[Mne_analysis] Questions about ICA

[Denis-Alexander Engemann]

Dear Maria,

I'm replying on mne_analysis so other people can join in or follow our
conversation. Please join if you haven't already (
https://mail.nmr.mgh.harvard.edu/mailman/listinfo/MNE_Analysis)


On Sun, Aug 3, 2014 at 10:21 AM, Hakonen Maria <maria.hakonen at aalto.fi>
wrote:
>
> Hi Denis,
>
> I would yet need noise covariance matrixes for roi analysis. I have
calculated them with EOG rejections using mne_process_raw as shown below. I
wonder if it causes problems if the noise covariance matrixes are
claculated with EOG rejections but averaged signals are calculated without
EOG rejections (and ica is applied on epochs).


I would not see why that would be a problem, it's a good ideat to not
estimate the covariance matrix on biological artefacts. Don't you use ICA
for handling EOG/ECG? Should be fine then.
What I normally do is to compute the noise covariance after applying ICA.
That makes things even more matching, e.g., also applying the same amount
of rank reduction.

>
> I can't use rejections because in the sustained field analysis long
epochs cause too many rejections. For transient analysis whit shorter
epochs EOG rejections worked well. Should I calculate new covariance
matrixes for sustained field analysis using data where EOG rejections are
not used but ica is applied instead? Any advice would help a lot!
>

Would it make sense to compute your noise cov from preceeding baseline
segments?
Then you couls simplify things a bit.
Apply ICA to your epochs and then use `mne.compute_covariance` on your
epochs.
FYI in there's also  `mne.compute_raw_data_covariance` for raw data.

>
> This is how I have calculated covariance matrixes:
>
> foreach file ( ah_sentences1b ah_sentences16b ah_sentences1b2 )
>         mne_process_raw --raw "$file"_raw.fif \
>         --digtrig "STI 014" --grad 0 --projon --events "$file"_merged.eve
\
>         --cov
/scratch/braindata/mhhakone/intell/scripts/cov_desc_merged.cov --savecovtag
"-merged.cov"
> end
>
> where cov_desc_merged.cov:
>
> cov {
>         name            "intell"
>
>         gradReject      3000e-13
>         magReject       4e-12
>         eogReject       150e-6
>         logfile         log_averaging
>
>         def {
>                 name    "all"
>                 event   1
>                 tmin    -0.1
>                 tmax    0
>                 bmin    -0.1
>                 bmax    0
>         }
>
> }
>
> Thanks,
> Maria
>

Hope this helps,
Denis
-------------- next part --------------
An HTML attachment was scrubbed...
URL: http://mail.nmr.mgh.harvard.edu/pipermail/mne_analysis/attachments/20140804/86bee43c/attachment.html