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Microstates in resting-state EEG: current status and future directions.

  • Khanna A Berenson-Allen Center for Non-invasive Brain Stimulation, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.
  • Pascual-Leone A Berenson-Allen Center for Non-invasive Brain Stimulation, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.
  • Michel CM EEG Brain Mapping Core, Center for Biomedical Imaging of Lausanne and Geneva, Switzerland; The Functional Brain Mapping Laboratory, Departments of Fundamental and Clinical Neurosciences, University of Geneva and University Hospital Geneva, Switzerland.
  • Farzan F Berenson-Allen Center for Non-invasive Brain Stimulation, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA; Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, University of Toronto, Toronto, Ontario, Canada. Electronic address: faranak.farzan@utoronto.ca.
  • 2014-12-21
Published in:
  • Neuroscience and biobehavioral reviews. - 2015
Aging
Dementia
Electroencephalography
Global field potential
Microstates
Resting state
Schizophrenia
Brain
Electroencephalography
Humans
Rest
English 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.
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  • English
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green
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https://sonar.ch/global/documents/147708
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