[FieldTrip] automatic IC rejection
jason.taylor at manchester.ac.uk
Fri Nov 30 18:08:22 CET 2018
No, not that I know of. I generally use a hacky combination of SPM, fieldtrip, and EEGLAB functions, but if you've already run ICA, you could accomplish what I suggested with some standard matlab functions.
From: Aitor Egurtzegi [mailto:aitor.martinezegurcegui at uzh.ch]
Sent: 30 November 2018 13:43
To: Jason Taylor; FieldTrip discussion list
Subject: Re: [FieldTrip] automatic IC rejection
Thanks a lot for your reply. Is there a Fieldtrip method already
implemented to run such temporal correlation? or would I have to do the
implementation in raw Matlab?
Thanks in advance,
On 11/30/18 2:05 AM, Jason Taylor wrote:
> Hi Aitor,
> If you have an 'objective' measure of the artefact you're trying to remove (e.g., VEOG for blinks), a relatively straightforward method is to run a temporal correlation between each IC's activation time-course and the artefact channel's time-course. You can then reject any IC with a correlation higher than some threshold, or with a Z-score (r value relative to the distribution of IC r values) above some threshold. This tends to work very well for identifying blinks, and fairly well for eye-movements (*EOG), and can work for pulse artefact if you have recorded ECG. To avoid spurious correlations due to high-frequency noise, you can filter (e.g., 1 to 30 Hz) the component and artefact signals before correlating them (but obviously go back to the original unfiltered signals to continue with your analysis).
> Best wishes,
> -----Original Message-----
> From: fieldtrip [mailto:fieldtrip-bounces at science.ru.nl] On Behalf Of David Schubring
> Sent: 28 November 2018 12:47
> To: fieldtrip at science.ru.nl; aitor.martinezegurcegui at uzh.ch
> Subject: Re: [FieldTrip] automatic IC rejection
> Dear Aitor,
> the closest thing I know of for a data-driven approach of selecting
> independent components is COMPASS, quote:
> "COMPASS is a MATLAB and EEGLAB based algorithm with the purpose of
> providing the user with a convenient technique for automatic Independent
> Component (IC) selection with respect to the contributions of the ICs to
> a certain ERP."
> Link to the toolbox:
> Wessel, J. R., & Ullsperger, M. (2011). Selection of independent
> components representing event-related brain potentials: a data-driven
> approach for greater objectivity. Neuroimage, 54(3), 2105-2115.
> I have only theoretical experience with the toolbox as I only learned
> about it in a workshop and did not yet have the time to test and
> implement it in my personal FieldTrip workflow (even though it is on my
> ever growing to-do list). So far it looked like a useful thing to try
> out to me, especially as code can better be reproduced than "personal
> Am 28.11.2018 um 10:49 schrieb Aitor Egurtzegi:
>> Dear researchers at Fieldtrip,
>> In order to make my work more reproducible, I would like to
>> automatically reject ICs instead of doing visual inspection and
>> rejection of the components. Unfortunately, I haven't found any
>> documentation for such thing. Is there a way to do it in Fieldtrip?
>> fieldtrip mailing list
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