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.