Microstate Analysis

  • Huibin Jia


The microstate analysis, which is based on the clustering of electric field maps, has been proved to be an efficient technique that could fully use the spatial information of topographies of EEG/ERP signals. Typically, researchers found that only four kinds of distinct topographies (i.e., microstate classes) could explain most variances of the spontaneous EEG data. Moreover, each of the four commonly observed microstate classes was closely associated with the activity of distinct resting-state brain networks revealed by BOLD signals of resting-state fMRI. For ERP signals, the microstate segmentation can be used to identify the underlying ERP components and their latencies from the multichannel ERP waveforms. In this chapter, we illustrated the basic concepts of microstate analysis, the commonly used clustering algorithms, the metrics derived from microstate analysis, and how to perform microstate analysis using open-access tools.


Topographic maps Spontaneous EEG ERP Spatial clustering 

Supplementary material

462234_1_En_8_MOESM1_ESM.m (5 kb)
restEEG_microstate_analysis (M 5 kb)


  1. Andreou C, Faber PL, Leicht G, Schoettle D, Polomac N, Hanganu-Opatz IL, Lehmann D, Mulert C. Resting-state connectivity in the prodromal phase of schizophrenia: insights from EEG microstates. Schizophr Res. 2014;152(2–3):513–20.CrossRefGoogle Scholar
  2. Britz J, Van De Ville D, Michel CM. BOLD correlates of EEG topography reveal rapid resting-state network dynamics. NeuroImage. 2010;52:1162–70.CrossRefGoogle Scholar
  3. Britz J, Díaz HL, Ro T, Michel CM. EEG-microstate dependent emergence of perceptual awareness. Front Behav Neurosci. 2014;8(20):163.PubMedPubMedCentralGoogle Scholar
  4. Brunet D, Murray MM, Michel CM. Spatiotemporal analysis of multichannel EEG: CARTOOL. Comput Intell Neurosci. 2010;2011:813870.Google Scholar
  5. Gao F, Jia H, Wu X, Yu D, Feng Y. Altered resting-state EEG microstate parameters and enhanced spatial complexity in male adolescent patients with mild spastic Diplegia. Brain Topogr. 2017;30(2):233–44.CrossRefGoogle Scholar
  6. Gärtner M, Brodbeck V, Laufs H, Schneider G. A stochastic model for EEG microstate sequence analysis. NeuroImage. 2015;104:199–208.CrossRefGoogle Scholar
  7. Hatz F, Hardmeier M, Benz N, Ehrensperger M, Gschwandtner U, Rüegg S, Schindler C, Monsch AU, Fuhr P. Microstate connectivity alterations in patients with early Alzheimer’s disease. Alzheimers Res Ther. 2015;7(1):1–11.CrossRefGoogle Scholar
  8. Hu L, Valentini E, Zhang ZG, Liang M, Iannetti GD. The primary somatosensory cortex contributes to the latest part of the cortical response elicited by nociceptive somatosensory stimuli in humans. NeuroImage. 2013;84(1):383–93.PubMedGoogle Scholar
  9. Jeremy H, Malone S, Bernat E. Theta and delta band activity explain N2 and P3 ERP component activity in a go/no-go task. Clin Neurophysiol. 2014;125(1):124–32.CrossRefGoogle Scholar
  10. Jia H, Peng W, Hu L. A novel approach to identify time-frequency oscillatory features in electrocortical signals. J Neurosci Methods. 2015;253:18–27.CrossRefGoogle Scholar
  11. Jia H, Li H, Yu D. The relationship between ERP components and EEG spatial complexity in a visual Go/Nogo task. J Neurophysiol. 2017;117(1):275–83.CrossRefGoogle Scholar
  12. Khanna A, Pascual-Leone A, Michel CM, Farzan F. Microstates in resting-state EEG: current status and future directions. Neurosci Biobehav Rev. 2014;49:105–13.CrossRefGoogle Scholar
  13. Kikuchi M, Koenig T, Munesue T, Hanaoka A, Strik W, Dierks T, Koshino Y, Minabe Y. EEG microstate analysis in drug-naive patients with panic disorder. PLoS One. 2011;6(7):65.CrossRefGoogle Scholar
