[Eeglablist] Concatenate data across visits prior to ICA?

[Tarik S Bel-Bahar]

Steve, brief note here. Perhaps useful or already considered? best wishes.
Consider finding matching ICs from each session and/or using group-ICA
(e.g., Calhoun's EEGgift)to do the same (perhaps grouped by sessions
somehow).
It's hard to estimate (until published evidence) how much noise is added in
by merging sessions vs. comparing across ICA from separate sessions.
And yes, the relatively (empty) green parts in ICA single trials (mentioned
by malte/,makoto) do occur when there has been even displacement of EEG
within a session,
not to speak of large differences in electrode placement across electrode
placements/sessions. ..I think i've also seen twin or triplet ICs emerge in
such situations.
Some form of modelling (cf Scott) should be able to eventually deal with
these issues. This may be due to most multi-session studies focusing on
sensor-level rather than ICA metrics.









On Mon, Mar 23, 2020 at 1:54 PM Coombes, Stephen A <scoombes at ufl.edu> wrote:

> Hi Malte,
>
> Makes sense. Thanks for the input.
>
> Best
> -Steve
>
> __________
> Stephen A. Coombes, Ph.D.
> Laboratory for Rehabilitation Neuroscience
> University of Florida
> Phone: 352.294.1768
> Website: lrnlab.org<http://www.lrnlab.org/>
>
> From: Malte Anders <malteanders at gmail.com>
> Sent: Monday, March 23, 2020 11:08 AM
> To: Coombes, Stephen A <scoombes at ufl.edu>
> Cc: EEGLAB List <eeglablist at sccn.ucsd.edu>
> Subject: Re: [Eeglablist] Concatenate data across visits prior to ICA?
>
> [External Email]
>
> Hi Steve,
>
> I'm afraid you shouldn't do that. Let me quote Makotos preprocessing
> pipeline:
>
> To apply a single ICA, your subject cannot take off the electrode cap! If
> you did this, then ICA may show ICs with very similar scalp topographies
> with differently block-separated activations (active only in some blocks,
> otherwise green) in ERPimage.
>
> Unless you subjects wear the cap for 6 months straight... The cap will
> never be at the exact same locations as before, thus ICA and DIPFIT will
> produce different results. Analyze the data for each visit independently
> and see if you get matching results.
>
> Best,
> Malte
>
> Coombes, Stephen A <scoombes at ufl.edu<mailto:scoombes at ufl.edu>> schrieb am
> Mo., 23. März 2020, 15:56:
> Dear EEG list members,
>
> We have EEG data from a cohort of subjects who come into the lab for 3
> visits spaced over a 6 month period. It is a repeated measures design with
> visit being the only variable. We have resting data and data during a task.
> For each data set (i.e., resting & task based), should we concatenate the
> data for each subject across visit before running ICA, and if so why?
>
> For the task based analysis we will run ICA then DIPFIT and then MPA. We
> are still exploring different options for the resting state pipeline once
> ICA and artifact removal is complete.
>
> Any advice greatly appreciated. Hope everyone is safe and well out there.
>
> Many thanks,
> Steve
>
> __________
> Stephen A. Coombes, Ph.D.
> Laboratory for Rehabilitation Neuroscience
> University of Florida
> Phone: 352.294.1768
> Website: lrnlab.org<
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