[Eeglablist] Batch Processing of multiple EEG datasets

Scott Makeig smakeig at gmail.com
Sun Apr 11 18:45:43 PDT 2021

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

Scott Makeig

On Sun, Apr 11, 2021 at 2:14 PM Krogmeier, Claudia M via eeglablist <
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

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