[Mne_analysis] Automatic Component Artefact Removal with EEG

[Denis-Alexander Engemann]

Hi,

This is correct. You can also use the corrmap approach to match EOG
components. We have some local Python implementations of ADJUST and FASTER
that we would not mind sharing if there is interest in this and would
facilitate adopting MNE-Python.

Cheers,
Denis

On Wed, Oct 12, 2016 at 2:16 PM Ben McCartney <bmccartney06 at qub.ac.uk>
wrote:









Hello,




We have been using EEGLAB to run preprocessing over our EEG data before
analysing it with Python, and recently we began looking into MNE as an
alternative for the preprocessing step. We were using ICA to detect and
automatically remove EOG components using
EEGLAB's Binica, along with FASTER and ADJUST. From a quick read through
the MNE docs it looks like we could get similar behaviour if we ran the ICA
in MNE, then used the find_bads_eog or detect_artifacts function to
identify noisy components. Is this the
correct approach? Note that we do not have any dedicated EOG channels in
our data, would either approach work fine just using a forehead electrode
location (like Fpz)?




Thanks,

Ben







_______________________________________________

Mne_analysis mailing list

Mne_analysis at nmr.mgh.harvard.edu

https://mail.nmr.mgh.harvard.edu/mailman/listinfo/mne_analysis





The information in this e-mail is intended only for the person to whom it is

addressed. If you believe this e-mail was sent to you in error and the
e-mail

contains patient information, please contact the Partners Compliance
HelpLine at

http://www.partners.org/complianceline . If the e-mail was sent to you in
error

but does not contain patient information, please contact the sender and
properly

dispose of the e-mail.
-------------- next part --------------
An HTML attachment was scrubbed...
URL: http://mail.nmr.mgh.harvard.edu/pipermail/mne_analysis/attachments/20161012/4f38e8b2/attachment.html