[Eeglablist] Video visualization EEG data

Arnaud Delorme arno at ucsd.edu
Tue Jan 28 19:13:24 PST 2014

Dear Jukka,

the eegmovie function (from the command line only) does nice 2-D and 3-D movies.
An example of call below is shown after loading a STUDY and storing the output of std_spectplot in the variable specdata (the movie function is the last line (this requires EEGLAB 13 for metal material in 3-D plot - otherwise simply remove that parameter).

When I have several conditions, I do multiple movies and then combine them with Screenflow on OSx, a very powerful tool.



mergelocs = eeg_mergelocs(ALLEEG.chanlocs);
% parameters for headplot. IMPORTANT NOTE: the transformation matrix depends on your montage.
% to find the correct transformation matrix, plot the 3-D head on one of the subject and look at the transformation matrix
headplotparams = { 'meshfile', 'mheadnew.mat', 'transform', [0.664455     -3.39403     -14.2521  -0.00241453     0.015519     -1.55584           11      10.1455           12] };
headplotparams = { 'meshfile', 'colin27headmesh.mat', 'transform', [0          -13            0          0.1            0        -1.57         11.7         12.5           12] };
% set up the spline file
headplot('setup', mergelocs, 'STUDY_headplot.spl', headplotparams{:});
% average subject and plot using headplot
scalp_spec = mean(specdata{2},3);
figure; headplot(scalp_spec, 'STUDY_headplot.spl', headplotparams{:}, 'maplimits', 'absmax', 'lighting', 'on');
figure; topoplot(scalp_spec, mergelocs);
figure('color', 'w'); [Movie,Colormap] = eegmovie( repmat(scalp_spec', [1 360]), 10, mergelocs, 'mode', '3d', 'headplotopt', { headplotparams{:}, 'maplimits', [-4 4], 'material', 'metal'}, 'camerapath', [-127 2 30 0]); 


On Jan 26, 2014, at 11:18 AM, Jukka Zitting <jukka.zitting at gmail.com> wrote:

> Hi,
> On Sun, Jan 26, 2014 at 1:45 PM, Jukka Zitting <jukka.zitting at gmail.com> wrote:
>> I'm looking for a way to visualize selected aspects of continuous EEG
>> data, for example by creating a video of the topoplot() output over
>> time for selected frequency bands or ICA components.
> On second thought it occurs to me that a video of a time-independent
> construct like an ICA component wouldn't be too interesting. Anyway,
> to give a bit more background, we're interested in spotting features
> like delta or alpha waves while a subject is falling asleep. A video
> visualization (besides being a nice demo feature :-) could help
> identify interesting periods of activity that might otherwise be hard
> to spot or auto-detect within the continuous raw data.
> BR,
> Jukka Zitting
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