[Eeglablist] Pipeline questions

Armand Hoxha - Volunteer AHoxha at kesslerfoundation.org
Thu Oct 22 06:58:24 PDT 2015

Dear EEGLAB community,

I am currently working on a dataset from which I need to get Beta band coherence (motor cortex to muscle coupling). My processing pipeline for the dataset so far has been:

1-     Import data

2-     Add channels, Optimize Center, Set channel types

3-     Cleanline (default settings, to EEG and EMG)

4-     FIR 1-250Hz (pop_eegfiltnew, to EEG and EMG)

5-     Segment data in epochs (0.5 seconds of epochs, for coherence purposes I noticed in most studies the general number of windows is usually above 170, thus to achieve the same statistical relevance I needed to have windows of 0.5s rather than 1second. I am a little confused about which window length should be preferred for beta band coherence)

6-     Remove noisy channel (if more than 10% of data is "bad", then I remove channel)
6a)pop_eegthresh on EEG channels, with limits of -50 to 50 uV
6b)pop_jointprob on EEG channels, single-channel std:6, All-channel std:2
if a channel is generally responsible for about 10% of rejected epochs, I reject channel

7-     Interpolate rejected channels, pop_interp ;Spherical method

8-     Average reference EEG channels(for ICA and coherence calculations, our actual reference is between FCZ and CZ)

9-     Run ICA on EEG channels only ( I have read that EOG and ECG channels can be included, but they are bipolar readings with a different reference from EEG, should I include them regardless?

10-  Use MARA toolbox to get a general sense of how I should feel about some IC's , also because I prefer the MARA spectrum plot over the default GUI

11-  Reject IC components related to EMG artifacts (facial movements, neck, jaw, eyes), from 64 components I reject ~20

12-  Reject epochs based on the Components (jointprob 6,2)

13-  Run ICA again, reject EMG components again

14-  Most of the time by this point I have retained ~75-85% of dataset, and I use this dataset to do coherence analysis. I have read that some have suggested instead to export the ICA matrix of the processed data, and apply it to the raw data?

Am I rejecting too many IC's from the data, or would this data produce reliable results?

Thanks in advance,

Armand Hoxha
Biomedical Engineer, HPEL
Kessler Foundation
1199 Pleasant Valley Way, West Orange, NJ 07052

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