CWL-Webinar

This repository contains the collection of files to get you started with the CWL Artefact correction as outlined in the Carbon Wire Loop EEG-fMRI Webinar. It contains the presentations, the toolbox, information of links and some example data.

The paper with the description of the correction + the dataset can be found here: ()[https://www.sciencedirect.com/science/article/pii/S1053811915009787]

Download EEGLAB
https://sccn.ucsd.edu/eeglab/downloadtoolbox.php

EELAB Extensions
https://sccn.ucsd.edu/eeglab/plugin_uploader/plugin_list_all.php
(but File -> Manage extension would also work)

• FileIO
• BvaIO
• eegplot_w

Download CWL-EEG-fMRI Toolbox (EEGLAB extension)
https://www.nitrc.org/projects/cwl_eeg_fmri/

Download CWL-EEG-fMRI Data (EEG & fMRI Data)
https://www.nitrc.org/projects/cwleegfmri_data/

Requirements

>> ver
-----------------------------------------------------------------------------------------------------
MATLAB Version: 9.3.0.713579 (R2017b)

Operating System: Linux 5.7.10-arch1-1 #1 SMP PREEMPT Wed, 22 Jul 2020 19:57:42 +0000 x86_64
Java Version: Java 1.8.0_121-b13 with Oracle Corporation Java HotSpot(TM) 64-Bit Server VM mixed mode
-----------------------------------------------------------------------------------------------------
MATLAB                                                Version 9.3         (R2017b)
EEGLAB Toolbox to process EEG data                    Version -           see     
Signal Processing Toolbox                             Version 7.5         (R2017b)

Whenever Matlab upgrades, sometimes a routine called by (any) toolbox might not work anymore and things break. I cannot guarantee operation on R2020; but I hope that R2017b is recent enough - it includes fixes for a crash when I upgraded from Matlab 2011b to 2017b.

Workflow

1. Remove MRI Gradient Artifact
   • there are more optimal and less optimal methods (!) I used the 'Bergen EEG-MRI Tooblox' to get rid of the MRI artefacts: ()[http://fmri.uib.no/tools/bergen_plugin.htm]
   • a syncbox is essenial, or if this is lacking; the Method of Sonia Goncalves (Clinical Neuropysioloy, 2007) is probably the best one.
2. Downsample (1000 Hz or 500 Hz are both good for the CWL-correction)
3. Fix the Channel Position(s) (Edit -> Channel Locations)
4. Filterings:
   • low-pass (can try different settings! -- anywhere between 45 - 75)
   • high-pass (can also try different settings -- usually >= 1)
5. Check the signals in the CWLs - do they look good?
6. Run the CWL Correction
7. Rationale for of those parameters
   • windows -> adaptive
   • window Length -> enough to capture some BCGs!
   • delay value -> increases/decreases model fit; might overfit (!)
8. Compare with the situation outside of the MRI scanner and see if you're happy
9. Identify the bad bits (channels/times), take care of those in follow-up.