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.
KeywordsFunctional connectivity Source localization Synchronization Granger causality
- 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
- 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
- Wiener N. The theory of prediction. In: Beckenbach EF, editor. Modern mathematics for the engineer. New York: McGraw-Hill; 1956.Google Scholar