EEG microstates as a tool for studying the temporal dynamics of whole-brain neuronal networks: A review

被引:766
作者
Michel, Christoph M. [1 ,2 ,3 ]
Koenig, Thomas [4 ]
机构
[1] Univ Geneva, Dept Basic Neurosci, Campus Biotech, Geneva, Switzerland
[2] Leman Biomed Imaging Ctr CIBM, Lausanne, Switzerland
[3] Leman Biomed Imaging Ctr CIBM, Geneva, Switzerland
[4] Univ Bern, Univ Hosp Psychiat, Translat Res Ctr, Bern, Switzerland
基金
瑞士国家科学基金会;
关键词
EEG microstates; Resting state networks; Consciousness; Psychiatric disease; State-dependent information processing; Metastability; STATE CORTICAL ACTIVITY; DEFAULT MODE; FUNCTIONAL CONNECTIVITY; MAP SERIES; ELECTROPHYSIOLOGICAL SIGNATURES; NEUROCOGNITIVE NETWORKS; INDEPENDENT COMPONENTS; PHASE SYNCHRONIZATION; MULTIMODAL ANALYSIS; STOCHASTIC-MODEL;
D O I
10.1016/j.neuroimage.2017.11.062
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
The present review discusses a well-established method for characterizing resting-state activity of the human brain using multichannel electroencephalography (EEG). This method involves the examination of electrical microstates in the brain, which are defined as successive short time periods during which the configuration of the scalp potential field remains semi-stable, suggesting quasi-simultaneity of activity among the nodes of large-scale networks. A few prototypic microstates, which occur in a repetitive sequence across time, can be reliably identified across participants. Researchers have proposed that these microstates represent the basic building blocks of the chain of spontaneous conscious mental processes, and that their occurrence and temporal dynamics determine the quality of mentation. Several studies have further demonstrated that disturbances of mental processes associated with neurological and psychiatric conditions manifest as changes in the temporal dynamics of specific microstates. Combined EEG-fMRI studies and EEG source imaging studies have indicated that EEG microstates are closely associated with resting-state networks as identified using fMRI. The scale-free properties of the time series of EEG microstates explain why similar networks can be observed at such different time scales. The present review will provide an overview of these EEG microstates, available methods for analysis, the functional interpretations of findings regarding these microstates, and their behavioral and clinical correlates.
引用
收藏
页码:577 / 593
页数:17
相关论文
共 192 条
[91]   Resting-state EEG in schizophrenia: Auditory verbal hallucinations are related to shortening of specific microstates [J].
Kindler, J. ;
Hubl, D. ;
Strik, W. K. ;
Dierks, T. ;
Koenig, T. .
CLINICAL NEUROPHYSIOLOGY, 2011, 122 (06) :1179-1182
[92]   MICROSTATE SEGMENTATION OF SPONTANEOUS MULTICHANNEL EEG MAP SERIES UNDER DIAZEPAM AND SULPIRIDE [J].
KINOSHITA, T ;
STRIK, WK ;
MICHEL, CM ;
YAGYU, T ;
SAITO, M ;
LEHMANN, D .
PHARMACOPSYCHIATRY, 1995, 28 (02) :51-55
[93]   Alpha-band oscillations, attention, and controlled access to stored information [J].
Klimesch, Wolfgang .
TRENDS IN COGNITIVE SCIENCES, 2012, 16 (12) :606-617
[94]   Brain connectivity at different time-scales measured with EEG [J].
Koenig, T ;
Studer, D ;
Hubl, D ;
Melie, L ;
Strik, WK .
PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES, 2005, 360 (1457) :1015-1023
[95]   Millisecond by millisecond, year by year: Normative EEG microstates and developmental stages [J].
Koenig, T ;
Prichep, L ;
Lehmann, D ;
Sosa, PV ;
Braeker, E ;
Kleinlogel, H ;
Isenhart, R ;
John, ER .
NEUROIMAGE, 2002, 16 (01) :41-48
[96]   A deviant EEG brain microstate in acute, neuroleptic-naive schizophrenics at rest [J].
Koenig, T ;
Lehmann, D ;
Merlo, MCG ;
Kochi, K ;
Hell, D ;
Koukkou, M .
EUROPEAN ARCHIVES OF PSYCHIATRY AND CLINICAL NEUROSCIENCE, 1999, 249 (04) :205-211
[97]   Topographic time-frequency decomposition of the EEG [J].
Koenig, T ;
Marti-Lopez, F ;
Valdes-Sosa, P .
NEUROIMAGE, 2001, 14 (02) :383-390
[98]  
Koenig T, 2009, ELECT NEUROIMAGING, P93, DOI 10.1017/CBO9780511596889.006.
[99]   Inappropriate assumptions about EEG state changes and their impact on the quantification of EEG state dynamics [J].
Koenig, Thomas ;
Brandeis, Daniel .
NEUROIMAGE, 2016, 125 :1104-1106
[100]   A Tutorial on Data-Driven Methods for Statistically Assessing ERP Topographies [J].
Koenig, Thomas ;
Stein, Maria ;
Grieder, Matthias ;
Kottlow, Mara .
BRAIN TOPOGRAPHY, 2014, 27 (01) :72-83