[Mne_analysis] CSD might break montage

[Eric Larson]

        External Email - Use Caution        

The topomaps in the example don't show this problem, at least for
plot_topomap:

https://mne.tools/dev/auto_examples/preprocessing/plot_eeg_csd.html#sphx-glr-auto-examples-preprocessing-plot-eeg-csd-py

First, it's worth trying latest
<https://mne.tools/dev/install/advanced.html#using-the-development-version-of-mne-python-latest-master>
`master` branch rather than 0.20.x to see if we have fixed it already.

If that doesn't work, can you see if you can reproduce on the `sample`
dataset by modifying the example above? If not, there might be something
about your data in particular -- if you can turn this into some tiny script
(probably gist <https://gist.github.com/>) to demonstrate the problem and
share your data someone can take a look.

Eric


On Wed, Jun 24, 2020 at 9:35 AM Gabriel Weindel <gabriel.weindel at gmail.com>
wrote:

>         External Email - Use Caution
>
> Hello all,
>
> I am applying CSD to my epoched data and want to compare the
> distributions of the ERPs on the scalp before and after surface laplacian.
>
> epochs_csd = mne.preprocessing.compute_current_source_density(epochs)
>
> I use : mne.viz.plot_compare_evokeds([epochs.average()], picks='eeg',
> axes='topo')
> To plot before CSD, everything works fine but then I use :
> mne.viz.plot_compare_evokeds([epochs_csd.average()], picks='csd',
> axes='topo')
> And then the channel order is preserved but the cartoon head is shrinked
> to the lower left of the figure (see attached) making it impossible to
> read.
>
> I am assuming that the montage is lost in the csd transform as
> epoch.info prints me :
> <Info | 11 non-empty values
>   bads: []
>   ch_names: Fp1, AF7, AF3, F1, F3, F5, F7, FT7, FC5, FC3, FC1, C1, C3,
> C5, ...
>   chs: 64 EEG
>   custom_ref_applied: True
>   dig: 712 items (3 Cardinal, 64 EEG, 645 Extra)
>   file_id: 4 items (dict)
>   highpass: 0.0 Hz
>   lowpass: 40.0 Hz
>   meas_date: 2019-06-06 11:46:59 UTC
>   meas_id: 4 items (dict)
>   nchan: 64
>   projs: []
>   sfreq: 1000.0 Hz
>  >
>
> and epochs_csd.info :
>
> <Info | 11 non-empty values
>   bads: []
>   ch_names: Fp1, AF7, AF3, F1, F3, F5, F7, FT7, FC5, FC3, FC1, C1, C3,
> C5, ...
>   chs: 64 CSD
>   custom_ref_applied: True
>   dig: 712 items (3 Cardinal, 64 EEG, 645 Extra)
>   file_id: 4 items (dict)
>   highpass: 0.0 Hz
>   lowpass: 40.0 Hz
>   meas_date: 2019-06-06 11:46:59 UTC
>   meas_id: 4 items (dict)
>   nchan: 64
>   projs: []
>   sfreq: 1000.0 Hz
>  >
>
> Is there a quick workaround ?
>
> Best,
> Gabriel
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