[Eeglablist] Uniform epoching my EEG data

[Arnaldo Batista]

Dear all,

We are using the physionet EEG epilepsy database which features continues
EEG data (23 channels).

We would like to analyze this data on fixed successive 4096 (samples) data
chunks, so we would need to divide the continuous signal on epochs with 4096
samples each. We would be left with around 200 epochs (per channel) to
process.

How can we, under EEGLAB, to epoch our signal in this way?

Thanks in advance


Arnaldo Batista


-----Original Message-----
From: eeglablist-bounces at sccn.ucsd.edu
[mailto:eeglablist-bounces at sccn.ucsd.edu] On Behalf Of James Desjardins
Sent: sábado, 9 de Abril de 2011 04:09
To: eeglablist at sccn.ucsd.edu
Subject: Re: [Eeglablist] <no subject>

Hi Guilia,

While trying to compare the results of multiple EEG systems I wrote a plugin
to interpolate scalp channels to the coordinates found in an *.sfp, *.elp,
etc.. coordinate file (e.g., take files recorded with a
256 channel EGI net, a 128 channel EGI net and a custom 128 channel BioSemi
cap and spatially resample all the files to the coordinates found in a
standard 81 channel extended 10-20 montage coordinate file). This plugin is
basically just a coordination of the readlocs, coregister and eeg_interp
functions in EEGlab, but was designed to be easily implemented into batching
scripts.

While this works well for the analysis of scalp data in study sets (forces
every file to have an identical scalp montage) I do not know what the
effects would be on subsequent ICA decompositions.

Let me know if this sounds like something that would be useful to you, if so
I will add some documentation and make it available.

James Desjardins
Technician, MA Student
Department of Psychology, Behavioural Neuroscience Cognitive and Affective
Neuroscience Lab Brock University
500 Glenridge Ave.
St. Catharines, ON, Canada
L2S 3A1
905-688-5550 x4676


Quoting Scott Makeig <smakeig at gmail.com>:

> Guilia -
>
> To combine datasets with 128 and 64 channels, construct an EEGLAB 
> STUDY containing datasets with 64 channels. Does the 128-channel 
> montage include the 64-channel montage as a subset? If so, the 
> reduction from 128- to 64--channel datasets should be simple.
>
> If not, then you may want to spatially resample. My suggested approach 
> for that would be to perform ICA (optimally, see the wiki tutorial) on 
> each of the 128-channel data sets, then resample the 3-D projection of 
> each independent component to the locations of the the 64 channels 
> used in your other datasets. There is not an EEGLAB function to do 
> just that, but it should not be difficult (for someone) to build. Then 
> reconstitute each 128-channel data set by summing the back-projections 
> of all the 128 components (perhaps omitting selected 'noise' 
> components) to the 64 channels. Note that you will then no longer be 
> able to separate all (<=) 128 components when you decompose the new 
> data using ICA (since the data now have only 64 degrees of freedom).
>
> A possibly simpler those less refinable method would be to sample the 
> 64 channels in the interpolated scalp maps of every raw data point - 
> requiring the same scalp map resampling function.
>
> Resampling the data from 64 to 128 channels is probably less optimal 
> (and less efficient). For one, it would still allow recovery of only 
> 64 independent components because the rank of the data matrix (>>help 
> rank) would remain 64, even when 128 channels have been resampled from 
> the scalp maps.
>
> Scott Makeig
>
> On Tue, Apr 5, 2011 at 8:23 AM, Giulia Righi <grighi at gmail.com> wrote:
>
>>  HI all
>>
>> I was wondering whether there is a way to combine datasets with 
>> different numbers of channels (64 and 128 channel nets) to include 
>> all participants within a study design to run ERSPs and ITCs?
>>
>> thank you
>>
>> giulia
>>
>>
>> _______________________________________________
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>
>
>
> --
> Scott Makeig, Research Scientist and Director, Swartz Center for 
> Computational Neuroscience, Institute for Neural Computation & Adj. 
> Prof. of Neurosciences, University of California San Diego, La Jolla 
> CA 92093-0559, http://sccn.ucsd.edu/~scott
>




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