[Eeglablist] re referencing to average after ICA

[Raquel London]

Dear Tarik,

Thanks so much for your reply, this is very helpful to me.
Once I have made some decisions and ran further steps I will definitely
share what I've come up with.

cheers,
Raquel

On Sat, Sep 3, 2016 at 10:24 PM, Tarik S Bel-Bahar <tarikbelbahar at gmail.com>
wrote:

> Thanks for your question Raquel, and great idea to get a better idea of
> the mechanics and assumptions. Hands-on playing with different options and
> rerunning ICAs can be quite useful. What I meant is that usually
> researchers, as far as I understand, usually apply the ICA decomposition to
> files (from processing steps before ICA) that are very similar to the files
> that went "into" ICA. But there are various ways the files could be the
> "same"....
>
> In other words, the usual thing is to apply the ICA weights to a file that
> has at least
> ***A. the *same* channels as the file(s) that went into ICA
> ***B. the *same* subject and same recording session as the file(s) that
> went into ICA
> I think this is due the basic expectations of ICA and the data structures
> in eeglab.  Also, each person/session of course has their own decomposition.
>
>
> FURTHER
> ***C. Usually,the file which is getting the ICA weights will be the *same
> *as the file(s) that went into the ICA (e.g, in terms of filtering or
> bandpassing or re-referencing). Relatedly, I don't believe it's appropriate
> to apply ICA weights from 1hz-highpass files to unfiltered files, but I
> might be wrong.
>
>
> HOWEVER
> ***D. The file which is getting the ICA weights does not need to have the *same
> *exact time points as the file(s) that went into the ICA, and it can be
> epoched or continuous. As long as it has the correct features matching the
> file that went into ICA. So it's in terms of time points to apply the ICA
> weights to that you have the most freedom, relative to other feature of the
> data.
> Thus.... one can re-apply to the continuous or near-continous epoched
> data, and then do artifact rejection with ICA info, re-do epoching after
> doing ICA cleaning, and other similar strategies. Some of the strategies
> are laidout in the eeglab tutorials and articles.
>
>
> ps. when things are setup wrong with ICA, the solutions will look weird,
> the eeg data will look weird, and/or eeglab will break. If you get a chance
> to, please consider sharing some examples of your next tests, or some
> summary of your understanding that could benefit new users later on.
>
>
>
>
>
>
>
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