Connectivity Analysis

  • Huibin Jia


The EEG signals could be used to assess the communication between brain regions. Various techniques have been developed in order to quantify the EEG connectivity of scalp-level EEG signals or source-level activities. Briefly speaking, four kinds of EEG connectivity measures are evaluated in literatures, including coherence-based measures, phase synchronization-based measures, generalized synchronization-based measures, and granger causality-based measures. All measures have their own advantages and disadvantages. Here, we illustrated the common sources problem in EEG analysis, the measures in EEG connectivity analysis, how to conduct EEG connectivity analysis using resting-state EEG signals and event-related EEG signals, and source-level connectivity. Moreover, we provided two examples of EEG connectivity, along with the EEG datasets and MATLAB codes, which are focused on the EEG connectivity of resting-state signals and event-related signals, respectively.


Functional connectivity Source localization Synchronization Granger causality 

Supplementary material (9 kb)
Code (ZIP 9 kb)


  1. Abrams DA, Lynch CJ, Cheng KM, Phillips J, Supekar K, Ryali S, Uddin LQ, Menon V. Underconnectivity between voice-selective cortex and reward circuitry in children with autism. Proc Natl Acad Sci U S A. 2013;110(29):12060–5.CrossRefGoogle Scholar
  2. Astolfi L, Cincotti F, Mattia D, Salinari S, Babiloni C, Basilisco A, Rossini PM, Ding L, Ni Y, He B, Marciani MG, Babiloni F. Estimation of the effective and functional human cortical connectivity with structural equation modeling and directed transfer function applied to high-resolution EEG. Magn Reson Imaging. 2004;22(10):1457–70.CrossRefGoogle Scholar
  3. Baccalá LA, Sameshima K. Partial directed coherence: a new concept in neural structure determination. Biol Cybern. 2001;84(6):463–74.CrossRefGoogle Scholar
  4. Buckner RL, Andrewshanna JR, Schacter DL. The brain’s default network: anatomy, function, and relevance to disease. Ann N Y Acad Sci. 2008;1124(1):1–38.CrossRefGoogle Scholar
  5. Cohen MX. Effects of time lag and frequency matching on phase-based connectivity. J Neurosci Methods. 2015;250:137–46.CrossRefGoogle Scholar
  6. Dhamala M, Rangarajan G, Ding M. Analyzing information flow in brain networks with nonparametric Granger causality. NeuroImage. 2008;41(2):354–62.CrossRefGoogle Scholar
  7. Ding M, Bressler SL, Yang W, Liang H. Short-window spectral analysis of cortical event-related potentials by adaptive multivariate autoregressive modeling: data preprocessing, model validation, and variability assessment. Biol Cybern. 2000;83(1):35–45.CrossRefGoogle Scholar
  8. Duann JR, Ide JX. Functional connectivity delineates distinct roles of the inferior frontal cortex and presupplementary motor area in stop signal inhibition. J Neurosci. 2009;29(32):10171–9.CrossRefGoogle Scholar
  9. Ercan ES, Suren S, Bacanlı A, Yazıcı KU, Callı C, Ardic UA, Aygunes D, Kosova B, Ozyurt O, Aydın C, ROhde LA. Altered structural connectivity is related to attention deficit/hyperactivity subtypes: a DTI study. Psychiatry Res Neuroimaging. 2016;256:57–64.CrossRefGoogle Scholar
  10. Friston KJ, Harrison LM, Penny WD. Dynamic causal modeling. NeuroImage. 2003;19(4):1273–302.CrossRefGoogle Scholar
  11. Gao Q, Duan X, Chen H. Evaluation of effective connectivity of motor areas during motor imagery and execution using conditional Granger causality. NeuroImage. 2011;54(2):1280–8.CrossRefGoogle Scholar
  12. Granger CWJ. Investigating causal relations by econometric models and cross-spectral methods. Econometrica. 1969;37(3):424–38.CrossRefGoogle Scholar
  13. Heise V, Filippini N, Trachtenberg AJ, Suri S, Ebmeier KP, Mackay CE. Apolipoprotein E genotype, gender and age modulate connectivity of the hippocampus in healthy adults. NeuroImage. 2014;98(7):23–30.CrossRefGoogle Scholar
  14. Huster RJ, Plis SM, Lavallee CF, Calhoun VD, Herrmann CS. Functional and effective connectivity of stopping. NeuroImage. 2014;94(6):120–8.CrossRefGoogle Scholar
  15. Kamiński MJ, Blinowska KJ. A new method of the description of the information ow in the brain structures. Biol Cybern. 1991;65(3):203–10.CrossRefGoogle Scholar
  16. Lachaux JP, Rodriguez E, Martinerie J, Varela FJ. Measuring phase synchrony in brain signals. Hum Brain Mapp. 1999;8(4):194–208.CrossRefGoogle Scholar
