[Eeglablist] Announcing Microstate Analysis Toolbox (MST) for EEGlab

[Andreas]

Dear EEGlab users

Our Microstate Analysis Toolbox (MST) is now available on EEGlab.

With MST we have focused on transparency and customisability in the methodology. We have therefore created an extensive and versatile toolbox, featuring all the common clustering algorithms for microstate analysis (plus some updates). 
 
MST includes the ability to run microstate analysis on both ERP and spontaneous (e.g. resting state) EEG.

In the toolbox, the following clustering algorithms are currently available:
• K-means.
• Modified K-means.
• Atomize and Agglomerate Hierarchical Clustering (AAHC).
• Topographic Atomize and Agglomerate Hierarchical Clustering (TAAHC).
• Variational Microstates.
MST is build with customisability in mind, so it is possible to add other clustering algorithms. 

See our guide for the full description of the toolbox as well as an introduction to the methods in microstate analysis, including a step-by-step guide with a tutorial dataset:
https://www.biorxiv.org/content/early/2018/03/27/289850

Additionally, we have sought to thoroughly document the code, to increase transparency of the methods employed.

We hope you find this toolbox helpful and welcome all comments here or directly in our inbox.


Sincerely

Andreas Pedroni, UZH, Zürich, Switzerland; andreas.pedroni at uzh.ch.
Andreas Trier Poulsen, DTU, Kgs. Lyngby, Denmark; atpo at dtu.dk.

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