichannel EEG recording as a series of quasi-stable “microstates” that are each characterized by a unique topography of electric potentials over the entire channel array. Because this technique simultaneously considers signals recorded from all areas of the cortex, it is capable of assessing the function of large-scale brain networks whose disruption is associated with several neuropsychiatric disorders. In this review, we first introduce the method of EEG microstate analysis. We then review studies that have discovered significant changes in the resting-state microstate series in a variety of neuropsychiatric disorders and behavioral states. We discuss the potential utility of this method in detecting neurophysiological impairments in disease and monitoring neurophysiological changes in response to an intervention. Finally, we discuss how the resting-state microstate series may reflect rapid switching among neural networks while the brain is at rest, which could represent activity of resting-state networks described by other neuroimaging modalities. We conclude by commenting on the current and future status of microstate analysis, and suggest that EEG microstates represent a promising neurophysiological tool for understanding and assessing brain network dynamics on a millisecond timescale in health and disease.

Subfields: Cognitive Neuroscience

View Paper: https://www.semanticscholar.org/paper/0f4bc9716a62595f39462b33aa653b471f62a9ef

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Citations in the corpus

Capturing the spatiotemporal dynamics of self-generated, task-initiated thoughts with EEG and fMRI (2019, neutral): “EEG microstates reflect brief epochs of coherent neuronal activity that persist for around 100ms (Khanna et al., 2015; Michel and Koenig, 2018).”
Electroencephalographic Resting-State Networks: Source Localization of Microstates (2017, positive): “The result shows that maps A, B, C, and D, the four of the seven maps most conventionally described in the literature (Khanna et al., 2015), together explain *60% of the variance when using seven clusters.”
EEG microstates as a tool for studying the temporal dynamics of whole‐brain neuronal networks: A review (2017, result): “, 2010), who utilized a more conventional approach, when interpreting the significance of specific microstate changes in different states and pathologies (see review by (Khanna et al., 2015).”
Combining non-invasive transcranial brain stimulation with neuroimaging and electrophysiology: Current approaches and future perspectives (2016, neutral): “Theymay be defined based on topographical EEGmicrostates (Khanna et al., 2015), certain rule-based classification schemes (e.”
Age-related neural dynamics of empathy in preschoolers: an EEG study with naturalistic viewing (2026, unknown): “Microstate analysis identifies quasi-stable patterns of scalp topography that persist for approximately 60–120ms, which have been linked to specific cognitive processes (Britz et al. 2010, Khanna et al. 2015, Michel and Koenig 2018).”
Age-Related Characteristics of Resting-State Electroencephalographic Signals and the Corresponding Analytic Approaches: A Review (2024, methodology): “…age because it allows the easy acquisition of neural signals in a more comfortable and natural environment than other techniques, such as functional magnetic resonance imaging (fMRI), diffusion tensor imaging (DTI), magnetoencephalography (MEG), and positron emission tomography (PET) [6,16–19].”