Comments (2)
Prep gives you the options to do it either way. The relevant options are:
in the Reference stage: the 'interpolationOrder' parameter controls when and if interpolation is performed. (The default is Post-reference, but you would want None. Pre-reference is not recommended. It is there for benchmarking purposes.). The options are:
post-reference: bad channels are detected again and interpolated after referencing
pre-reference: bad channels detected before referencing and interpolated
none: no interpolation is performed
In the Post process section, there is also an option: removeInterpolatedChannels which if true If true, removes channels interpolated by Prep.
As far as whether you should or not, I don't have a definitive answer on that. I have done it both ways depending on what I am doing. This is something that deserves more benchmarking. If you use the interpolated channels, you have to use PCA to reduce the dimension on the interpolated data. My sense is that this does a better job of capturing spatial variability more consistently especially when you are comparing across a lot of datasets.
On a side note, if using ASR for artifact removal, you absolutely cannot interpolate channels or the method blows up. ASR does seem to do slightly better if you remove bad channels as detected by PREP and then apply ASR. Again, this would need more systematic benchmarking to cast as a "rule".
from eeg-clean-tools.
@VisLab , is the none: no interpolation is performed
still available in latest version. I notice this option is not available for version0.55.4
. There are option for post-reference
and pre-reference
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Related Issues (20)
- adding back online reference
- restoreEEGOptions not quite working correctly HOT 1
- struct2str getNumerical HOT 2
- Change to EEGLAB options HOT 1
- Change name of findpeaks
- Print out errors on command line when verbose option is set HOT 1
- Should I do the channel location first? HOT 7
- should I do a low pass filter and another rereference after PREP, before ICA?
- Add reference information in EEG struct after PREP
- Crash on movefile in publishPrepReport HOT 4
- Minimum of three iterations in robust re-reference? HOT 2
- Error using cleanLineNoise (line 57) HOT 3
- Bad-by-dropout channels ignored during re-referencing? HOT 5
- Why is EEGlab PREP not flagging up EEG files as "problematic" if the number of interpolated channels is > 25%? HOT 1
- Out of memory error HOT 3
- Channel locations missing after the pipeline
- Computation of windowSize based on detrendCutoff in localDetrend HOT 7
- PyPrep Noisy Channel Parameters
- Keep receiving errors when running the PREPpipeline
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