[Eeglablist] Batch Processing of multiple EEG datasets

Krogmeier, Claudia M ckrogmei at purdue.edu
Sun Apr 11 19:00:16 PDT 2021


Thank you for the explanation, and the reference. I did not remove the eeg device, so I will concatenate the 2 runs/subject.

If I do my preprocessing in a for loop with the total subjects, I believe this will do a separate ICA decomposition for each subject (and therefore a slightly different randomness to each subject's ICA decomposition). Is this acceptable?

Thank you!
Claudia
________________________________
From: Scott Makeig <smakeig at gmail.com>
Sent: Sunday, April 11, 2021 9:45 PM
To: Krogmeier, Claudia M <ckrogmei at purdue.edu>
Cc: EEGLAB List <eeglablist at sccn.ucsd.edu>
Subject: Re: [Eeglablist] Batch Processing of multiple EEG datasets

Claudia -

You may concatenate two runs per subject to run one ICA decomposition -- IFF the electrode cap remained in place during both runs.  Concatenating data across multiple subjects makes little sense, because even equivalent brain sources are expected to have different scalp projections (scalp maps) in different individuals. This is because the scalp projection (scalp map) of a cortical area/patch depends largely on the orientation of the patch in addition to its location (relative to scalp landmarks). See Tsai, Makeig, et al., 2014 for a very nice demonstration of this.

Scott Makeig

On Sun, Apr 11, 2021 at 2:14 PM Krogmeier, Claudia M via eeglablist <eeglablist at sccn.ucsd.edu<mailto:eeglablist at sccn.ucsd.edu>> wrote:
Hello,

I have 20 subjects each with 2 runs, for a total of 40 EEG datasets in which the task and procedure was the same for all runs.

What is the best workflow for preprocessing? Previously I have processed each individual dataset (one run) alone, but I understand ICA may be slightly different each time due to its random learning rate.

Is it recommended to concatenate each subject's 2 runs, and preprocess those as a merged dataset?   My baseline recording is at the start of each run, and I would like to do baseline normalization. Is this still possible with a merged dataset?

Is it recommended to concatenate all datasets from all subjects for preprocessing, or is it recommended to write a script to loop through all subjects - which then would do a slightly different ICA decomposition for each subject?

Thank you for any pointers in processing multiple subjects.
Claudia
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--
Scott Makeig, Research Scientist and Director, Swartz Center for Computational Neuroscience, Institute for Neural Computation, University of California San Diego, La Jolla CA 92093-0559, http://sccn.ucsd.edu/~scott<http://sccn.ucsd.edu/%7Escott>


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