  14. Koenig T, Prichep L, Lehmann D, Sosa PV, Braeker E, Kleinlogel H, Isenhart R, John ER. Millisecond by millisecond, year by year: normative EEG microstates and developmental stages. NeuroImage. 2002;16(1):41–8.CrossRefGoogle Scholar
  15. Lehmann D, Ozaki H, Pal I. EEG alpha map series: brain micro-states by space-oriented adaptive segmentation. Electroencephalogr Clin Neurophysiol. 1987;67(3):271–88.CrossRefGoogle Scholar
  16. Lehmann D, Strik WK, Henggeler B, Koenig T, Koukkou M. Brain electric microstates and momentary conscious mind states as building blocks of spontaneous thinking: I. Visual imagery and abstract thoughts. Int J Psychophysiol. 1998;29(1):1–11.CrossRefGoogle Scholar
  17. Lehmann D, Faber PL, Galderisi S, Herrmann WM, Kinoshita T, Koukkou M, Mucci A, Pascualmarqui RD, Saito N, Wackermann J. EEG microstate duration and syntax in acute, medication-naive, first-episode schizophrenia: a multi-center study. Psychiatry Res. 2005;138(2):141–56.CrossRefGoogle Scholar
  18. Li H, Jia H, Yu D. The influence of vertical disparity gradient and cue conflict on EEG omega complexity in Panum’s limiting case. J Neurophysiol. 2018;119(3):1201–8.CrossRefGoogle Scholar
  19. Maxwell CR, Villalobos ME, Schultz RT, Herpertz-Dahlmann B, Konrad K, Kohls G. Atypical laterality of resting gamma oscillations in autism spectrum disorders. J Autism Dev Disord. 2015;45(2):292–7.CrossRefGoogle Scholar
  20. Michel CM, Koenig T. EEG microstates as a tool for studying the temporal dynamics of whole-brain neuronal networks: a review. NeuroImage. 2017;180:577–93.CrossRefGoogle Scholar
  21. Murray MM, Brunet D, Michel CM. Topographic ERP analyses: a step-by-step tutorial review. Brain Topogr. 2008;20(4):249–64.CrossRefGoogle Scholar
  22. Pascual-Marqui RD. Standardized low-resolution brain electromagnetic tomography (sLORETA): technical details. Methods Find Exp Clin Pharmacol. 2002;24(Suppl D):5–12.PubMedGoogle Scholar
  23. Pascual-Marqui RD, Michel CM, Lehmann D. Segmentation of brain electrical activity into microstates: model estimation and validation. IEEE Trans Biomed Eng. 1995;42(7):658–65.CrossRefGoogle Scholar
  24. Rieger K, Diaz Hernandez L, Baenninger A, Koenig T. 15 years of microstate research in schizophrenia – where are we? A meta-analysis. Front Psych. 2016;7:22.Google Scholar
  25. Santarnecchi E, Khanna AR, Musaeus CS, Benwell CSY, Davila P, Farzan F, Matham S, Pascual-Leone A, Shafi MM. EEG microstate correlates of fluid intelligence and response to cognitive training. Brain Topogr. 2017;30:502–20.CrossRefGoogle Scholar
  26. Schlegel F, Lehmann D, Faber PL, Milz P, Gianotti LRR. EEG microstates during resting represent personality differences. Brain Topogr. 2012;25(1):20–6.CrossRefGoogle Scholar
  27. Seitzman BA, Abell M, Bartley SC, Erickson MA, Bolbecker AR, Hetrick WP. Cognitive manipulation of brain electric microstates. NeuroImage. 2017;146:533–43.CrossRefGoogle Scholar
  28. Van de Ville D, Britz J, Michel CM. EEG microstate sequences in healthy humans at rest reveal scale-free dynamics. Proc Natl Acad Sci U S A. 2010;107(42):18179–84.CrossRefGoogle Scholar
  29. Wu X, Jia H, Wang E, Du C, Wu X, Dang C. Vertical position of Chinese power words influences power judgments: evidence from spatial compatibility task and event-related potentials. Int J Psychophysiol. 2016;102:55–61.CrossRefGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Huibin Jia
    • 1
  1. 1.Key Laboratory of Child Development and Learning Science of Ministry of Education, School of Biological Sciences & Medical EngineeringSoutheast UniversityNanjingChina

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