The EEGLAB microstate plugin lets you perform and visually access all the analyses steps we have developed for the identification and quantification of EEG microstates in continuous data. (For the analysis of microstates in evoked potentials, the Ragu program is far better suited.)
The plugin is free, but we offer only limited support and expect you to quote the suggested papers. We are open for suggestions to improve the software where we find it useful for a wider community. We take absolutely no responsibility for the results obtained with plugin and the software may not be fool-prove. The documentation of the programs features sometimes lag behind their development, but should be and become available here. The download of the code is here.
In particular, the plugin lets you:
- Identify microstates on the level of the individual EEG (first level clustering)
- Do a constraint clustering of the individual microstate classes to obtain second level average microstate class maps
- Reorder individual and average microstate class maps based on data-driven or published templates
- Display and edit some features of microstate class maps and the microstate dynamics of a given EEG
- Use a graphical interface to infer a useful number of microstate classes
- Create new datasets with the microstate assignment
- Quantify microstate parameters, using individual, average or previously published microstate class maps
- Export individual microstate class maps for testing of topographic differences using Ragu.
There are several typical pathways to conduct a microstate analysis of resting state data.
- The easiest way is that you base your analysis on some existing microstate templates. If this is your choice, you can directly proceed to the quantification of the microstate parameters in all your EEGs.
- A typical way is that you first identify microstate class maps in each subject, then do a second level clustering. Then, you take an educated decision on the number of classes you want to use, and eventually order the labels of the microstate classes of this mean according to some published template. Finally, you quantify the microstates in the EEG based on the obtained and ordered mean microstate class maps.
- Alternatively, you again start with first identifying microstate class maps in each subject, followed by a second level clustering and a meaningful ordering of the obtained mean microstate class maps. Next, you assign the individual maps to the ordered mean microstate class maps. Finally you quantify the microstates in the EEG based on the ordered individual microstate class maps.
As pathways 2. and 3. yield information ordered individual microstate class maps, it is possible that despite the effort to maximize the commonality of the individual microstate class maps across subjects, some groups differ systematically in the topography of some of the microstate classes. You can test this by exporting the ordered individual microstate class maps to Ragu.
To get a basic overview of the procedures, you may also call:
help_HowToDoMicrostateAnalyses in Matlab
There is also a Matlab script in the package called TestMSAnalyses.m that performes an entire microstate analysis with several groups of subjects. Finally, here's a brief video that guides thru a standard analysis and explains the underlying concepts: Download / view the video.