[Eeglablist] Re-epoching data into bigger pieces

[Arnaud Delorme]

Dear Bart,

you would need to create a new dataset (from the continuous data) with 3000 ms epochs, then apply the ICA weights you have obtained on the shorter epochs (select menu "Edit > Dataset info" which allows you to use the ICA decomposition from another dataset).

Best,

Arno

On Dec 4, 2013, at 2:06 AM, Bart Michiels <MICHELSB at tcd.ie> wrote:

> Hi,
> 
> My idea was to break down continuous data into pieces of 750 ms after rejecting some time frames in its continuous form.
> After 750 ms epoching I'd want to do some ICA and reject some component epochs.
> Finally I'd re-epoch the data to bits of 3000ms to do some time-frequency analysis.
> 
> The problem is that eeglab can't create any epochs.
> 
> ########################################################################################
> ########################################################################################
> % First epoching, I took 1 seconds here
> test = eeg_regepochs(EEG_eo, 'recurrence', 1, 'limits', [0 1], 'rmbase', NaN, 'eventtype', 'EO');
> The input dataset will be split into 389 epochs of 1 s
> Epochs will overlap by  0%.
> Inserting 389 type 'EO' events: .......................................40
> .......................................80..............................
> .........120......................................160....................
> ...................200.......................................240..........
> .............................280.......................................320
> .......................................360.............................
> Sorting the event table.
> Splitting the data into 389 1.00-s epochs
> pop_epoch():389 epochs selected
> Epoching...
> pop_epoch():389 epochs generated
> eeg_checkset: found empty values for field 'urevent'
>              filling with values of other events in the same epochs
> eeg_checkset: found empty values for field 'duration' (filling with 0)
> Event resorted by increasing latencies.
> pop_epoch(): checking epochs for data discontinuity
> Removing 5 trial(s)...
> Pop_select: removing 15 unreferenced events
> 
> % Second epoch, tried to take 2 seconds
>>> pop_epoch(test,{'EO'},[0 2])
> pop_epoch():767 epochs selected
> Epoching...
> Warning: event 1 out of data boundary
> Warning: event 2 out of data boundary
> ...
> ########################################################################################
> ########################################################################################
> 
> I know if eeglab can't find 4 consecutive 750 ms (4*750 = 3000) it would be unable to generate any epochs, but this isn't happening in my case.
> 
> Also: when epoching the continuous data, how can I make sure that 2 consecutive epochs are close neighbors without any deleted data points in between them?
> 
> Regards, Bart
> 
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