[FieldTrip] automatic artifact detection and ft_denoise_pca

[Robin]

Hi all,

I am a new fieldtrip user getting started preprocessing a large MEG
data set (I am in Glasgow and the data was collected at CCNi).

I think I am slowly getting to grips with all the steps necessary, but
I have a question about the artifact rejection.

My undersanding is that the denoise procedure helps correct external
sources of noise, so having the signal cleaned in this way should help
detect the biological artifacts which are valid magnetic signal at the
scalp. But I can't see an easy way to do this since the ft_artifact_*
functions want to load the raw continuous data from disk. I can get
them to act on the in memory trials data if I set the padding options
to 0, but then I get an unacceptable amount of rejections (I guess
because of the filter artifacts the padding usually prevents).

Is it possible to run ft_artifact_muscle, ft_artifact_eog etc. on the
denoised signal from ft_denoise_pca and if so how?

At the moment I am performing the following steps:

Load each run
Detect jumps with ft_artifact_jump.
Concatenate the jump-free trials from all runs together for this block.

Visually inspect the reference channels and remove high variance
trials (across the whole block).
Compute denoise PCA weights using only good reference data (and no MEG
jump) trials across the whole block.

I would now like to apply the denoise PCA weights, perform other
automatic artifact removal on the cleaned data, before further visual
inspection and the next steps of ICA etc.

Is there any problems with this strategy?

Thanks in advance for any advice,

Robin