Abstract
EEGLAB (sccn.ucsc.edu/eeglab) is an easily extensible, highly evolved, and widely used open source environment for signal processing and visualization of electroencephalographic data running on MATLAB (The Mathworks, Inc.). Methods central to EEGLAB include time- and time-frequency analysis and visualization of individual datasets and complete studies, independent component analysis (ICA), and rich tools for connectivity analysis, brain computer interface (BCI) development, and tools for fusion and joint analysis of simultaneously recorded motion-capture and brain data. We introduce a new MEEG plug-in that enables MEG and simultaneously recorded MEG/EEG (MEEG) data to be readily analyzed using EEGLAB. Its use is demonstrated by the analysis of an MEEG dataset. Here we show a first ICA decomposition of an MEEG data set and use MEEG plotting tools to localize and evaluate maximally independent joint MEG/EEG component processes in the data. The analysis naturally recovers a range of artifact sources, as well as brain sources common to MEG and EEG, as well as sources primarily visible only to EEG.
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Acknowledgments
The authors thank Michael Wibral and colleagues for the use of the MEG/EEG data set, and Jason Palmer, Zeynep Akalin Acar, and Arnaud Delorme for useful discussions. This work was funded by a gift from The Swartz Center (Old Field NY) and from grant R01 NS047293-09 from the National Institutes of Health USA.
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Iversen, J.R., Makeig, S. (2014). MEG/EEG Data Analysis Using EEGLAB. In: Supek, S., Aine, C. (eds) Magnetoencephalography. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33045-2_8
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DOI: https://doi.org/10.1007/978-3-642-33045-2_8
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