[Mne_analysis] concatenate_epochs and subset of them

Jaakko Leppakangas jaeilepp at gmail.com
Thu Dec 15 08:58:01 EST 2016
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Hi,

the first logging message is actually a bit misleading because it is only
storing the baseline parameters. So the baselining actually only happens
when the data is loaded (probably on concatenation in your case).

If you construct the epochs by passing a dict as the event_id (see for
example
http://mne-tools.github.io/stable/auto_tutorials/plot_object_epochs.html),
you can get a copy of the 'A' category by doing ``epochs['A']``.

-Jaakko

On Thu, Dec 15, 2016 at 2:03 PM, Lorenzo Alfine <lorenzo.alfine at gmail.com>
wrote:

> Dear mne users,
> I´m dealing with a 3 blocks experiment and for each block I have a raw
> object.
> Then I´m epoching every raw object using the same event_id = [A, B, C, D].
>
> Later I concatenate the 3 epochs objects with:
> epochs_merged = mne.concatenate_epochs([epochs1, epochs2, epochs3])
>
> First question, when concatenating, in the console I have the message:
> *Applying baseline correction (mode: mean)* , but in the documentation I
> can´t find any reference of it.
> Since I already used baseline correction when creating epochs1, epochs2,
> epochs3, could this additional correction generate any problem?
>
> Later I´m doing some processing on epochs_merged (AutoReject, ICA). Is it
> possible to access a subset of epochs_merged, for example just the epochs
> with the event A, and average them?
> Otherwise I have to re-run the analysis on a newly created epochs object
> with event_id = A, but I would prefer to avoid this, since from my
> understanding ICA performs better with more data.
>
> Thank you in advance,
>
> LA
>
> MSc student, University of Padova
>
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