  17. Lutkepohl H. New introduction to multiple time series analysis. Berlin: Springer; 2005.CrossRefGoogle Scholar
  18. Niso G, Bruña R, Pereda E, Gutiérrez R, Bajo R, Maestú F, del-Pozo F. HERMES: towards an integrated toolbox to characterize functional and effective brain connectivity. Neuroinformatics. 2013;11(4):405–34.CrossRefGoogle Scholar
  19. Nolte G, Bai O, Wheaton L, Mari Z, Vorbach S, Hallett M. Identifying true brain interaction from EEG data using the imaginary part of coherency. Clin Neurophysiol. 2004;115(10):2292–307.CrossRefGoogle Scholar
  20. Nolte G, Ziehe A, Nikulin VV, Schlögl A, Krämer N, Brismar T, Müller KR. Robustly estimating the flow direction of information in complex physical systems. Phys Rev Lett. 2007;100(23):234101.CrossRefGoogle Scholar
  21. Nunez PL, Srinivasan R, Westdorp AF, Wijesinghe RS, Tucker DM, Silberstein RB, Cadusch PJ. EEG coherency : I: statistics, reference electrode, volume conduction, Laplacians, cortical imaging, and interpretation at multiple scales. Electroencephalogr Clin Neurophysiol. 1997;103(5):499–515.CrossRefGoogle Scholar
  22. O’Reilly C, Lewis JD, Elsabbagh M. Is functional brain connectivity atypical in autism? A systematic review of EEG and MEG studies. PLoS One. 2017;12(5):e0175870.CrossRefGoogle Scholar
  23. Rasero J, Amoroso N, La Rocca M, Tangaro S, Bellotti R, Stramaglia S. Multivariate regression analysis of structural MRI connectivity matrices in Alzheimer’s disease. PLoS One. 2017;12(11):e0187281.CrossRefGoogle Scholar
  24. Sommerlade L, Henschel K, Wohlmuth J, Jachan M, Amtage F, Hellwig B, Lücking CH, Timmer J, Schelter B. Time-variant estimation of directed influences during Parkinsonian tremor. J Physiol-Paris. 2009;103(6):348–52.CrossRefGoogle Scholar
  25. Srinivasan R, Winter WR, Ding J, Nunez PL. EEG and MEG coherence: measures of functional connectivity at distinct spatial scales of neocortical dynamics. J Neurosci Methods. 2007;166(1):41–52.CrossRefGoogle Scholar
  26. Stam CJ, Nolte G, Daffertshofer A. Phase lag index: assessment of functional connectivity from multi channel EEG and MEG with diminished bias from common sources. Hum Brain Mapp. 2007;28(11):1178–93.CrossRefGoogle Scholar
  27. Stam CJ, van Dijk BW. Synchronization likelihood: an unbiased measure of generalized synchronization in multivariate data sets. Physica D. 2002;163(3):236–51.CrossRefGoogle Scholar
  28. Sun Y, Lim J, Kwok K, Bezerianos A. Functional cortical connectivity analysis of mental fatigue unmasks hemispheric asymmetry and changes in small-world networks. Brain Cogn. 2014;85(1):220–30.CrossRefGoogle Scholar
  29. van den Broek SP, Reinders F, Donderwinkel M, Peters MJ. Volume conduction effects in EEG and MEG. Electroencephalogr Clin Neurophysiol. 1998;106(6):522–34.CrossRefGoogle Scholar
  30. Vicente R, Wibral M, Lindner M, Pipa G. Transfer entropy--a model-free measure of effective connectivity for the neurosciences. J Comput Neurosci. 2011;30(1):45–67.CrossRefGoogle Scholar
  31. Vinck M, Oostenveld R, van Wingerden M, Battaglia F, Pennartz CMA. An improved index of phase-synchronization for electrophysiological data in the presence of volume-conduction, noise and sample-size bias. NeuroImage. 2011;55(4):1548–65.CrossRefGoogle Scholar
  32. Wiener N. The theory of prediction. In: Beckenbach EF, editor. Modern mathematics for the engineer. New York: McGraw-Hill; 1956.Google Scholar
  33. Yao D, Wang L, Arendt-Nielsen L, Chen ACN. The effect of reference choices on the spatio-temporal analysis of brain evoked potentials: the use of infinite reference. Comput Biol Med. 2007;37(11):1529–38.CrossRefGoogle Scholar
  34. Yao D, Wang L, Oostenveld R, Nielsen KD, Arendtnielsen L, Chen AC. A comparative study of different references for EEG spectral mapping: the issue of the neutral reference and the use of the infinity reference. Physiol Meas. 2005;26(3):173–84.CrossRefGoogle Scholar
  35. Yu D. Additional brain functional network in adults with attention-deficit/hyperactivity disorder: a phase synchrony analysis. PLoS One. 2013;8(8):e54516.CrossRefGoogle Scholar
  36. Zalesky A, Fornito A, Bullmore ET. Network-based statistic: identifying differences in brain networks. NeuroImage. 2010;53(4):1197–207.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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