[Eeglablist] Spread blinks and eye artifacts over IC
Tarik S Bel-Bahar
tarikbelbahar at gmail.com
Tue Nov 14 12:16:26 PST 2017
Okay thanks Mahsa! remember you can run an ICA with 1 Hz highpass and then
apply the ICA weights to continuous pre-ICA data that are filtered
Also, make sure you are appropriately correcting for rank.
It's probably best to stay overall with the components that are truly
neural. regarding whether to keep the mixed ones or not, you may review
existing literature that works with similar data and protocols as yours.
yes, there is a tradeoff regarding keeping or dropping mixed components
that one has to deal with and understand the pros/cons.. Your "other"
components if they don't have clear neural information and/or spectral
peak, are probably candidates for removal.
On Mon, Nov 13, 2017 at 9:42 PM, mahsa shalchy <mahsa.shalchy at gmail.com>
> Dear Tarik,
> Thank you so much for your explanation. I had tried 1Hz HP cut-off and it
> did not improve my ICA results and since I am also interested in early
> components such as P1, I decided to go with 0.1 Hz. Also, I am visually
> rejecting my epochs before feeding them to ICA but unfortunately I forgot
> to mention. Using Luca's IC labeling and SASICA I'm able to keep only
> neural components, however, mixed or "other" components are usually the
> highest ICs ( IC3 to IC9) and by discarding them I am not only losing great
> amount of information but also ending up with low SNR.
> Many thanks,
> On Mon, Nov 13, 2017 at 11:44 AM, Tarik S Bel-Bahar <
> tarikbelbahar at gmail.com> wrote:
>> Hello Mahsa,
>> You may want to use a 1 Hz bottom for your filter to get better ICA.
>> It's probably best to remove any components that are dominated by eye
>> I would recommend just sticking with analysis of just the IC components
>> that are valid/neural, and ignoring/discounting the rest.
>> If you are rejecting IC components and rebuilding the eeg data: Some
>> researchers try to be extra cautious and they try not to remove ICs that
>> are "mixed", so as not to inadvertantly remove neural signal.
>> Note that ICA is not a perfect method, and that there are often ICs that
>> have both artifact and neural signal.
>> See Luca's reaching site to get info and training on selecting/reviewing
>> ICs, including a "practice" option that provides feedback about your
>> classification. At minimum, I recommend that students do about 200
>> classifications, review with an ICA-EEG expert, and then do another 200-300
>> Remember that you also have to do cleaning before ICA, which does not
>> seem to be one of the steps you listed.
>> If you haven't had a chance to yet, please be sure to review the eeglab
>> tutorial steps, practice with with eeglab tutorial data, and check out
>> Makoto's pipeline suggestions.
>> If you haven't yet, you should check out the various ICA classification
>> plugins, such as MARA and SASICA, which should help you make a decision on
>> your ICs.
>> On Thu, Nov 9, 2017 at 3:54 PM, mahsa shalchy <mahsa.shalchy at gmail.com>
>>> Dear Experts,
>>> I am trying to correct EEG data blinks and saccades using ICA, however,
>>> in some cases (i.e. when the subject is double blinking), ICA finds
>>> multiple eye related components.
>>> The problem is that except for the main blink component, other eye
>>> contaminated ICs, have neural information and I can not easily discard them
>>> ( please find an image of ICs here:
>>> I tried using PCA before ICA but it didn't seem to work.
>>> For the preprocessing I did the following steps before applying ICA:
>>> Resampling, Filtering (0.1-40), re-referencing to average
>>> I highly appreciate your help on this problem.
>>> Many thanks,
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