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 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 dataset 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.