[Eeglablist] [Update] Independent component classification help from eeglablist members

[Luca Pion-Tonachini]

Dear EEGLAB mailing list subscribers,

A week ago I introduced a website for labeling EEG independent components and asked for your help in doing so. Unfortunately the website was broken at the time of my last email due to a last minute change. I've since fixed that problem and invite you all to try it again. You can find more information at reaching.ucsd.edu:8000/tutorial or by reading the original email copied below.

Thank you,
Luca Pion-Tonachini 

> On Feb 5, 2016, at 9:15 AM, Luca Pion-Tonachini <lpionton at ucsd.edu> wrote:
> 
> Dear EEGLAB mailing list subscribers,
> 
> I would like to ask for your help on a project that will likely be of use to you in your research or any other endeavor involving ICA decomposition of EEG data. I am an Electrical Engineering Ph.D. student at UCSD and I work at the Swartz Center for Computational Neuroscience, where EEGLAB is developed.
> 
> Here at the SCCN, we have gathered a lot of ICA decomposed EEG data. My plan is to use it to create a multi-class EEG independent component (IC) classifier, one you can run and trust the results as much as if a domain expert had personally labeled them for you. The secret to making such a classifier accurate is in the data used to train it. Including results from many different experiments, electrode montages, subjects, and EEG devices — as well as tentative classifications by many judges — should allow a level of generalization that makes the resulting classifier usable on any dataset. A lot of people I’ve spoken with are excited by this prospect, as I hope you are too.
> 
> If you are interested in participating in this project, please browse this website ( http://reaching.ucsd.edu:8000 ) and suggest classifications for as many ICs as you have time for. Each IC is represented by a figure showing several measures (scalp map, equivalent dipole location, mean spectrum, erpimage, etc.). There is a tutorial on the site that will tell you more about the project and how to use it — and also a guide to discriminating several types of EEG IC processes. 
> 
> If you have comments, questions, or suggestions, please give me feedback through the website or at this email address. We will make use of all data entries, regardless of how many get labeled — and each IC you label will make the classifier more useful.
> 
> Thank you,
> Luca Pion-Tonachini
> _______________________________________________
> Eeglablist page: http://sccn.ucsd.edu/eeglab/eeglabmail.html
> To unsubscribe, send an empty email to eeglablist-unsubscribe at sccn.ucsd.edu
> For digest mode, send an email with the subject "set digest mime" to eeglablist-request at sccn.ucsd.edu
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://sccn.ucsd.edu/pipermail/eeglablist/attachments/20160214/800f7413/attachment.html>